def main():
parser = _build_arg_parser()
args = parser.parse_args()
assert_inputs_exist(parser, [args.tractogram])
assert_outputs_exist(parser, args, [], [args.save])
tracts_format = detect_format(args.tractogram)
if tracts_format is not TrkFile:
raise ValueError("Invalid input streamline file format " +
"(must be trk): {0}".format(args.tractogram_filename))
# Load files and data. TRKs can have 'same' as reference
tractogram = load_tractogram(args.tractogram, 'same')
# Streamlines are saved in RASMM but seeds are saved in VOX
# This might produce weird behavior with non-iso
tractogram.to_vox()
streamlines = tractogram.streamlines
if 'seeds' not in tractogram.data_per_streamline:
parser.error('Tractogram does not contain seeds')
seeds = tractogram.data_per_streamline['seeds']
# Make display objects
streamlines_actor = actor.line(streamlines)
points = actor.dots(seeds, color=(1., 1., 1.))
# Add display objects to canvas
s = window.Scene()
s.add(streamlines_actor)
s.add(points)
# Show and record if needed
if args.save is not None:
window.record(s, out_path=args.save, size=(1000, 1000))
window.show(s)
def main():
parser = _build_args_parser()
args = parser.parse_args()
assert_inputs_exist(parser, [args.tractogram])
assert_outputs_exist(parser, args, [], [args.save])
tracts_format = detect_format(args.tractogram)
if tracts_format is not TrkFile:
raise ValueError("Invalid input streamline file format " +
"(must be trk): {0}".format(args.tractogram_filename))
# Load files and data
trk = TrkFile.load(args.tractogram)
tractogram = trk.tractogram
streamlines = tractogram.streamlines
if 'seeds' not in tractogram.data_per_streamline:
parser.error('Tractogram does not contain seeds')
seeds = tractogram.data_per_streamline['seeds']
# Make display objects
streamlines_actor = actor.line(streamlines)
points = actor.dots(seeds, color=(1., 1., 1.))
# Add display objects to canvas
r = window.Renderer()
r.add(streamlines_actor)
r.add(points)
# Show and record if needed
if args.save is not None:
window.record(r, out_path=args.save, size=(1000, 1000))
window.show(r)
def save_tractogram(fname,
streamlines,
affine,
vox_size=None,
shape=None,
header=None,
reduce_memory_usage=False,
tractogram_file=None):
""" Saves tractogram files (*.trk or *.tck or *.dpy)
Parameters
----------
fname : str
output trk filename
streamlines : list of 2D arrays, generator or ArraySequence
Each 2D array represents a sequence of 3D points (points, 3).
affine : array_like (4, 4)
The mapping from voxel coordinates to streamline points.
vox_size : array_like (3,), optional
The sizes of the voxels in the reference image (default: None)
shape : array, shape (dim,), optional
The shape of the reference image (default: None)
header : dict, optional
Metadata associated to the tractogram file(*.trk). (default: None)
reduce_memory_usage : {False, True}, optional
If True, save streamlines in a lazy manner i.e. they will not be kept
in memory. Otherwise, keep all streamlines in memory until saving.
tractogram_file : class TractogramFile, optional
Define tractogram class type (TrkFile vs TckFile)
Default is None which means auto detect format
"""
if 'dpy' in os.path.splitext(fname)[1].lower():
dpw = Dpy(fname, 'w')
dpw.write_tracks(Streamlines(streamlines))
dpw.close()
return
tractogram_file = tractogram_file or detect_format(fname)
if tractogram_file is None:
raise ValueError("Unknown format for 'fname': {}".format(fname))
if vox_size is not None and shape is not None:
if not isinstance(header, dict):
header = {}
header[Field.VOXEL_TO_RASMM] = affine.copy()
header[Field.VOXEL_SIZES] = vox_size
header[Field.DIMENSIONS] = shape
header[Field.VOXEL_ORDER] = "".join(aff2axcodes(affine))
if reduce_memory_usage and not callable(streamlines):
sg = lambda: (s for s in streamlines)
else:
sg = streamlines
tractogram_loader = LazyTractogram if reduce_memory_usage else Tractogram
tractogram = tractogram_loader(sg)
tractogram.affine_to_rasmm = affine
track_file = tractogram_file(tractogram, header=header)
nib.streamlines.save(track_file, fname)
def save_tractogram(fname, streamlines, affine, vox_size=None, shape=None,
header=None, reduce_memory_usage=False,
tractogram_file=None):
""" Saves tractogram files (*.trk or *.tck or *.dpy)
Parameters
----------
fname : str
output trk filename
streamlines : list of 2D arrays, generator or ArraySequence
Each 2D array represents a sequence of 3D points (points, 3).
affine : array_like (4, 4)
The mapping from voxel coordinates to streamline points.
vox_size : array_like (3,), optional
The sizes of the voxels in the reference image (default: None)
shape : array, shape (dim,), optional
The shape of the reference image (default: None)
header : dict, optional
Metadata associated to the tractogram file(*.trk). (default: None)
reduce_memory_usage : {False, True}, optional
If True, save streamlines in a lazy manner i.e. they will not be kept
in memory. Otherwise, keep all streamlines in memory until saving.
tractogram_file : class TractogramFile, optional
Define tractogram class type (TrkFile vs TckFile)
Default is None which means auto detect format
"""
if 'dpy' in os.path.splitext(fname)[1].lower():
dpw = Dpy(fname, 'w')
dpw.write_tracks(Streamlines(streamlines))
dpw.close()
return
tractogram_file = tractogram_file or detect_format(fname)
if tractogram_file is None:
raise ValueError("Unknown format for 'fname': {}".format(fname))
if vox_size is not None and shape is not None:
if not isinstance(header, dict):
header = {}
header[Field.VOXEL_TO_RASMM] = affine.copy()
header[Field.VOXEL_SIZES] = vox_size
header[Field.DIMENSIONS] = shape
header[Field.VOXEL_ORDER] = "".join(aff2axcodes(affine))
if reduce_memory_usage and not callable(streamlines):
sg = lambda: (s for s in streamlines)
else:
sg = streamlines
tractogram_loader = LazyTractogram if reduce_memory_usage else Tractogram
tractogram = tractogram_loader(sg)
tractogram.affine_to_rasmm = affine
track_file = tractogram_file(tractogram, header=header)
nib.streamlines.save(track_file, fname)
def create_tractogram_header(tractogram_type, affine, dimensions, voxel_sizes,
voxel_order):
""" Write a standard trk/tck header from spatial attribute """
if isinstance(tractogram_type, str):
tractogram_type = detect_format(tractogram_type)
new_header = tractogram_type.create_empty_header()
new_header[nib.streamlines.Field.VOXEL_SIZES] = tuple(voxel_sizes)
new_header[nib.streamlines.Field.DIMENSIONS] = tuple(dimensions)
new_header[nib.streamlines.Field.VOXEL_TO_RASMM] = affine
new_header[nib.streamlines.Field.VOXEL_ORDER] = voxel_order
return new_header
def main():
parser = _build_arg_parser()
args = parser.parse_args()
assert_inputs_exist(parser, [args.tractogram_filename])
assert_outputs_exist(parser, args, [args.seed_density_filename])
tracts_format = detect_format(args.tractogram_filename)
if tracts_format is TckFile:
raise ValueError("Invalid input streamline file format " +
"(must be trk): {0}".format(args.tractogram_filename))
max_ = np.iinfo(np.int16).max
if args.binary is not None and (args.binary <= 0 or args.binary > max_):
parser.error(
'The value of --binary ({}) '
'must be greater than 0 and smaller or equal to {}'.format(
args.binary, max_))
# Load tractogram and load seeds
tracts_file = load(args.tractogram_filename, args.lazy_load)
if 'seeds' in tracts_file.tractogram.data_per_streamline:
seeds = tracts_file.tractogram.data_per_streamline['seeds']
else:
parser.error('Tractogram does not contain seeds')
# Transform seeds if they're all in memory
if not args.lazy_load:
seeds = apply_affine(np.linalg.inv(tracts_file.affine), seeds)
# Create seed density map
shape = tracts_file.header[Field.DIMENSIONS]
seed_density = np.zeros(shape, dtype=np.int32)
for seed in seeds:
# If seeds are lazily loaded, we have to transform them
# as they get loaded
if args.lazy_load:
seed = apply_affine(np.linalg.inv(tracts_file.affine), seed)
# Set value at mask, either binary or increment
seed_voxel = np.round(seed).astype(np.int)
if args.binary is not None:
seed_density[tuple(seed_voxel)] = args.binary
else:
seed_density[tuple(seed_voxel)] += 1
# Save seed density map
dm_img = Nifti1Image(seed_density.astype(np.int32), tracts_file.affine)
dm_img.to_filename(args.seed_density_filename)
def main():
parser = _build_arg_parser()
args = parser.parse_args()
assert_inputs_exist(parser, [args.tractogram_filename])
assert_outputs_exist(parser, args, [args.seed_density_filename])
tracts_format = detect_format(args.tractogram_filename)
if tracts_format is not TrkFile:
raise ValueError("Invalid input streamline file format " +
"(must be trk): {0}".format(args.tractogram_filename))
max_ = np.iinfo(np.int16).max
if args.binary is not None and (args.binary <= 0 or args.binary > max_):
parser.error(
'The value of --binary ({}) '
'must be greater than 0 and smaller or equal to {}'.format(
args.binary, max_))
# Load files and data. TRKs can have 'same' as reference
# Can handle streamlines outside of bbox
sft = load_tractogram(args.tractogram_filename,
'same',
bbox_valid_check=False)
# Streamlines are saved in RASMM but seeds are saved in VOX
# This might produce weird behavior with non-iso
sft.to_vox()
sft.to_corner()
if 'seeds' in sft.data_per_streamline:
seeds = sft.data_per_streamline['seeds']
else:
parser.error('Tractogram does not contain seeds')
# Create seed density map
_, shape, _, _ = sft.space_attributes
seed_density = np.zeros(shape, dtype=np.int32)
for seed in seeds:
# Set value at mask, either binary or increment
seed_voxel = np.round(seed).astype(int)
if args.binary is not None:
seed_density[tuple(seed_voxel)] = args.binary
else:
seed_density[tuple(seed_voxel)] += 1
# Save seed density map
dm_img = Nifti1Image(seed_density.astype(np.int32), sft.affine)
dm_img.to_filename(args.seed_density_filename)
def save_tractogram(sft, filename, bbox_valid_check=True):
""" Save the stateful tractogram in any format (trk, tck, vtk, fib, dpy)
Parameters
----------
sft : StatefulTractogram
The stateful tractogram to save
filename : string
Filename with valid extension
bbox_valid_check : bool
Verification for negative voxel coordinates or values above the
volume dimensions. Default is True, to enforce valid file.
Returns
-------
output : bool
True if the saving operation was successful
"""
_, extension = os.path.splitext(filename)
if extension not in ['.trk', '.tck', '.vtk', '.fib', '.dpy']:
raise TypeError('Output filename is not one of the supported format')
if bbox_valid_check and not sft.is_bbox_in_vox_valid():
raise ValueError('Bounding box is not valid in voxel space, cannot ' +
'load a valid file if some coordinates are ' +
'invalid. Please use the function ' +
'remove_invalid_streamlines to discard invalid ' +
'streamlines or set bbox_valid_check to False')
old_space = deepcopy(sft.space)
old_shift = deepcopy(sft.shifted_origin)
sft.to_rasmm()
sft.to_center()
timer = time.time()
if extension in ['.trk', '.tck']:
tractogram_type = detect_format(filename)
header = create_tractogram_header(tractogram_type,
*sft.space_attributes)
new_tractogram = Tractogram(sft.streamlines, affine_to_rasmm=np.eye(4))
if extension == '.trk':
new_tractogram.data_per_point = sft.data_per_point
new_tractogram.data_per_streamline = sft.data_per_streamline
fileobj = tractogram_type(new_tractogram, header=header)
nib.streamlines.save(fileobj, filename)
elif extension in ['.vtk', '.fib']:
save_vtk_streamlines(sft.streamlines, filename, binary=True)
elif extension in ['.dpy']:
dpy_obj = Dpy(filename, mode='w')
dpy_obj.write_tracks(sft.streamlines)
dpy_obj.close()
logging.debug('Save %s with %s streamlines in %s seconds', filename,
len(sft), round(time.time() - timer, 3))
if old_space == Space.VOX:
sft.to_vox()
elif old_space == Space.VOXMM:
sft.to_voxmm()
if old_shift:
sft.to_corner()
return True
def save_tractogram(sft, filename, bbox_valid_check=True):
""" Save the stateful tractogram in any format (trk, tck, vtk, fib, dpy)
Parameters
----------
sft : StatefulTractogram
The stateful tractogram to save
filename : string
Filename with valid extension
Returns
-------
output : bool
Did the saving work properly
"""
_, extension = os.path.splitext(filename)
if extension not in ['.trk', '.tck', '.vtk', '.fib', '.dpy']:
TypeError('Output filename is not one of the supported format')
if bbox_valid_check and not sft.is_bbox_in_vox_valid():
raise ValueError('Bounding box is not valid in voxel space, cannot ' +
'save a valid file if some coordinates are invalid')
old_space = deepcopy(sft.space)
old_shift = deepcopy(sft.shifted_origin)
sft.to_rasmm()
sft.to_center()
timer = time.time()
if extension in ['.trk', '.tck']:
tractogram_type = detect_format(filename)
header = create_tractogram_header(tractogram_type,
*sft.space_attribute)
new_tractogram = Tractogram(sft.streamlines,
affine_to_rasmm=np.eye(4))
if extension == '.trk':
new_tractogram.data_per_point = sft.data_per_point
new_tractogram.data_per_streamline = sft.data_per_streamline
fileobj = tractogram_type(new_tractogram, header=header)
nib.streamlines.save(fileobj, filename)
elif extension in ['.vtk', '.fib']:
save_vtk_streamlines(sft.streamlines, filename, binary=True)
elif extension in ['.dpy']:
dpy_obj = Dpy(filename, mode='w')
dpy_obj.write_tracks(sft.streamlines)
dpy_obj.close()
logging.debug('Save %s with %s streamlines in %s seconds',
filename, len(sft), round(time.time() - timer, 3))
if old_space == Space.VOX:
sft.to_vox()
elif old_space == Space.VOXMM:
sft.to_voxmm()
if old_shift:
sft.to_corner()
return True
