Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.
# option was called without any output spaces, so user does not want outputs
spaces.checkpoint()
for val in values:
val = val.rstrip(":")
if (
val not in NONSTANDARD_REFERENCES
and not val.split(":")[0].startswith("fs")
and ":res-" not in val
and ":resolution-" not in val
):
# by default, explicitly set volumetric resolution to native
# relevant discussions:
# https://github.com/nipreps/niworkflows/pull/457#discussion_r375510227
# https://github.com/nipreps/niworkflows/pull/494
val = ":".join((val, "res-native"))
for sp in Reference.from_string(val):
spaces.add(sp)
setattr(namespace, self.dest, spaces)
def init_spaces(checkpoint=True):
"""Initialize the :attr:`~workflow.spaces` setting."""
from niworkflows.utils.spaces import Reference, SpatialReferences
spaces = execution.output_spaces or SpatialReferences()
if not isinstance(spaces, SpatialReferences):
spaces = SpatialReferences(
[ref for s in spaces.split(" ") for ref in Reference.from_string(s)]
)
if checkpoint and not spaces.is_cached():
spaces.checkpoint()
# Make the SpatialReferences object available
workflow.spaces = spaces
Non-standard spaces imply specific orientations and sampling grids. \
The default value of this flag (meaning, if the argument is not include in the command line) \
is ``--output-spaces run`` - the original space and sampling grid of the original DWI run. \
Important to note, the ``res-*`` modifier does not define the resolution used for \
the spatial normalization. To generate no DWI outputs (if that is intended for some reason), \
use this option without specifying any spatial references. For further details, please check out \
https://www.nipreps.org/dmriprep/en/%s/spaces.html"""
% (currentv.base_version if is_release else "latest"),
)
# ANTs options
g_ants = parser.add_argument_group("Specific options for ANTs registrations")
g_ants.add_argument(
"--skull-strip-template",
default="OASIS30ANTs",
type=Reference.from_string,
help="select a template for skull-stripping with antsBrainExtraction",
)
g_ants.add_argument(
"--skull-strip-fixed-seed",
action="store_true",
help="do not use a random seed for skull-stripping - will ensure "
"run-to-run replicability when used with --omp-nthreads 1",
)
# Fieldmap options
g_fmap = parser.add_argument_group("Specific options for handling fieldmaps")
g_fmap.add_argument(
"--fmap-bspline",
action="store_true",
default=False,
help="fit a B-Spline field using least-squares (experimental)",
g_perfm.add_argument("-v", "--verbose", dest="verbose_count", action="count", default=0,
help="increases log verbosity for each occurence, debug level is -vvv")
g_conf = parser.add_argument_group('Workflow configuration')
g_conf.add_argument(
'--output-spaces', nargs='*', action=OutputReferencesAction, default=SpatialReferences(),
help='paths or keywords prescribing output spaces - '
'standard spaces will be extracted for spatial normalization.')
g_conf.add_argument(
'--longitudinal', action='store_true',
help='treat dataset as longitudinal - may increase runtime')
# ANTs options
g_ants = parser.add_argument_group('Specific options for ANTs registrations')
g_ants.add_argument(
'--skull-strip-template', default='OASIS30ANTs', type=Reference.from_string,
help='select a template for skull-stripping with antsBrainExtraction')
g_ants.add_argument('--skull-strip-fixed-seed', action='store_true',
help='do not use a random seed for skull-stripping - will ensure '
'run-to-run replicability when used with --omp-nthreads 1')
g_ants.add_argument(
'--skull-strip-mode', action='store', choices=('auto', 'skip', 'force'),
default='auto', help='determiner for T1-weighted skull stripping (force ensures skull '
'stripping, skip ignores skull stripping, and auto automatically '
'ignores skull stripping if pre-stripped brains are detected).')
# FreeSurfer options
g_fs = parser.add_argument_group('Specific options for FreeSurfer preprocessing')
g_fs.add_argument(
'--fs-license-file', metavar='PATH', type=Path,
help='Path to FreeSurfer license key file. Get it (for free) by registering'
' at https://surfer.nmr.mgh.harvard.edu/registration.html')