def _load_bids(ctx, bids_dir):
layout = BIDSLayout(bids_dir, absolute_paths=True)
other_entities = ["datatype", "extension", "suffix"]
# load
anatfiles = layout.get(return_type="filename",
datatype="anat",
suffix="T1w")
anat_pattern_set = _get_pattern_set(
layout,
anatfiles,
["subject"],
other_entities,
[],
)
_load_part(ctx, BIDSAnatTagsSchema(), anat_pattern_set)
funcfiles = layout.get(return_type="filename",
datatype="func",
suffix="bold")
func_pattern_set = _get_pattern_set(
layout,
funcfiles,
["subject", "session", "run", "task"],
other_entities,
["RepetitionTime", "PhaseEncodingDirection", "EffectiveEchoSpacing"],
)
_load_part(ctx, BIDSBoldTagsSchema(), func_pattern_set)
eventfiles = layout.get(return_type="filename",
datatype="func",
suffix="events",
extension="tsv")
events_pattern_set = _get_pattern_set(
layout,
eventfiles,
["subject", "session", "run", "task"],
other_entities,
[],
)
_load_part(ctx, BIDSEventsTagsSchema(), events_pattern_set)
fmap_pattern_set = _get_fmap_pattern_set(
layout,
funcfiles,
["subject", "session", "run", "task"],
other_entities,
["PhaseEncodingDirection", "EchoTimeDifference", "EchoTime"],
)
_load_part(ctx, BIDSFmapTagsSchema(), fmap_pattern_set)
participantsfilepath = op.join(bids_dir, "participants.tsv")
if op.isfile(participantsfilepath):
ctx.spreadsheet_file = participantsfilepath
# validate
funcfiles = ctx.database.get(
datatype="func",
suffix="bold") # only validate files that made it to the database
for funcfile in funcfiles:
bidsfmapset = set()
fmapslist = layout.get_fieldmap(funcfile, return_list=True)
for fmaps in fmapslist:
for fmapfile in fmaps.values():
if not op.isfile(fmapfile):
continue
bidsfmapset.add(fmapfile)
fmapfiles = ctx.database.get_associations(funcfile, datatype="fmap")
if fmapfiles is not None:
specfmapset = set(fmapfiles)
assert bidsfmapset == specfmapset, "Inconsistent FieldMap specification"
def main(sourcedata,
derivatives,
tmp_dir,
subject=None,
acquisition=None,
session=None,
run=None):
if run is []:
run = '[0-9]+'
if subject in ['04', '01']:
dof = 9
else:
dof = 6
layout = BIDSLayout(sourcedata)
derivatives_layout = BIDSLayout(derivatives)
dtissue_left = get_derivative(derivatives,
'nighres',
'anat',
subject,
'dseg',
hemi='left',
space='average',
description='cortex',
session='anat')
dtissue_right = get_derivative(derivatives,
'nighres',
'anat',
subject,
'dseg',
hemi='right',
space='average',
description='cortex',
session='anat')
dura = get_dura_mask(derivatives, subject, 'average', 'anat')
get_wm_wf = get_wm_seg_from_nighres(dtissue_left, dtissue_right)
bold = []
bold = layout.get(subject=subject,
session=session,
run=run,
acquisition=acquisition,
suffix='bold',
return_type='file')
print(bold)
epi = []
for b in bold:
fmaps = layout.get_fieldmap(b, return_list=True)
for fmap in fmaps:
if ('type' not in fmap) or (fmap['type'] == 'epi'):
break
epi.append(fmap['epi'])
print('Using {} as epi_op for {}'.format(fmap['epi'], b))
print(epi)
t1w = get_derivative(derivatives,
'masked_mp2rages',
'anat',
subject,
'T1w',
session='anat',
space='average',
description='masked',
extension='nii.gz')
print(t1w, os.path.exists(t1w))
init_matrix = get_derivative(derivatives,
'manual_transformations',
'func',
subject,
'transform',
session=session,
space='average',
extension='mat')
os.environ['SUBJECTS_DIR'] = op.join(derivatives, 'freesurfer')
wf = init_hires_unwarping_wf(
name="unwarp_hires_{}_{}_{}".format(subject, session, acquisition),
method='topup',
bids_layout=layout,
single_warpfield=False,
register_to='last',
init_transform=init_matrix,
linear_registration_parameters='linear_hires.json',
nonlinear_registration_parameters='nonlinear_precise.json',
bold=bold,
epi_op=epi,
t1w_epi=None,
t1w=t1w,
dura_mask=dura,
wm_seg=True,
inv2_epi=None,
dof=dof,
crop_bolds=True,
topup_package='afni',
epi_to_t1_package='fsl',
highpass_filter=True,
within_epi_reg=True,
freesurfer_subject_id='sub-{}'.format(subject),
polish=True,
num_threads_ants=4)
wf.connect(get_wm_wf, 'outputspec.wm_seg', wf.get_node('inputspec'),
'wm_seg')
wf.base_dir = tmp_dir
wf.run(plugin='MultiProc', plugin_args={'n_procs': 8})