class SubjectSummaryInputSpec(BaseInterfaceInputSpec):
t1w = InputMultiPath(File(exists=True), desc='T1w structural images')
t2w = InputMultiPath(File(exists=True), desc='T2w structural images')
subjects_dir = Directory(desc='FreeSurfer subjects directory')
subject_id = Str(desc='Subject ID')
bold = traits.List(desc='BOLD functional series')
output_spaces = traits.List(desc='Target spaces')
template = traits.Enum('MNI152NLin2009cAsym', desc='Template space')
class FSDetectInputsInputSpec(BaseInterfaceInputSpec):
t1w_list = InputMultiPath(File(exists=True),
mandatory=True,
desc='input file, part of a BIDS tree')
t2w_list = InputMultiPath(File(exists=True),
desc='input file, part of a BIDS tree')
hires_enabled = traits.Bool(True,
usedefault=True,
desc='enable hi-resolution processing')
class FirstEchoInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(File(exists=True),
mandatory=True,
minlen=2,
desc='multi-echo BOLD EPIs')
ref_imgs = InputMultiPath(File(exists=True),
mandatory=True,
minlen=2,
desc='generated reference image for each '
'multi-echo BOLD EPI')
te_list = traits.List(traits.Float, mandatory=True, desc='echo times')
class IntraModalMergeInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(File(exists=True),
mandatory=True,
desc='input files')
hmc = traits.Bool(True, usedefault=True)
zero_based_avg = traits.Bool(True, usedefault=True)
to_ras = traits.Bool(True, usedefault=True)
class TemplateDimensionsInputSpec(BaseInterfaceInputSpec):
t1w_list = InputMultiPath(File(exists=True),
mandatory=True,
desc='input T1w images')
max_scale = traits.Float(3.0,
usedefault=True,
desc='Maximum scaling factor in images to accept')
class DerivativesDataSinkInputSpec(BaseInterfaceInputSpec):
base_directory = traits.Directory(
desc='Path to the base directory for storing data.')
in_file = InputMultiPath(File(exists=True), mandatory=True,
desc='the object to be saved')
source_file = File(exists=False, mandatory=True, desc='the input func file')
suffix = traits.Str('', mandatory=True, desc='suffix appended to source_file')
extra_values = traits.List(traits.Str)
class T2SMapInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(File(exists=True),
mandatory=True,
desc='multi-echo BOLD EPIs')
te_list = traits.List(traits.Float, mandatory=True, desc='echo times')
compress = traits.Bool(True,
usedefault=True,
desc='use gzip compression on .nii output')
class CombineROIsInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(File(exists=True),
mandatory=True,
desc='input list of ROIs')
ref_header = File(
exists=True,
mandatory=True,
desc='reference NIfTI file with desired output header/affine')
class MCFLIRT2ITKInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(File(exists=True), mandatory=True,
desc='list of MAT files from MCFLIRT')
in_reference = File(exists=True, mandatory=True,
desc='input image for spatial reference')
in_source = File(exists=True, mandatory=True,
desc='input image for spatial source')
num_threads = traits.Int(1, usedefault=True, nohash=True,
desc='number of parallel processes')
class MultiApplyTransformsInputSpec(ApplyTransformsInputSpec):
input_image = InputMultiPath(File(exists=True), mandatory=True,
desc='input time-series as a list of volumes after splitting'
' through the fourth dimension')
num_threads = traits.Int(1, usedefault=True, nohash=True,
desc='number of parallel processes')
save_cmd = traits.Bool(True, usedefault=True,
desc='write a log of command lines that were applied')
copy_dtype = traits.Bool(False, usedefault=True,
desc='copy dtype from inputs to outputs')
class MaskEPIInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(File(exists=True),
mandatory=True,
desc='input EPI or list of files')
lower_cutoff = traits.Float(0.2, usedefault=True)
upper_cutoff = traits.Float(0.85, usedefault=True)
connected = traits.Bool(True, usedefault=True)
opening = traits.Int(2, usedefault=True)
exclude_zeros = traits.Bool(False, usedefault=True)
ensure_finite = traits.Bool(True, usedefault=True)
target_affine = traits.File()
target_shape = traits.File()
class StructuralQCInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='file to be plotted')
in_noinu = File(exists=True,
mandatory=True,
desc='image after INU correction')
in_segm = File(exists=True,
mandatory=True,
desc='segmentation file from FSL FAST')
in_bias = File(exists=True, mandatory=True, desc='bias file')
head_msk = File(exists=True, mandatory=True, desc='head mask')
air_msk = File(exists=True, mandatory=True, desc='air mask')
rot_msk = File(exists=True, mandatory=True, desc='rotation mask')
artifact_msk = File(exists=True, mandatory=True, desc='air mask')
in_pvms = InputMultiPath(File(exists=True),
mandatory=True,
desc='partial volume maps from FSL FAST')
in_tpms = InputMultiPath(File(),
desc='tissue probability maps from FSL FAST')
mni_tpms = InputMultiPath(File(),
desc='tissue probability maps from FSL FAST')
in_fwhm = traits.List(traits.Float,
mandatory=True,
desc='smoothness estimated with AFNI')
class MergeInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(File(exists=True),
mandatory=True,
desc='input list of files to merge')
dtype = traits.Enum('f4',
'f8',
'u1',
'u2',
'u4',
'i2',
'i4',
usedefault=True,
desc='numpy dtype of output image')
header_source = File(
exists=True,
desc='a Nifti file from which the header should be copied')
class DerivativesDataSinkInputSpec(BaseInterfaceInputSpec):
base_directory = traits.Directory(
desc='Path to the base directory for storing data.')
in_file = InputMultiPath(File(exists=True),
mandatory=True,
desc='the object to be saved')
source_file = File(exists=False,
mandatory=True,
desc='the input func file')
suffix = traits.Str('',
mandatory=True,
desc='suffix appended to source_file')
extra_values = traits.List(traits.Str)
compress = traits.Bool(
desc="force compression (True) or uncompression (False)"
" of the output file (default: same as input)")
class MaskEPIInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(File(exists=True),
mandatory=True,
desc='input EPI or list of files')
lower_cutoff = traits.Float(0.2, usedefault=True)
upper_cutoff = traits.Float(0.85, usedefault=True)
connected = traits.Bool(True, usedefault=True)
enhance_t2 = traits.Bool(False,
usedefault=True,
desc='enhance T2 contrast on image')
opening = traits.Int(2, usedefault=True)
closing = traits.Bool(True, usedefault=True)
fill_holes = traits.Bool(True, usedefault=True)
exclude_zeros = traits.Bool(False, usedefault=True)
ensure_finite = traits.Bool(True, usedefault=True)
target_affine = traits.Either(None,
traits.File(exists=True),
default=None,
usedefault=True)
target_shape = traits.Either(None,
traits.File(exists=True),
default=None,
usedefault=True)
no_sanitize = traits.Bool(False, usedefault=True)
class MakeMidthicknessInputSpec(fs.utils.MRIsExpandInputSpec):
graymid = InputMultiPath(desc='Existing graymid/midthickness file')
class ConformSeriesInputSpec(BaseInterfaceInputSpec):
t1w_list = InputMultiPath(File(exists=True),
mandatory=True,
desc='input T1w images')
class CombineROIsInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(File(exists=True),
mandatory=True,
desc='input list of ROIs')
ref_header = File(exists=True, mandatory=True, desc='input mask')
class AddTPMsInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(File(exists=True), mandatory=True, desc='input list of ROIs')
indices = traits.List(traits.Int, desc='select specific maps')