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 FSDetectInputsOutputSpec(TraitedSpec):
t2w = File(desc='reference T2w image')
use_t2w = traits.Bool(desc='enable use of T2w downstream computation')
flair = File(desc='reference FLAIR image')
use_flair = traits.Bool(desc='enable use of FLAIR downstream computation')
hires = traits.Bool(desc='enable hi-res processing')
mris_inflate = traits.Str(desc='mris_inflate argument')
class FieldEnhanceInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='input fieldmap')
in_mask = File(exists=True, desc='brain mask')
in_magnitude = File(exists=True, desc='input magnitude')
unwrap = traits.Bool(False, usedefault=True, desc='run phase unwrap')
despike = traits.Bool(True, usedefault=True, desc='run despike filter')
bspline_smooth = traits.Bool(True, usedefault=True, desc='run 3D bspline smoother')
mask_erode = traits.Int(1, usedefault=True, desc='mask erosion iterations')
despike_threshold = traits.Float(0.2, usedefault=True, desc='mask erosion iterations')
njobs = traits.Int(1, usedefault=True, nohash=True, desc='number of jobs')
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 SpikesInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='input fMRI dataset')
in_mask = File(exists=True, desc='brain mask')
invert_mask = traits.Bool(False, usedefault=True, desc='invert mask')
no_zscore = traits.Bool(False, usedefault=True, desc='do not zscore')
detrend = traits.Bool(True, usedefault=True, desc='do detrend')
spike_thresh = traits.Float(6., usedefault=True,
desc='z-score to call one timepoint of one axial slice a spike')
skip_frames = traits.Int(0, usedefault=True,
desc='number of frames to skip in the beginning of the time series')
out_tsz = File('spikes_tsz.txt', usedefault=True, desc='output file name')
out_spikes = File(
'spikes_idx.txt', usedefault=True, desc='output file name')
class FunctionalSummaryInputSpec(BaseInterfaceInputSpec):
slice_timing = traits.Enum(False,
True,
'TooShort',
usedefault=True,
desc='Slice timing correction used')
distortion_correction = traits.Enum(
'epi',
'fieldmap',
'phasediff',
'SyN',
'None',
desc='Susceptibility distortion correction method',
mandatory=True)
pe_direction = traits.Enum(None,
'i',
'i-',
'j',
'j-',
mandatory=True,
desc='Phase-encoding direction detected')
registration = traits.Enum(
'FSL',
'FreeSurfer',
mandatory=True,
desc='Functional/anatomical registration method')
fallback = traits.Bool(desc='Boundary-based registration rejected')
registration_dof = traits.Enum(6,
9,
12,
desc='Registration degrees of freedom',
mandatory=True)
output_spaces = traits.List(desc='Target spaces')
confounds = traits.List(desc='Confounds collected')
class DemeanImageInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True,
desc='image to be demeaned')
in_mask = File(exists=True, mandatory=True,
desc='mask where median will be calculated')
only_mask = traits.Bool(False, usedefault=True,
desc='demean only within mask')
class PlotContoursInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='File to be plotted')
in_contours = File(exists=True,
mandatory=True,
desc='file to pick the contours from')
cut_coords = traits.Int(8, usedefault=True, desc='number of slices')
levels = traits.List([.5],
traits.Float,
usedefault=True,
desc='add a contour per level')
colors = traits.List(['r'],
traits.Str,
usedefault=True,
desc='colors to be used for contours')
display_mode = traits.Enum('ortho',
'x',
'y',
'z',
'yx',
'xz',
'yz',
usedefault=True,
desc='visualization mode')
saturate = traits.Bool(False, usedefault=True, desc='saturate background')
out_file = traits.File(exists=False, desc='output file name')
vmin = traits.Float(desc='minimum intensity')
vmax = traits.Float(desc='maximum intensity')
class ComputeQI2InputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='File to be plotted')
air_msk = File(exists=True,
mandatory=True,
desc='air (without artifacts) mask')
erodemsk = traits.Bool(True, usedefault=True, desc='erode mask')
ncoils = traits.Int(12, usedefault=True, desc='number of coils')
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 MaskT2SMapInputSpec(BaseInterfaceInputSpec):
image = File(mandatory=True, exists=True, desc='T2* volume to mask')
mask = File(mandatory=True,
exists=True,
desc='skull-stripped mean optimal combination volume')
compress = traits.Bool(True,
usedefault=True,
desc='use gzip compression on .nii output')
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 BIDSFreeSurferDirInputSpec(BaseInterfaceInputSpec):
derivatives = Directory(exists=True, mandatory=True,
desc='BIDS derivatives directory')
freesurfer_home = Directory(exists=True, mandatory=True,
desc='FreeSurfer installation directory')
subjects_dir = traits.Str('freesurfer', usedefault=True,
desc='Name of FreeSurfer subjects directory')
spaces = traits.List(traits.Str, desc='Set of output spaces to prepare')
overwrite_fsaverage = traits.Bool(False, usedefault=True,
desc='Overwrite fsaverage directories, if present')
class UploadIQMsInputSpec(BaseInterfaceInputSpec):
in_iqms = File(exists=True,
mandatory=True,
desc='the input IQMs-JSON file')
url = Str(mandatory=True, desc='URL (protocol and name) listening')
port = traits.Int(desc='MRIQCWebAPI service port')
path = Str(desc='MRIQCWebAPI endpoint root path')
email = Str(desc='set sender email')
strict = traits.Bool(False,
usedefault=True,
desc='crash if upload was not succesfull')
class PlotBaseInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='File to be plotted')
title = traits.Str(desc='a title string for the plot')
annotate = traits.Bool(True, usedefault=True, desc='annotate left/right')
figsize = traits.Tuple((11.69, 8.27),
traits.Float,
traits.Float,
usedefault=True,
desc='Figure size')
dpi = traits.Int(300, usedefault=True, desc='Desired DPI of figure')
out_file = File('mosaic.svg', usedefault=True, desc='output file name')
cmap = traits.Str('Greys_r', usedefault=True)
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 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')
compress = traits.Bool(True,
usedefault=True,
desc='Use gzip compression on .nii output')
class GCORInputSpec(CommandLineInputSpec):
in_file = File(desc='input dataset to compute the GCOR over',
argstr='-input %s',
position=-1,
mandatory=True,
exists=True,
copyfile=False)
mask = File(desc='mask dataset, for restricting the computation',
argstr='-mask %s',
exists=True,
copyfile=False)
nfirst = traits.Int(0,
argstr='-nfirst %d',
desc='specify number of initial TRs to ignore')
no_demean = traits.Bool(False,
argstr='-no_demean',
desc='do not (need to) demean as first step')
class FunctionalSummaryInputSpec(BaseInterfaceInputSpec):
slice_timing = traits.Bool(False,
usedefault=True,
desc='Slice timing correction used')
distortion_correction = traits.Enum(
'epi',
'fieldmap',
'phasediff',
'SyN',
'None',
desc='Susceptibility distortion correction method',
mandatory=True)
registration = traits.Enum(
'FLIRT',
'bbregister',
mandatory=True,
desc='Functional/anatomical registration method')
output_spaces = traits.List(desc='Target spaces')
confounds = traits.List(desc='Confounds collected')
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 ConcatAffinesInputSpec(DynamicTraitedSpec, BaseInterfaceInputSpec):
invert = traits.Bool(False, usedefault=True, desc='Invert output transform')
class ICAConfoundsInputSpec(BaseInterfaceInputSpec):
in_directory = Directory(mandatory=True,
desc='directory where ICA derivatives are found')
ignore_aroma_err = traits.Bool(False,
usedefault=True,
desc='ignore ICA-AROMA errors')
class HarmonizeInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True,
mandatory=True,
desc='input data (after bias correction)')
wm_mask = File(exists=True, mandatory=True, desc='white-matter mask')
erodemsk = traits.Bool(True, usedefault=True, desc='erode mask')
class PlotMosaicInputSpec(PlotBaseInputSpec):
bbox_mask_file = File(exists=True, desc='brain mask')
only_noise = traits.Bool(False, desc='plot only noise')
class ConformImageInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='input image')
check_ras = traits.Bool(True, usedefault=True,
desc='check that orientation is RAS')
check_dtype = traits.Bool(True, usedefault=True,
desc='check data type')