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 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 TPM2ROIInputSpec(BaseInterfaceInputSpec):
in_tpm = File(exists=True, mandatory=True, desc='Tissue probability map file in T1 space')
in_mask = File(exists=True, mandatory=True, desc='Binary mask of skull-stripped T1w image')
mask_erode_mm = traits.Float(xor=['mask_erode_prop'],
desc='erode input mask (kernel width in mm)')
erode_mm = traits.Float(xor=['erode_prop'],
desc='erode output mask (kernel width in mm)')
mask_erode_prop = traits.Float(xor=['mask_erode_mm'],
desc='erode input mask (target volume ratio)')
erode_prop = traits.Float(xor=['erode_mm'],
desc='erode output mask (target volume ratio)')
prob_thresh = traits.Float(0.95, usedefault=True,
desc='threshold for the tissue probability maps')
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 FilledImageLikeInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='image to be demeaned')
fill_value = traits.Float(1.0, usedefault=True, desc='value to fill')
dtype = traits.Enum('float32',
'uint8',
usedefault=True,
desc='force output data type')
class FunctionalQCInputSpec(BaseInterfaceInputSpec):
in_epi = File(exists=True, mandatory=True, desc='input EPI file')
in_hmc = File(exists=True,
mandatory=True,
desc='input motion corrected file')
in_tsnr = File(exists=True, mandatory=True, desc='input tSNR volume')
in_mask = File(exists=True, mandatory=True, desc='input mask')
direction = traits.Enum('all',
'x',
'y',
'-x',
'-y',
usedefault=True,
desc='direction for GSR computation')
in_fd = File(exists=True,
mandatory=True,
desc='motion parameters for FD computation')
fd_thres = traits.Float(0.2,
usedefault=True,
desc='motion threshold for FD computation')
in_dvars = File(exists=True,
mandatory=True,
desc='input file containing DVARS')
in_fwhm = traits.List(traits.Float,
mandatory=True,
desc='smoothness estimated with AFNI')
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 TPM2ROIInputSpec(BaseInterfaceInputSpec):
t1_tpm = File(exists=True,
mandatory=True,
desc='Tissue probability map file in T1 space')
t1_mask = File(exists=True,
mandatory=True,
desc='Binary mask of skull-stripped T1w image')
bold_mask = File(exists=True,
mandatory=True,
desc='Binary mask of skull-stripped BOLD image')
mask_erode_mm = traits.Float(0.0,
usedefault=True,
desc='erode input mask (kernel width in mm)')
erode_mm = traits.Float(0.0,
usedefault=True,
desc='erode output mask (kernel width in mm)')
prob_thresh = traits.Float(
0.95,
usedefault=True,
desc='threshold for the tissue probability maps')
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 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 GenerateCiftiInputSpec(BaseInterfaceInputSpec):
bold_file = File(mandatory=True, exists=True, desc="input BOLD file")
volume_target = traits.Enum("MNI152NLin2009cAsym",
mandatory=True,
usedefault=True,
desc="CIFTI volumetric output space")
surface_target = traits.Enum("fsaverage5",
"fsaverage6",
mandatory=True,
usedefault=True,
desc="CIFTI surface target space")
subjects_dir = Directory(mandatory=True, desc="FreeSurfer SUBJECTS_DIR")
TR = traits.Float(mandatory=True, desc="repetition time")
gifti_files = traits.List(
File(exists=True),
mandatory=True,
desc="list of surface geometry files (length 2 with order [L,R])")
class GCOROutputSpec(TraitedSpec):
out = traits.Float(desc='global correlation value')
class ComputeQI2OutputSpec(TraitedSpec):
qi2 = traits.Float(desc='computed QI2 value')
out_file = File(desc='output plot: noise fit')
class EnsureSizeInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, copyfile=False, mandatory=True, desc='input image')
in_mask = File(exists=True, copyfile=False, desc='input mask')
pixel_size = traits.Float(2.0, usedefault=True,
desc='desired pixel size (mm)')
class FieldToRadSInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='input fieldmap')
fmap_range = traits.Float(desc='range of input field map')
class FieldToRadSOutputSpec(TraitedSpec):
out_file = File(desc='the output fieldmap')
fmap_range = traits.Float(desc='range of input field map')
class FieldToHzInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='input fieldmap')
range_hz = traits.Float(mandatory=True, desc='range of input field map')
