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')