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')