class CalculateProbabilityFromSamplesInput(TraitedSpec):
sample_maps = InputMultiPath(File(exists=True), mandatory=True)
stat_map = File(exists=True, mandatory=True)
mask = traits.File(
exists=True,
desc="restrict the fitting only to the region defined by this mask")
independent_voxel_nulls = traits.Bool(False, usedefault=True)
class AnnotateTractsInputSpec(BaseInterfaceInputSpec):
trackvis_file = File(exists=True, mandatory=True)
stat_files = InputMultiPath(File(exists=True), mandatory=True)
stat_labels = traits.List()
interpolation_order = traits.Int(0, usedefault=True)
out_tracks = File('ann_tract_samples.trk', usedefault=True)
out_max_map_prefix = traits.Str('max_map', usedefault=True)
out_mean_map_prefix = traits.Str('mean_map', usedefault=True)
class ClassifierInputSpec(CommandLineInputSpec):
mel_ica = Directory(exists=True, copyfile=False, desc='Melodic output directory or directories',
argstr='%s', position=1)
trained_wts_file = File(exists=True, desc='trained-weights file', argstr='%s', position=2, mandatory=True, copyfile=False)
thresh = traits.Int(argstr='%d', desc='Threshold for cleanup.', position=-1, mandatory=True)
artifacts_list_file = File(desc='Text file listing which ICs are artifacts; can be the output from classification or can be created manually')
class AccuracyTesterInputSpec(CommandLineInputSpec):
mel_icas = InputMultiPath(Directory(exists=True), copyfile=False,
desc='Melodic output directories',
argstr='%s', position=3, mandatory=True)
trained_wts_file = File(desc='trained-weights file', argstr='%s', position=1, mandatory=True)
output_directory = Directory(desc='Path to folder in which to store the results of the accuracy test.', argstr='%s', position=2, mandatory=True)
class CleanerInputSpec(CommandLineInputSpec):
artifacts_list_file = File(exists=True, argstr='%s', position=1, mandatory=True, desc='Text file listing which ICs are artifacts; can be the output from classification or can be created manually')
cleanup_motion = traits.Bool(argstr='-m',
desc='cleanup motion confounds, looks for design.fsf for highpass filter cut-off',
position=2)
highpass = traits.Float(argstr='-m -h %f',
desc='cleanup motion confounds', value=100, position=2)
aggressive = traits.Bool(argstr='-A',
desc='Apply aggressive (full variance) cleanup, instead of the default less-aggressive (unique variance) cleanup.', position=3)
confound_file = traits.File(argstr='-x %s',
desc='Include additional confound file.', position=4)
confound_file_1 = traits.File(argstr='-x %s',
desc='Include additional confound file.', position=5)
confound_file_2 = traits.File(argstr='-x %s',
desc='Include additional confound file.', position=6)
class CleanerOutputSpec(TraitedSpec):
cleaned_functional_file = File(exists=True, desc='Cleaned session data')
class ClassifierOutputSpec(TraitedSpec):
artifacts_list_file = File(
desc=
'Text file listing which ICs are artifacts; can be the output from classification or can be created manually'
)
class TrainingOutputSpec(TraitedSpec):
trained_wts_file = File(exists=True, desc='Trained-weights file')
class PermuteTimeSeriesOutputSpec(TraitedSpec):
permuted_volume = File(exists=True)
class PermuteTimeSeriesInputSpec(TraitedSpec):
original_volume = File(exists=True,
desc="source volume for bootstrapping",
mandatory=True)
id = traits.Int()
class BootstrapTimeSeriesOutputSpec(TraitedSpec):
bootstraped_volume = File(exists=True)
class CalculateFDRQMapInput(TraitedSpec):
p_map = File(exists=True, mandatory=True)
mask = traits.File(
exists=True,
desc="restrict the fitting only to the region defined by this mask")
class AnnotateTractsOutputSpec(BaseInterfaceInputSpec):
annotated_trackvis_file = File(exists=True)
max_maps = OutputMultiPath(File(exists=True))
mean_maps = OutputMultiPath(File(exists=True))
class CalculateProbabilityFromSamplesOutput(TraitedSpec):
p_map = File(exists=True)
class CalculateFDRQMapOutput(TraitedSpec):
q_map = File(exists=True)
class Particle2TrackvisInputSpec(BaseInterfaceInputSpec):
particle_files = InputMultiPath(File(exists=True), mandatory=True)
reference_file = File(exists=True)
out_file = File('tract_samples.trk', usedefault=True)
class Particle2TrackvisOutputSpec(BaseInterfaceInputSpec):
trackvis_file = File(exists=True)
class CalculateNonParametricFWEThresholdInput(TraitedSpec):
sample_maps = InputMultiPath(File(exists=True), mandatory=True)
p_threshold = traits.Float(0.05, usedefault=True)