class_docstr: construct an unbiased robust template for longitudinal volumes
  
  Examples
  --------
  >>> from nipype.interfaces.freesurfer import RobustTemplate
  >>> template = RobustTemplate()
  >>> template.inputs.in_files = ['structural.nii', 'functional.nii']
  >>> template.inputs.auto_detect_sensitivity = True
  >>> template.inputs.average_metric = 'mean'
  >>> template.inputs.initial_timepoint = 1
  >>> template.inputs.fixed_timepoint = True
  >>> template.inputs.no_iteration = True
  >>> template.inputs.subsample_threshold = 200
  >>> template.cmdline  #doctest:
  'mri_robust_template --satit --average 0 --fixtp --mov structural.nii functional.nii --inittp 1 --noit --template mri_robust_template_out.mgz --subsample 200'
  >>> template.inputs.out_file = 'T1.nii'
  >>> template.cmdline  #doctest:
  'mri_robust_template --satit --average 0 --fixtp --mov structural.nii functional.nii --inittp 1 --noit --template T1.nii --subsample 200'
  
  >>> template.inputs.transform_outputs = ['structural.lta',
  ...                                      'functional.lta']
  >>> template.inputs.scaled_intensity_outputs = ['structural-iscale.txt',
  ...                                             'functional-iscale.txt']
  >>> template.cmdline    #doctest: +ELLIPSIS
  'mri_robust_template --satit --average 0 --fixtp --mov structural.nii functional.nii --inittp 1 --noit --template T1.nii --iscaleout .../structural-iscale.txt .../functional-iscale.txt --subsample 200 --lta .../structural.lta .../functional.lta'
  
  >>> template.inputs.transform_outputs = True
  >>> template.inputs.scaled_intensity_outputs = True
  >>> template.cmdline    #doctest: +ELLIPSIS
  'mri_robust_template --satit --average 0 --fixtp --mov structural.nii functional.nii --inittp 1 --noit --template T1.nii --iscaleout .../is1.txt .../is2.txt --subsample 200 --lta .../tp1.lta .../tp2.lta'
  
  >>> template.run()  #doctest: +SKIP
  
  References
  ----------
  [https://surfer.nmr.mgh.harvard.edu/fswiki/mri_robust_template]
class_docstr_tok: ["construct","an","unbiased","robust","template","for","longitudinal","volumes","Examples","--","--","--","--",">",">",">","from","nipype.interfaces.freesurfer","import","RobustTemplate",">",">",">","template","=","RobustTemplate","(",")",">",">",">","template.inputs.in_files","=","[","'structural.nii","'",",","'functional.nii","'","]",">",">",">","template.inputs.auto_detect_sensitivity","=","True",">",">",">","template.inputs.average_metric","=","'mean'",">",">",">","template.inputs.initial_timepoint","=","1",">",">",">","template.inputs.fixed_timepoint","=","True",">",">",">","template.inputs.no_iteration","=","True",">",">",">","template.inputs.subsample_threshold","=","200",">",">",">","template.cmdline","#","doctest",":","'mri_robust_template","--","satit","--","average","0","--","fixtp","--","mov","structural.nii","functional.nii","--","inittp","1","--","noit","--","template","mri_robust_template_out.mgz","--","subsample","200'",">",">",">","template.inputs.out_file","=","'T1.nii'",">",">",">","template.cmdline","#","doctest",":","'mri_robust_template","--","satit","--","average","0","--","fixtp","--","mov","structural.nii","functional.nii","--","inittp","1","--","noit","--","template","T1.nii","--","subsample","200'",">",">",">","template.inputs.transform_outputs","=","[","'structural.lta","'",",","...","'functional.lta","'","]",">",">",">","template.inputs.scaled_intensity_outputs","=","[","'structural-iscale.txt","'",",","...","'functional-iscale.txt","'","]",">",">",">","template.cmdline","#","doctest",":","+ELLIPSIS","'mri_robust_template","--","satit","--","average","0","--","fixtp","--","mov","structural.nii","functional.nii","--","inittp","1","--","noit","--","template","T1.nii","--","iscaleout","...","\/structural-iscale.txt","...","\/functional-iscale.txt","--","subsample","200","--","lta","...","\/structural.lta","...","\/functional.lta'",">",">",">","template.inputs.transform_outputs","=","True",">",">",">","template.inputs.scaled_intensity_outputs","=","True",">",">",">","template.cmdline","#","doctest",":","+ELLIPSIS","'mri_robust_template","--","satit","--","average","0","--","fixtp","--","mov","structural.nii","functional.nii","--","inittp","1","--","noit","--","template","T1.nii","--","iscaleout","...","\/is1.txt","...","\/is2.txt","--","subsample","200","--","lta","...","\/tp1.lta","...","\/tp2.lta'",">",">",">","template.run","(",")","#","doctest",":","+SKIP","References","--","--","--","--","--","[","https",":","\/\/surfer.nmr.mgh.harvard.edu\/fswiki\/mri_robust_template","]"]
code: def _list_outputs(self):
      outputs = self.output_spec().get()
      outputs["out_file"] = os.path.abspath(self.inputs.out_file)
      n_files = len(self.inputs.in_files)
      fmt = "{}{:02d}.{}" if n_files > 9 else "{}{:d}.{}"
      if isdefined(self.inputs.transform_outputs):
          fnames = self.inputs.transform_outputs
          if fnames is True:
              fnames = [
                  fmt.format("tp", i + 1, "lta") for i in range(n_files)
              ]
          outputs["transform_outputs"] = [
              os.path.abspath(x) for x in fnames
          ]
      if isdefined(self.inputs.scaled_intensity_outputs):
          fnames = self.inputs.scaled_intensity_outputs
          if fnames is True:
              fnames = [
                  fmt.format("is", i + 1, "txt") for i in range(n_files)
              ]
          outputs["scaled_intensity_outputs"] = [
              os.path.abspath(x) for x in fnames
          ]
      return outputs
  
imports: import os
  from ...None import logging
  from ..base import TraitedSpec, File, traits, InputMultiPath, OutputMultiPath, isdefined, InputMultiObject, Directory
  from .base import FSCommand, FSTraitedSpec, FSCommandOpenMP, FSTraitedSpecOpenMP, CommandLine
  from .preprocess import ReconAllInputSpec
  from ..io import FreeSurferSource
label_desc: Use image node_id 2 for calling the RobustTemplate obj's underlying member method code with example usage: obj._list_outputs() and returns: outputs