class_docstr: Resample a metric file to a different mesh
  
  Resamples a metric file, given two spherical surfaces that are in
  register.  If ``ADAP_BARY_AREA`` is used, exactly one of -area-surfs or
  ``-area-metrics`` must be specified.
  
  The ``ADAP_BARY_AREA`` method is recommended for ordinary metric data,
  because it should use all data while downsampling, unlike ``BARYCENTRIC``.
  The recommended areas option for most data is individual midthicknesses
  for individual data, and averaged vertex area metrics from individual
  midthicknesses for group average data.
  
  The ``-current-roi`` option only masks the input, the output may be slightly
  dilated in comparison, consider using ``-metric-mask`` on the output when
  using ``-current-roi``.
  
  The ``-largest option`` results in nearest vertex behavior when used with
  ``BARYCENTRIC``.  When resampling a binary metric, consider thresholding at
  0.5 after resampling rather than using ``-largest``.
  
  >>> from nipype.interfaces.workbench import MetricResample
  >>> metres = MetricResample()
  >>> metres.inputs.in_file = 'sub-01_task-rest_bold_space-fsaverage5.L.func.gii'
  >>> metres.inputs.method = 'ADAP_BARY_AREA'
  >>> metres.inputs.current_sphere = 'fsaverage5_std_sphere.L.10k_fsavg_L.surf.gii'
  >>> metres.inputs.new_sphere = 'fs_LR-deformed_to-fsaverage.L.sphere.32k_fs_LR.surf.gii'
  >>> metres.inputs.area_metrics = True
  >>> metres.inputs.current_area = 'fsaverage5.L.midthickness_va_avg.10k_fsavg_L.shape.gii'
  >>> metres.inputs.new_area = 'fs_LR.L.midthickness_va_avg.32k_fs_LR.shape.gii'
  >>> metres.cmdline
  'wb_command -metric-resample sub-01_task-rest_bold_space-fsaverage5.L.func.gii     fsaverage5_std_sphere.L.10k_fsavg_L.surf.gii     fs_LR-deformed_to-fsaverage.L.sphere.32k_fs_LR.surf.gii     ADAP_BARY_AREA fs_LR-deformed_to-fsaverage.L.sphere.32k_fs_LR.surf.out     -area-metrics fsaverage5.L.midthickness_va_avg.10k_fsavg_L.shape.gii     fs_LR.L.midthickness_va_avg.32k_fs_LR.shape.gii'
code: def _list_outputs(self):
      outputs = super()._list_outputs()
      if self.inputs.valid_roi_out:
          roi_file = self._gen_filename(
              self.inputs.in_file, suffix="_roi"
          )
          outputs["roi_file"] = os.path.abspath(roi_file)
      return outputs
  
file_path: nipype/nipype/interfaces/workbench/metric.py
imports: import os
  from ..base import TraitedSpec, File, traits, CommandLineInputSpec
  from .base import WBCommand
  from ...None import logging
label_desc: Use image node_id 2 for calling the MetricResample obj's underlying member method code with example usage: obj._list_outputs() and returns: outputs