code: def test_DARTELNorm2MNI_inputs():
      input_map = dict(
          apply_to_files=dict(
              copyfile=False,
              field="mni_norm.data.subjs.images",
              mandatory=True,
          ),
          bounding_box=dict(
              field="mni_norm.bb",
          ),
          flowfield_files=dict(
              field="mni_norm.data.subjs.flowfields",
              mandatory=True,
          ),
          fwhm=dict(
              field="mni_norm.fwhm",
          ),
          matlab_cmd=dict(),
          mfile=dict(
              usedefault=True,
          ),
          modulate=dict(
              field="mni_norm.preserve",
          ),
          paths=dict(),
          template_file=dict(
              copyfile=False,
              extensions=[".hdr", ".img", ".img.gz", ".nii"],
              field="mni_norm.template",
              mandatory=True,
          ),
          use_mcr=dict(),
          use_v8struct=dict(
              min_ver="8",
              usedefault=True,
          ),
          voxel_size=dict(
              field="mni_norm.vox",
          ),
      )
      inputs = DARTELNorm2MNI.input_spec()
  
      for key, metadata in list(input_map.items()):
          for metakey, value in list(metadata.items()):
              assert getattr(inputs.traits()[key], metakey) == value
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_DARTELNorm2MNI_inputs() without return types