code: def test_DiffeoScalarVol_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          flip=dict(
              argstr="-flip %d %d %d",
          ),
          in_file=dict(
              argstr="-in %s",
              extensions=None,
              mandatory=True,
          ),
          interpolation=dict(
              argstr="-interp %s",
              usedefault=True,
          ),
          out_file=dict(
              argstr="-out %s",
              extensions=None,
              keep_extension=True,
              name_source="in_file",
              name_template="%s_diffeoxfmd",
          ),
          resampling_type=dict(
              argstr="-type %s",
          ),
          target=dict(
              argstr="-target %s",
              extensions=None,
              xor=["voxel_size"],
          ),
          transform=dict(
              argstr="-trans %s",
              extensions=None,
              mandatory=True,
          ),
          voxel_size=dict(
              argstr="-vsize %g %g %g",
              xor=["target"],
          ),
      )
      inputs = DiffeoScalarVol.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_DiffeoScalarVol_inputs() without return types