code: def test_ResampleImageBySpacing_inputs():
      input_map = dict(
          addvox=dict(
              argstr="%d",
              position=6,
              requires=["apply_smoothing"],
          ),
          apply_smoothing=dict(
              argstr="%d",
              position=5,
          ),
          args=dict(
              argstr="%s",
          ),
          dimension=dict(
              argstr="%d",
              position=1,
              usedefault=True,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          input_image=dict(
              argstr="%s",
              extensions=None,
              mandatory=True,
              position=2,
          ),
          nn_interp=dict(
              argstr="%d",
              position=-1,
              requires=["addvox"],
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          out_spacing=dict(
              argstr="%s",
              mandatory=True,
              position=4,
          ),
          output_image=dict(
              argstr="%s",
              extensions=None,
              keep_extension=True,
              name_source=["input_image"],
              name_template="%s_resampled",
              position=3,
          ),
      )
      inputs = ResampleImageBySpacing.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_ResampleImageBySpacing_inputs() without return types