code: def test_LaplacianThickness_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          dT=dict(
              argstr="%s",
              position=6,
              requires=["prior_thickness"],
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          input_gm=dict(
              argstr="%s",
              copyfile=True,
              extensions=None,
              mandatory=True,
              position=2,
          ),
          input_wm=dict(
              argstr="%s",
              copyfile=True,
              extensions=None,
              mandatory=True,
              position=1,
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          output_image=dict(
              argstr="%s",
              hash_files=False,
              keep_extension=True,
              name_source=["input_wm"],
              name_template="%s_thickness",
              position=3,
          ),
          prior_thickness=dict(
              argstr="%s",
              position=5,
              requires=["smooth_param"],
          ),
          smooth_param=dict(
              argstr="%s",
              position=4,
          ),
          sulcus_prior=dict(
              argstr="%s",
              position=7,
              requires=["dT"],
          ),
          tolerance=dict(
              argstr="%s",
              position=8,
              requires=["sulcus_prior"],
          ),
      )
      inputs = LaplacianThickness.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_LaplacianThickness_inputs() without return types