code: def test_CorticalThickness_inputs():
      input_map = dict(
          anatomical_image=dict(
              argstr="-a %s",
              extensions=None,
              mandatory=True,
          ),
          args=dict(
              argstr="%s",
          ),
          b_spline_smoothing=dict(
              argstr="-v",
          ),
          brain_probability_mask=dict(
              argstr="-m %s",
              copyfile=False,
              extensions=None,
              mandatory=True,
          ),
          brain_template=dict(
              argstr="-e %s",
              extensions=None,
              mandatory=True,
          ),
          cortical_label_image=dict(
              extensions=None,
          ),
          debug=dict(
              argstr="-z 1",
          ),
          dimension=dict(
              argstr="-d %d",
              usedefault=True,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          extraction_registration_mask=dict(
              argstr="-f %s",
              extensions=None,
          ),
          image_suffix=dict(
              argstr="-s %s",
              usedefault=True,
          ),
          keep_temporary_files=dict(
              argstr="-k %d",
          ),
          label_propagation=dict(
              argstr="-l %s",
          ),
          max_iterations=dict(
              argstr="-i %d",
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          out_prefix=dict(
              argstr="-o %s",
              usedefault=True,
          ),
          posterior_formulation=dict(
              argstr="-b %s",
          ),
          prior_segmentation_weight=dict(
              argstr="-w %f",
          ),
          quick_registration=dict(
              argstr="-q 1",
          ),
          segmentation_iterations=dict(
              argstr="-n %d",
          ),
          segmentation_priors=dict(
              argstr="-p %s",
              mandatory=True,
          ),
          t1_registration_template=dict(
              argstr="-t %s",
              extensions=None,
              mandatory=True,
          ),
          use_floatingpoint_precision=dict(
              argstr="-j %d",
          ),
          use_random_seeding=dict(
              argstr="-u %d",
          ),
      )
      inputs = CorticalThickness.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_CorticalThickness_inputs() without return types