code: def test_N4BiasFieldCorrection_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          bias_image=dict(
              extensions=None,
              hash_files=False,
          ),
          bspline_fitting_distance=dict(
              argstr="--bspline-fitting %s",
          ),
          bspline_order=dict(
              requires=["bspline_fitting_distance"],
          ),
          convergence_threshold=dict(
              requires=["n_iterations"],
          ),
          copy_header=dict(
              mandatory=True,
              usedefault=True,
          ),
          dimension=dict(
              argstr="-d %d",
              usedefault=True,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          histogram_sharpening=dict(
              argstr="--histogram-sharpening [%g,%g,%d]",
          ),
          input_image=dict(
              argstr="--input-image %s",
              extensions=None,
              mandatory=True,
          ),
          mask_image=dict(
              argstr="--mask-image %s",
              extensions=None,
          ),
          n_iterations=dict(
              argstr="--convergence %s",
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          output_image=dict(
              argstr="--output %s",
              hash_files=False,
              keep_extension=True,
              name_source=["input_image"],
              name_template="%s_corrected",
          ),
          rescale_intensities=dict(
              argstr="-r",
              min_ver="2.1.0",
              usedefault=True,
          ),
          save_bias=dict(
              mandatory=True,
              usedefault=True,
              xor=["bias_image"],
          ),
          shrink_factor=dict(
              argstr="--shrink-factor %d",
          ),
          weight_image=dict(
              argstr="--weight-image %s",
              extensions=None,
          ),
      )
      inputs = N4BiasFieldCorrection.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_N4BiasFieldCorrection_inputs() without return types