code: def test_N4ITKBiasFieldCorrection_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          bsplineorder=dict(
              argstr="--bsplineorder %d",
          ),
          convergencethreshold=dict(
              argstr="--convergencethreshold %f",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          histogramsharpening=dict(
              argstr="--histogramsharpening %s",
              sep=",",
          ),
          inputimage=dict(
              argstr="--inputimage %s",
              extensions=None,
          ),
          iterations=dict(
              argstr="--iterations %s",
              sep=",",
          ),
          maskimage=dict(
              argstr="--maskimage %s",
              extensions=None,
          ),
          meshresolution=dict(
              argstr="--meshresolution %s",
              sep=",",
          ),
          outputbiasfield=dict(
              argstr="--outputbiasfield %s",
              hash_files=False,
          ),
          outputimage=dict(
              argstr="--outputimage %s",
              hash_files=False,
          ),
          shrinkfactor=dict(
              argstr="--shrinkfactor %d",
          ),
          splinedistance=dict(
              argstr="--splinedistance %f",
          ),
          weightimage=dict(
              argstr="--weightimage %s",
              extensions=None,
          ),
      )
      inputs = N4ITKBiasFieldCorrection.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_N4ITKBiasFieldCorrection_inputs() without return types