code: def test_BRAINSPosteriorToContinuousClass_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          inputBasalGmVolume=dict(
              argstr="--inputBasalGmVolume %s",
              extensions=None,
          ),
          inputCrblGmVolume=dict(
              argstr="--inputCrblGmVolume %s",
              extensions=None,
          ),
          inputCrblWmVolume=dict(
              argstr="--inputCrblWmVolume %s",
              extensions=None,
          ),
          inputCsfVolume=dict(
              argstr="--inputCsfVolume %s",
              extensions=None,
          ),
          inputSurfaceGmVolume=dict(
              argstr="--inputSurfaceGmVolume %s",
              extensions=None,
          ),
          inputVbVolume=dict(
              argstr="--inputVbVolume %s",
              extensions=None,
          ),
          inputWhiteVolume=dict(
              argstr="--inputWhiteVolume %s",
              extensions=None,
          ),
          outputVolume=dict(
              argstr="--outputVolume %s",
              hash_files=False,
          ),
      )
      inputs = BRAINSPosteriorToContinuousClass.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_BRAINSPosteriorToContinuousClass_inputs() without return types