code: def test_BRAINSCreateLabelMapFromProbabilityMaps_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          cleanLabelVolume=dict(
              argstr="--cleanLabelVolume %s",
              hash_files=False,
          ),
          dirtyLabelVolume=dict(
              argstr="--dirtyLabelVolume %s",
              hash_files=False,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          foregroundPriors=dict(
              argstr="--foregroundPriors %s",
              sep=",",
          ),
          inclusionThreshold=dict(
              argstr="--inclusionThreshold %f",
          ),
          inputProbabilityVolume=dict(
              argstr="--inputProbabilityVolume %s...",
          ),
          nonAirRegionMask=dict(
              argstr="--nonAirRegionMask %s",
              extensions=None,
          ),
          priorLabelCodes=dict(
              argstr="--priorLabelCodes %s",
              sep=",",
          ),
      )
      inputs = BRAINSCreateLabelMapFromProbabilityMaps.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_BRAINSCreateLabelMapFromProbabilityMaps_inputs() without return types