code: def test_BrainExtraction_outputs():
      output_map = dict(
          BrainExtractionBrain=dict(
              extensions=None,
          ),
          BrainExtractionCSF=dict(
              extensions=None,
          ),
          BrainExtractionGM=dict(
              extensions=None,
          ),
          BrainExtractionInitialAffine=dict(
              extensions=None,
          ),
          BrainExtractionInitialAffineFixed=dict(
              extensions=None,
          ),
          BrainExtractionInitialAffineMoving=dict(
              extensions=None,
          ),
          BrainExtractionLaplacian=dict(
              extensions=None,
          ),
          BrainExtractionMask=dict(
              extensions=None,
          ),
          BrainExtractionPrior0GenericAffine=dict(
              extensions=None,
          ),
          BrainExtractionPrior1InverseWarp=dict(
              extensions=None,
          ),
          BrainExtractionPrior1Warp=dict(
              extensions=None,
          ),
          BrainExtractionPriorWarped=dict(
              extensions=None,
          ),
          BrainExtractionSegmentation=dict(
              extensions=None,
          ),
          BrainExtractionTemplateLaplacian=dict(
              extensions=None,
          ),
          BrainExtractionTmp=dict(
              extensions=None,
          ),
          BrainExtractionWM=dict(
              extensions=None,
          ),
          N4Corrected0=dict(
              extensions=None,
          ),
          N4Truncated0=dict(
              extensions=None,
          ),
      )
      outputs = BrainExtraction.output_spec()
  
      for key, metadata in list(output_map.items()):
          for metakey, value in list(metadata.items()):
              assert getattr(outputs.traits()[key], metakey) == value
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_BrainExtraction_outputs() without return types