code: def test_gtractTensor_inputs():
      input_map = dict(
          applyMeasurementFrame=dict(
              argstr="--applyMeasurementFrame ",
          ),
          args=dict(
              argstr="%s",
          ),
          b0Index=dict(
              argstr="--b0Index %d",
          ),
          backgroundSuppressingThreshold=dict(
              argstr="--backgroundSuppressingThreshold %d",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          ignoreIndex=dict(
              argstr="--ignoreIndex %s",
              sep=",",
          ),
          inputVolume=dict(
              argstr="--inputVolume %s",
              extensions=None,
          ),
          maskProcessingMode=dict(
              argstr="--maskProcessingMode %s",
          ),
          maskVolume=dict(
              argstr="--maskVolume %s",
              extensions=None,
          ),
          medianFilterSize=dict(
              argstr="--medianFilterSize %s",
              sep=",",
          ),
          numberOfThreads=dict(
              argstr="--numberOfThreads %d",
          ),
          outputVolume=dict(
              argstr="--outputVolume %s",
              hash_files=False,
          ),
          resampleIsotropic=dict(
              argstr="--resampleIsotropic ",
          ),
          size=dict(
              argstr="--size %f",
          ),
      )
      inputs = gtractTensor.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_gtractTensor_inputs() without return types