code: def test_BRAINSAlignMSP_inputs():
      input_map = dict(
          BackgroundFillValue=dict(
              argstr="--BackgroundFillValue %s",
          ),
          OutputresampleMSP=dict(
              argstr="--OutputresampleMSP %s",
              hash_files=False,
          ),
          args=dict(
              argstr="%s",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          inputVolume=dict(
              argstr="--inputVolume %s",
              extensions=None,
          ),
          interpolationMode=dict(
              argstr="--interpolationMode %s",
          ),
          mspQualityLevel=dict(
              argstr="--mspQualityLevel %d",
          ),
          numberOfThreads=dict(
              argstr="--numberOfThreads %d",
          ),
          rescaleIntensities=dict(
              argstr="--rescaleIntensities ",
          ),
          rescaleIntensitiesOutputRange=dict(
              argstr="--rescaleIntensitiesOutputRange %s",
              sep=",",
          ),
          resultsDir=dict(
              argstr="--resultsDir %s",
              hash_files=False,
          ),
          trimRescaledIntensities=dict(
              argstr="--trimRescaledIntensities %f",
          ),
          verbose=dict(
              argstr="--verbose ",
          ),
          writedebuggingImagesLevel=dict(
              argstr="--writedebuggingImagesLevel %d",
          ),
      )
      inputs = BRAINSAlignMSP.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_BRAINSAlignMSP_inputs() without return types