code: def test_GenerateEdgeMapImage_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          inputMRVolumes=dict(
              argstr="--inputMRVolumes %s...",
          ),
          inputMask=dict(
              argstr="--inputMask %s",
              extensions=None,
          ),
          lowerPercentileMatching=dict(
              argstr="--lowerPercentileMatching %f",
          ),
          maximumOutputRange=dict(
              argstr="--maximumOutputRange %d",
          ),
          minimumOutputRange=dict(
              argstr="--minimumOutputRange %d",
          ),
          numberOfThreads=dict(
              argstr="--numberOfThreads %d",
          ),
          outputEdgeMap=dict(
              argstr="--outputEdgeMap %s",
              hash_files=False,
          ),
          outputMaximumGradientImage=dict(
              argstr="--outputMaximumGradientImage %s",
              hash_files=False,
          ),
          upperPercentileMatching=dict(
              argstr="--upperPercentileMatching %f",
          ),
      )
      inputs = GenerateEdgeMapImage.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_GenerateEdgeMapImage_inputs() without return types