code: def test_MedicAlgorithmN3_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          inAutomatic=dict(
              argstr="--inAutomatic %s",
          ),
          inEnd=dict(
              argstr="--inEnd %f",
          ),
          inField=dict(
              argstr="--inField %f",
          ),
          inInput=dict(
              argstr="--inInput %s",
              extensions=None,
          ),
          inKernel=dict(
              argstr="--inKernel %f",
          ),
          inMaximum=dict(
              argstr="--inMaximum %d",
          ),
          inSignal=dict(
              argstr="--inSignal %f",
          ),
          inSubsample=dict(
              argstr="--inSubsample %f",
          ),
          inWeiner=dict(
              argstr="--inWeiner %f",
          ),
          null=dict(
              argstr="--null %s",
          ),
          outInhomogeneity=dict(
              argstr="--outInhomogeneity %s",
              hash_files=False,
          ),
          outInhomogeneity2=dict(
              argstr="--outInhomogeneity2 %s",
              hash_files=False,
          ),
          xDefaultMem=dict(
              argstr="-xDefaultMem %d",
          ),
          xMaxProcess=dict(
              argstr="-xMaxProcess %d",
              usedefault=True,
          ),
          xPrefExt=dict(
              argstr="--xPrefExt %s",
          ),
      )
      inputs = MedicAlgorithmN3.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_MedicAlgorithmN3_inputs() without return types