code: def test_AffineRegistration_inputs():
      input_map = dict(
          FixedImageFileName=dict(
              argstr="%s",
              extensions=None,
              position=-2,
          ),
          MovingImageFileName=dict(
              argstr="%s",
              extensions=None,
              position=-1,
          ),
          args=dict(
              argstr="%s",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          fixedsmoothingfactor=dict(
              argstr="--fixedsmoothingfactor %d",
          ),
          histogrambins=dict(
              argstr="--histogrambins %d",
          ),
          initialtransform=dict(
              argstr="--initialtransform %s",
              extensions=None,
          ),
          iterations=dict(
              argstr="--iterations %d",
          ),
          movingsmoothingfactor=dict(
              argstr="--movingsmoothingfactor %d",
          ),
          outputtransform=dict(
              argstr="--outputtransform %s",
              hash_files=False,
          ),
          resampledmovingfilename=dict(
              argstr="--resampledmovingfilename %s",
              hash_files=False,
          ),
          spatialsamples=dict(
              argstr="--spatialsamples %d",
          ),
          translationscale=dict(
              argstr="--translationscale %f",
          ),
      )
      inputs = AffineRegistration.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_AffineRegistration_inputs() without return types