code: def test_MeasureImageSimilarity_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          dimension=dict(
              argstr="--dimensionality %d",
              position=1,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          fixed_image=dict(
              extensions=None,
              mandatory=True,
          ),
          fixed_image_mask=dict(
              argstr="%s",
              extensions=None,
          ),
          metric=dict(
              argstr="%s",
              mandatory=True,
          ),
          metric_weight=dict(
              requires=["metric"],
              usedefault=True,
          ),
          moving_image=dict(
              extensions=None,
              mandatory=True,
          ),
          moving_image_mask=dict(
              extensions=None,
              requires=["fixed_image_mask"],
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          radius_or_number_of_bins=dict(
              mandatory=True,
              requires=["metric"],
          ),
          sampling_percentage=dict(
              mandatory=True,
              requires=["metric"],
          ),
          sampling_strategy=dict(
              requires=["metric"],
              usedefault=True,
          ),
      )
      inputs = MeasureImageSimilarity.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_MeasureImageSimilarity_inputs() without return types