code: def test_Segment_outputs():
      output_map = dict(
          bias_corrected_image=dict(
              extensions=None,
          ),
          inverse_transformation_mat=dict(
              extensions=None,
          ),
          modulated_csf_image=dict(
              extensions=None,
          ),
          modulated_gm_image=dict(
              extensions=None,
          ),
          modulated_input_image=dict(
              deprecated="0.10",
              extensions=None,
              new_name="bias_corrected_image",
          ),
          modulated_wm_image=dict(
              extensions=None,
          ),
          native_csf_image=dict(
              extensions=None,
          ),
          native_gm_image=dict(
              extensions=None,
          ),
          native_wm_image=dict(
              extensions=None,
          ),
          normalized_csf_image=dict(
              extensions=None,
          ),
          normalized_gm_image=dict(
              extensions=None,
          ),
          normalized_wm_image=dict(
              extensions=None,
          ),
          transformation_mat=dict(
              extensions=None,
          ),
      )
      outputs = Segment.output_spec()
  
      for key, metadata in list(output_map.items()):
          for metakey, value in list(metadata.items()):
              assert getattr(outputs.traits()[key], metakey) == value
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_Segment_outputs() without return types