code: def test_EstimateModel_outputs():
      output_map = dict(
          ARcoef=dict(),
          Cbetas=dict(),
          RPVimage=dict(
              extensions=[".hdr", ".img", ".img.gz", ".nii"],
          ),
          SDbetas=dict(),
          SDerror=dict(),
          beta_images=dict(),
          con_images=dict(),
          ess_images=dict(),
          labels=dict(
              extensions=[".hdr", ".img", ".img.gz", ".nii"],
          ),
          mask_image=dict(
              extensions=[".hdr", ".img", ".img.gz", ".nii"],
          ),
          residual_image=dict(
              extensions=[".hdr", ".img", ".img.gz", ".nii"],
          ),
          residual_images=dict(),
          spmF_images=dict(),
          spmT_images=dict(),
          spm_mat_file=dict(
              extensions=None,
          ),
      )
      outputs = EstimateModel.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_EstimateModel_outputs() without return types