code: def test_estimate_competence_batch(example_estimate_competence):
      (
          _,
          _,
          neighbors,
          distances,
          dsel_processed,
          _,
      ) = example_estimate_competence
      expected = np.array(
          [
              [0.57142857, 0.71428571, 0.71428571],
              [0.71428571, 0.85714286, 0.71428571],
              [0.57142857, 0.71428571, 0.57142857],
          ]
      )
  
      ola_test = OLA()
      ola_test.DSEL_processed_ = dsel_processed
  
      ola_test.DFP_mask = np.ones((3, 3))
      competences = ola_test.estimate_competence(
          neighbors, distances=distances
      )
      assert np.allclose(competences, expected)
  
imports: import numpy
  from sklearn.linear_model import Perceptron
  from sklearn.utils.estimator_checks import check_estimator
  from deslib.dcs.ola import OLA
label_desc: Use image node_id 2 for calling a global function with example usage: test_estimate_competence_batch(example_estimate_competence) without return types