code: def test_estimate_competence_all_ones(index, example_all_ones):
      (
          _,
          y,
          neighbors,
          distances,
          dsel_processed,
          dsel_scores,
      ) = example_all_ones
  
      mla_test = MLA()
      mla_test.n_classifiers_ = 3
  
      mla_test.DSEL_processed_ = dsel_processed
      mla_test.DSEL_scores = dsel_scores
      mla_test.DSEL_target_ = y
      mla_test.n_classes_ = 2
  
      neighbors = neighbors[index, :].reshape(1, -1)
      distances = distances[index, :].reshape(1, -1)
  
      expected = [1.0, 1.0, 1.0]
  
      predictions = np.array([[0, 1, 0]])
  
      competences = mla_test.estimate_competence(
          neighbors, distances=distances, predictions=predictions
      )
  
      assert np.isclose(competences, expected).all()
  
file_path: DESlib/deslib/tests/dcs/test_mla.py
imports: import numpy
  import pytest
  from sklearn.linear_model import Perceptron
  from sklearn.utils.estimator_checks import check_estimator
  from deslib.dcs.mla import MLA
label_desc: Use image node_id 2 for calling a global function with example usage: test_estimate_competence_all_ones(index, example_all_ones) without return types