code: def example_estimate_competence(create_X_y):
      X, y = create_X_y
  
      # Pre-processed results on DSEL. This information is used by the majority
      # of DS techniques to estimate the classifier competence.
      dsel_processed = np.array(
          [
              [1, 1, 1],
              [0, 0, 1],
              [0, 0, 1],
              [1, 1, 0],
              [1, 1, 1],
              [0, 0, 1],
              [0, 0, 0],
              [1, 1, 1],
              [1, 1, 0],
              [0, 0, 1],
              [0, 0, 1],
              [0, 1, 0],
              [0, 1, 0],
              [1, 1, 1],
              [1, 1, 1],
          ]
      )
  
      # pre-calculated indices of 7 Nearest neighbors for competence estimation.
      neighbors = np.array(
          [
              [8, 11, 4, 7, 13, 10, 1],
              [7, 1, 11, 13, 0, 8, 4],
              [5, 3, 4, 8, 10, 11, 7],
          ]
      )
  
      # Scores obtained for the two classes. This information is used by the
      # techniques based on posterior probabilities
      dsel_scores = np.tile(
          np.array([[1.0, 0.0], [0.5, 0.5], [0.8, 0.2]]), (15, 1, 1)
      )
  
      # Distance information is used by the probabilistic techniques
      # (des.probabilistic) as well as the MLA, A Priori and A Posteriori methods
      distances = np.array(
          [
              [
                  0.35355339,
                  0.35355339,
                  0.55901699,
                  0.79056942,
                  0.79056942,
                  0.90138782,
                  1.03077641,
              ],
              [
                  0.3,
                  0.39051248,
                  0.53851648,
                  0.86023253,
                  0.94339811,
                  1.04403065,
                  1.28549601,
              ],
              [
                  0.70710678,
                  1.41421356,
                  1.95256242,
                  2.12132034,
                  2.79508497,
                  2.82842712,
                  2.91547595,
              ],
          ]
      )
  
      return X, y, neighbors, distances, dsel_processed, dsel_scores
  
file_path: DESlib/deslib/tests/conftest.py
imports: import pytest
  import numpy
  from unittest.mock import MagicMock
  from sklearn.tree import DecisionTreeClassifier
label_desc: Use image node_id 1 for calling a global function with example usage: example_estimate_competence(create_X_y) and returns: X,  y,  neighbors,  distances,  dsel_processed,  dsel_scores