code: def test_select_batch():
      meta_test = METADES()
      competences = np.tile(
          np.array([0.8, 0.6, 0.7, 0.2, 0.3, 0.4, 0.6, 0.1, 1.0, 0.98]),
          (10, 1),
      )
      expected = np.tile(
          [
              True,
              True,
              True,
              False,
              False,
              False,
              True,
              False,
              True,
              True,
          ],
          (10, 1),
      )
      selected_matrix = meta_test.select(competences)
      assert np.array_equal(selected_matrix, expected)
  
imports: from unittest.mock import MagicMock
  import numpy
  import pytest
  from sklearn.linear_model import Perceptron
  from sklearn.naive_bayes import GaussianNB
  from sklearn.svm import SVC
  from sklearn.utils.estimator_checks import check_estimator
  from sklearn.utils.validation import check_is_fitted
  from deslib.des.meta_des import METADES
label_desc: Use image node_id 12 for calling a global function with example usage: test_select_batch() without return types