code: def test_sample_selection():
      meta_test = METADES()
      meta_test.n_classifiers_ = 15
      meta_test.DSEL_processed_ = np.ones((5, 15))
      meta_test.DSEL_processed_[(1, 3, 4), 5:] = 0
      expected = np.asarray([1, 1 / 3, 1, 1 / 3, 1 / 3])
      value = meta_test._sample_selection_agreement()
      assert np.array_equal(value, 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 14 for calling a global function with example usage: test_sample_selection() without return types