code: def test_source_competence_exponential():
      exp_test = Exponential()
      exp_test.n_classifiers_ = 1
      exp_test.dsel_scores_ = np.array(
          [[[0.5, 0.5], [1.0, 0.0], [0.0, 1.0]]]
      ).reshape(3, 1, 2)
  
      exp_test.DSEL_target_ = [1, 1, 1]
      exp_test.n_classes_ = 2
      exp_test.n_samples_ = 3
      C_src = exp_test.source_competence()
      expected = np.array([[0.0], [-1.0], [1.0]])
      assert np.allclose(C_src, expected, atol=0.01)
  
imports: import numpy
  import pytest
  from sklearn.linear_model import Perceptron
  from sklearn.utils.estimator_checks import check_estimator
  from deslib.des.probabilistic import BaseProbabilistic, Logarithmic, Exponential, RRC, DESKL, MinimumDifference
label_desc: Use image node_id 21 for calling a global function with example usage: test_source_competence_exponential() without return types