code: def test_source_competence_logarithmic():
      log_test = Logarithmic()
      log_test.n_classifiers_ = 1
      log_test.dsel_scores_ = np.array(
          [[[0.67, 0.33, 0.0], [1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]]
      ).reshape(3, 1, 3)
  
      log_test.DSEL_target_ = [1, 1, 1]
      log_test.n_classes_ = 3
      log_test.n_samples_ = 3
      C_src = log_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 20 for calling a global function with example usage: test_source_competence_logarithmic() without return types