code: def test_source_competence_rrc():
      rrc_test = RRC()
      rrc_test.n_classifiers_ = 1
      rrc_test.dsel_scores_ = np.array(
          [
              [
                  [0.3, 0.6, 0.1],
                  [1.0 / 3, 1.0 / 3, 1.0 / 3],
                  [0.5, 0.2, 0.3],
                  [0.5, 0.2, 0.3],
              ]
          ]
      ).reshape(4, 1, 3)
      rrc_test.DSEL_target_ = [1, 0, 0, 1]
      rrc_test.n_classes_ = 3
      rrc_test.n_samples_ = 4
      C_src = rrc_test.source_competence()
      expected = np.array([[0.7849], [0.3328], [0.6428], [0.1194]])
      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 17 for calling a global function with example usage: test_source_competence_rrc() without return types