def test_source_competence_kl():
entropy_test = DESKL()
entropy_test.n_classifiers_ = 1
entropy_test.dsel_scores_ = np.array([[[0.33, 0.33, 0.33], [1.0, 0.0, 0.0],
[1.0, 0.0, 0.0]]]).reshape(3, 1, 3)
entropy_test.DSEL_processed_ = np.array([[False], [True], [False]])
entropy_test.n_classes_ = 3
entropy_test.n_samples_ = 3
C_src = entropy_test.source_competence()
expected = np.array([[0.0], [1.0], [-1.0]])
assert np.allclose(C_src, expected, atol=0.01)
def test_source_competence_kl():
pool_classifiers = [
create_base_classifier(return_value=1, return_prob=1.0)
]
entropy_test = DESKL(pool_classifiers=pool_classifiers)
entropy_test.n_classifiers_ = len(pool_classifiers)
# 3 Samples, 1 classifier, 3 classes
entropy_test.dsel_scores_ = np.array([[[0.33, 0.33, 0.33], [1.0, 0.0, 0.0],
[1.0, 0.0, 0.0]]]).reshape(3, 1, 3)
entropy_test.DSEL_processed_ = np.array([[False], [True], [False]])
entropy_test.n_classes_ = 3
entropy_test.n_samples_ = 3
C_src = entropy_test.source_competence()
expected = np.array([[0.0], [1.0], [-1.0]])
assert np.allclose(C_src, expected, atol=0.01)