def test_select_none_competent():
des_p_test = DESP(create_pool_classifiers())
des_p_test.n_classes = 2
competences = np.ones(des_p_test.n_classifiers) * 0.49
indices = des_p_test.select(competences)
expected = np.array([[True, True, True]])
assert np.array_equal(expected, indices)
def test_select_three_classes(index, expected):
query = np.atleast_2d([1, 1])
des_p_test = DESP(create_pool_classifiers())
des_p_test.fit(X_dsel_ex1, y_dsel_ex1)
des_p_test.n_classes = 3
des_p_test.neighbors = neighbors_ex1[index, :]
des_p_test.distances = distances_ex1[index, :]
competences = des_p_test.estimate_competence(query)
selected = des_p_test.select(competences)
assert np.array_equal(selected, expected)
def test_select_ten_classes(index, ):
query = np.atleast_2d([1, 1])
des_p_test = DESP(create_pool_classifiers())
des_p_test.fit(X_dsel_ex1, y_dsel_ex1)
des_p_test.n_classes = 10
des_p_test.DFP_mask = np.ones(des_p_test.n_classifiers)
des_p_test.neighbors = neighbors_ex1[index, :]
des_p_test.distances = distances_ex1[index, :]
competences = des_p_test.estimate_competence(query)
selected = des_p_test.select(competences)
assert selected == list(range(des_p_test.n_classifiers))
def test_select_none_competent():
des_p_test = DESP(create_pool_classifiers())
des_p_test.n_classes = 2
competences = np.ones(des_p_test.n_classifiers) * 0.49
indices = des_p_test.select(competences)
assert indices == list(range(des_p_test.n_classifiers))
