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(): des_p_test = DESP() des_p_test.n_classes_ = 3 expected = np.array([[True, False, True], [True, False, True], [False, True, False]]) competences = np.array([[0.34, 0.32, 1.0], [0.50, 0.30, 1.01], [0.25, 1.0, 0.25]]) selected = des_p_test.select(competences) assert np.array_equal(selected, expected)
def test_select_two_classes(): des_p_test = DESP() des_p_test.n_classes_ = 2 expected = np.array([[True, False, True], [True, False, True], [False, True, False]]) competences = np.array([[0.51, 0.0, 0.51], [0.51, 0.0, 0.51], [0.49, 1.0, 0.49]]) selected = des_p_test.select(competences) assert np.array_equal(selected, expected)
def test_select_two_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) neighbors = neighbors_ex1[index, :].reshape(1, -1) distances = distances_ex1[index, :].reshape(1, -1) competences = des_p_test.estimate_competence(query, neighbors, distances) selected = des_p_test.select(competences) assert np.array_equal(selected, expected)
def test_select_two_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.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 == expected
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_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))