def test_estimate_competence(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)
assert np.isclose(competences, expected, atol=0.01).all()
def test_estimate_competence_batch():
query = np.ones((3, 2))
expected = np.array([[0.57142857, 0.4285714, 0.57142857],
[0.71428571, 0.2857142, 0.71428571],
[0.2857142, 0.71428571, 0.2857142]])
des_p_test = DESP(create_pool_classifiers())
des_p_test.fit(X_dsel_ex1, y_dsel_ex1)
des_p_test.DFP_mask = np.ones((3, des_p_test.n_classifiers))
des_p_test.neighbors = neighbors_ex1
des_p_test.distances = distances_ex1
competences = des_p_test.estimate_competence(query)
assert np.allclose(competences, expected, atol=0.01)
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)
