def test_select():
knop_test = KNOP(create_pool_classifiers())
competences = np.ones(3)
competences[0] = 0
expected = np.atleast_2d([False, True, True])
selected = knop_test.select(competences)
assert np.array_equal(expected, selected)
def test_weights_zero():
knop_test = KNOP(create_pool_classifiers())
knop_test.fit(X_dsel_ex1, y_dsel_ex1)
competences = np.zeros((1, 3))
result = knop_test.select(competences)
assert np.all(result)
def test_weights_zero():
query = np.atleast_2d([1, 1])
knop_test = KNOP(create_pool_classifiers())
knop_test.fit(X_dsel_ex1, y_dsel_ex1)
knop_test.estimate_competence = MagicMock(return_value=np.zeros(3))
result = knop_test.select(query)
assert np.array_equal(result, np.array([0, 1, 0]))
def test_weights_zero():
knop_test = KNOP()
competences = np.zeros((1, 3))
result = knop_test.select(competences)
assert np.all(result)