def test_get_dsel_scores():
ds_test = DS(create_pool_classifiers())
ds_test.fit(X_dsel_ex1, y_dsel_ex1)
ds_test.dsel_scores = dsel_scores_ex1
assert np.array_equal(ds_test._get_scores_dsel(0, 0), np.array([1.0, 0.0]))
assert np.array_equal(ds_test._get_scores_dsel(1, 0), np.array([0.5, 0.5]))
assert np.array_equal(ds_test._get_scores_dsel(2, 0), np.array([0.8, 0.2]))
def test_predict_proba_all_agree():
query = np.atleast_2d([1, 1])
ds_test = DS(create_pool_classifiers())
ds_test.fit(X_dsel_ex1, y_dsel_ex1)
ds_test.dsel_scores = dsel_scores_ex1
ds_test._all_classifier_agree = MagicMock(return_value=True)
proba = ds_test.predict_proba(query)
assert np.isclose(proba, np.atleast_2d([0.61, 0.39])).all()
def test_predict_proba_all_agree():
query = np.atleast_2d([1, 1])
ds_test = DS(create_pool_classifiers())
ds_test.fit(X_dsel_ex1, y_dsel_ex1)
ds_test.dsel_scores = dsel_scores_ex1
backup_all_agree = DS._all_classifier_agree
DS._all_classifier_agree = MagicMock(return_value=np.array([True]))
proba = ds_test.predict_proba(query)
DS._all_classifier_agree = backup_all_agree
assert np.allclose(proba, np.atleast_2d([0.61, 0.39]))
def test_predict_proba_IH_knn(index):
query = np.atleast_2d([1, 1])
ds_test = DS(create_pool_classifiers(), with_IH=True, IH_rate=0.5)
ds_test.fit(X_dsel_ex1, y_dsel_ex1)
ds_test.dsel_scores = dsel_scores_ex1
ds_test.neighbors = neighbors_ex1[index, :]
ds_test.distances = distances_ex1[index, :]
ds_test.roc_algorithm.predict_proba = MagicMock(return_value=np.atleast_2d([0.45, 0.55]))
proba = ds_test.predict_proba(query)
assert np.isclose(proba, np.atleast_2d([0.45, 0.55])).all()
def test_get_dsel_scores_all_samples():
ds_test = DS(create_pool_classifiers())
ds_test.fit(X_dsel_ex1, y_dsel_ex1)
ds_test.dsel_scores = dsel_scores_ex1
expected = np.ones((15, 2)) * 0.5
assert np.array_equal(ds_test._get_scores_dsel(1), expected)
