def test_decision_function_neg():
ypred_proba = np.arange(6) / 5.0
y_true = pd.Series(np.array([0] * 3 + [1] * 3), dtype=bool)
obj = F1()
pd.testing.assert_series_equal(obj.decision_function(ypred_proba), y_true)
pd.testing.assert_series_equal(
obj.decision_function(pd.Series(ypred_proba, dtype=float)), y_true)
def test_optimize_threshold():
ypred_proba = np.array([0.2, 0.4])
y_true = np.array([0, 1])
obj = F1()
np.random.seed(
42
) # unfortunately scipy.optimize.minimize_scalar has no ability to accept seed as input
threshold = obj.optimize_threshold(ypred_proba, y_true)
assert 0.2 < threshold and threshold < 0.4
def test_decision_function():
ypred_proba = np.arange(6) / 5.0
obj = F1()
pd.testing.assert_series_equal(
obj.decision_function(ypred_proba),
pd.Series(np.array([0] * 3 + [1] * 3), dtype=bool))
pd.testing.assert_series_equal(
obj.decision_function(ypred_proba, threshold=0.5),
pd.Series(np.array([0] * 3 + [1] * 3), dtype=bool))
pd.testing.assert_series_equal(
obj.decision_function(ypred_proba, threshold=0.0),
pd.Series(np.array([0] + [1] * 5, dtype=int), dtype=bool))
pd.testing.assert_series_equal(
obj.decision_function(ypred_proba, threshold=1.0),
pd.Series(np.array([0] * 6, dtype=int), dtype=bool))
def test_can_optimize_threshold():
assert F1().can_optimize_threshold
assert not AUC().can_optimize_threshold