def test_top_k():
y_true = np.array([True, True, False, False])
y_score = np.array([.25, 1, 0, .5])
assert top_k(y_true, y_score,3) == (2,3)
def test_top_k_len_error():
y_true = np.array([True, False])
y_score = np.array([1,0,.5])
with pytest.raises(ValueError):
top_k(y_true, y_score, 3)
def test_top_k_0():
y_true = np.array([True])
y_score = np.array([1])
assert top_k(y_true, y_score, 0) == (0,0)
def test_top_k_extrapolate_empty():
y_true = np.array([np.nan, False, np.nan])
y_score = np.array([1,0,.5])
assert top_k(y_true, y_score, 2, extrapolate=True) == (0,0)
def test_top_k_extrapolate():
y_true = np.array([True, False, np.nan])
y_score = np.array([1,0,.5])
assert top_k(y_true, y_score,2, extrapolate=True) == (1,1)
def test_top_k_null():
y_true = np.array([True, False, np.nan])
y_score = np.array([1,0,.5])
assert top_k(y_true, y_score,2) == (1,2)