def test_lag_k_estimation_for_positive_k():
data = [-1, 0, 1, 0] * 10
st = Statistic(data)
np.testing.assert_almost_equal(st.lag(0), 1)
np.testing.assert_almost_equal(st.lag(1), 0)
np.testing.assert_almost_equal(st.lag(2), -1)
np.testing.assert_almost_equal(st.lag(3), 0)
def test_lag_0_is_always_1():
st1 = Statistic([10])
st2 = Statistic([-1, 1] * 5)
st3 = Statistic(np.random.exponential(1, 7))
assert st1.lag(0) == 1
assert st2.lag(0) == 1
assert st3.lag(0) == 1
def test_lag_k_raises_error_when_passed_negative_or_float():
st = Statistic([1, 2, 3])
with pytest.raises(ValueError) as excinfo:
st.lag(-1)
assert 'non-negative integer expected' in str(excinfo.value).lower()
with pytest.raises(ValueError) as excinfo:
st.lag(2.5)
assert 'non-negative integer expected' in str(excinfo.value).lower()
def test_lag_k_raises_error_when_k_greater_then_length():
st = Statistic([1, 2])
error_message = 'statistic has too few samples'
with pytest.raises(ValueError) as excinfo1:
st.lag(2)
with pytest.raises(ValueError) as excinfo2:
st.lag(3)
assert error_message in str(excinfo1.value).lower()
assert error_message in str(excinfo2.value).lower()
def test_lag_k_raises_error_when_called_for_empty_statistic():
st = Statistic()
with pytest.raises(ValueError) as excinfo:
st.lag(1)
assert 'no data' in str(excinfo.value).lower()