def test_u_error(self):
dist = StandardNormal()
rng = NumericalInversePolynomial(dist, u_resolution=1e-10)
max_error, mae = rng.u_error()
assert max_error < 1e-10
assert mae <= max_error
rng = NumericalInversePolynomial(dist, u_resolution=1e-14)
max_error, mae = rng.u_error()
assert max_error < 1e-14
assert mae <= max_error
def test_bad_args(self):
dist = StandardNormal()
rng = NumericalInversePolynomial(dist)
msg = r"CDF is not available."
with pytest.raises(ValueError, match=msg):
rng.cdf([1, 2, 3])
msg = r"`sample_size` must be greater than or equal to 1000."
with pytest.raises(ValueError, match=msg):
rng.u_error(10)
class Distribution:
def pdf(self, x):
return np.exp(-0.5 * x * x)
dist = Distribution()
rng = NumericalInversePolynomial(dist)
msg = r"Exact CDF required but not found."
with pytest.raises(ValueError, match=msg):
rng.u_error()