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()
def test_cdf(self, x):
dist = StandardNormal()
rng = NumericalInversePolynomial(dist,
keep_cdf=True,
u_resolution=1e-14)
# Older versions of NumPy throw RuntimeWarnings for comparisons
# with nan.
with suppress_warnings() as sup:
sup.filter(RuntimeWarning, "invalid value encountered in greater")
sup.filter(RuntimeWarning, "invalid value encountered in "
"greater_equal")
sup.filter(RuntimeWarning, "invalid value encountered in less")
sup.filter(RuntimeWarning, "invalid value encountered in "
"less_equal")
res = rng.cdf(x)
expected = stats.norm.cdf(x)
assert_allclose(res, expected, rtol=1e-11, atol=1e-11)
assert res.shape == expected.shape