def test_richardson_extr(test_f: Callable[[float], float]):
"""Test of the Richardson's extrapolator."""
seeded_f = apply_seed_to_func(test_f, SEED)
fac = RichardsonFactory(scale_factors=X_VALS)
assert not fac._opt_params
fac.run_classical(seeded_f)
zne_value = fac.reduce()
assert np.isclose(zne_value, seeded_f(0, err=0), atol=CLOSE_TOL)
assert len(fac._opt_params) == len(X_VALS)
assert np.isclose(fac._opt_params[-1], zne_value)
exp_vals = fac.get_expectation_values()
assert np.isclose(fac.extrapolate(X_VALS, exp_vals), zne_value)
assert np.isclose(
fac.extrapolate(X_VALS, exp_vals, full_output=True)[0], zne_value,
)
def test_fake_nodes_extrapolation():
"""Test that there exists a regime in which FakeNodesFactory
is better than RichardsonFactory.
Note: in many cases RichardsonFactory is better.
"""
y_vals = [f_runge(x) for x in UNIFORM_X]
zne_runge = FakeNodesFactory.extrapolate(UNIFORM_X, y_vals)
zne_richard = RichardsonFactory.extrapolate(UNIFORM_X, y_vals)
abs_err_runge = np.abs(zne_runge - f_runge(0.0))
abs_err_richard = np.abs(zne_richard - f_runge(0.0))
# Test Richardson extrapolation error is much larger
assert 500 * abs_err_runge < abs_err_richard