def test_get_methods_of_factories():
"""Tests the get methods of a factory"""
x_values = [0, 0, 1]
y_values = [-1, 1, 0]
fac = LinearFactory(x_values)
fac._instack = [
{
"scale_factor": 0
},
{
"scale_factor": 0
},
{
"scale_factor": 1
},
]
fac._outstack = y_values
zne_reduce = fac.reduce()
assert np.allclose(fac.get_expectation_values(), y_values)
assert np.allclose(fac.get_extrapolation_curve()(0.0), zne_reduce)
assert np.allclose(fac.get_optimal_parameters(), [0.0, 0.0])
assert np.allclose(fac.get_parameters_covariance(),
[[3.0, -1.0], [-1.0, 1.0]])
assert np.allclose(fac.get_scale_factors(), x_values)
assert np.allclose(fac.get_zero_noise_limit(), zne_reduce)
assert np.allclose(fac.get_zero_noise_limit_error(), 1.0)
def test_push_after_already_reduced_warning():
"""Tests a warning is raised if new data is pushed in a factory
which was already reduced."""
fac = LinearFactory([1, 2])
fac.push({"scale_factor": 1.0}, 1.0)
fac.push({"scale_factor": 2.0}, 2.0)
fac.reduce()
with warns(
ExtrapolationWarning,
match=r"You are pushing new data into a factory object",
):
fac.push({"scale_factor": 3.0}, 3.0)
# Assert no warning is raised when .reset() is used
fac.reset()
fac.push({"scale_factor": 1.0}, 2.0)
fac.push({"scale_factor": 2.0}, 1.0)
assert np.isclose(3.0, fac.reduce())
def test_linear_extr():
"""Tests extrapolation with a LinearFactory."""
seeded_f = apply_seed_to_func(f_lin, SEED)
fac = LinearFactory(X_VALS)
assert not fac._opt_params
fac.run_classical(seeded_f)
assert np.isclose(fac.reduce(), seeded_f(0, err=0), atol=CLOSE_TOL)
assert np.allclose(fac._opt_params, [B, A], atol=CLOSE_TOL)
def test_linear_extr():
"""Tests extrapolation with a LinearFactory."""
seeded_f = apply_seed_to_func(f_lin, SEED)
fac = LinearFactory(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 np.allclose(fac._opt_params, [B, A], atol=CLOSE_TOL)
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,
)
