def test_frequentist_calculator_one_poi(constraint):
with pytest.raises(TypeError):
FrequentistCalculator()
loss, (mean, sigma) = create_loss(constraint=constraint)
calc = FrequentistCalculator(loss, Minuit(), ntoysnull=100, ntoysalt=100)
assert calc.ntoysnull == 100
assert calc.ntoysalt == 100
samplers = calc.sampler(floating_params=[mean])
assert all(is_valid_data(s) for s in samplers)
loss = calc.toys_loss(mean.name)
assert is_valid_loss(loss)
def test_with_gauss_fluctuations():
x_true = -2.0
minimizer = Minuit()
bounds = (-10, 10)
obs = zfit.Space("x", limits=bounds)
mean = zfit.Parameter("mean", 0)
sigma = zfit.Parameter("sigma", 1.0)
model = zfit.pdf.Gauss(obs=obs, mu=mean, sigma=sigma)
npzfile = f"{notebooks_dir}/toys/FC_toys_{x_true}.npz"
data = zfit.data.Data.from_numpy(obs=obs, array=np.load(npzfile)["x"])
nll = UnbinnedNLL(model=model, data=data)
minimum = minimizer.minimize(loss=nll)
minimum.hesse()
toys_fname = f"{notebooks_dir}/toys/FC_toys_{x_true}.yml"
calculator = FrequentistCalculator.from_yaml(toys_fname, minimum,
minimizer)
keys = np.unique([k[0].value for k in calculator.keys()])
keys.sort()
poinull = POIarray(mean, keys)
ci = ConfidenceInterval(calculator, poinull, qtilde=False)
with pytest.warns(UserWarning):
ci.interval(alpha=0.05, printlevel=0)
ci = ConfidenceInterval(calculator, poinull, qtilde=True)
ci.interval(alpha=0.05, printlevel=0)
def test_with_frequentist_calculator():
loss, (Nsig, Nbkg) = create_loss()
calculator = FrequentistCalculator.from_yaml(
f"{notebooks_dir}/toys/discovery_freq_zfit_toys.yml", loss, Minuit())
poinull = POI(Nsig, 0)
discovery_test = Discovery(calculator, poinull)
pnull, significance = discovery_test.result()
assert pnull == pytest.approx(0.0004, rel=0.05, abs=0.0005)
assert significance == pytest.approx(3.3527947805048592, rel=0.05, abs=0.1)
assert significance >= 3
def test_counting_with_frequentist_calculator():
(
loss,
Nsig,
) = create_loss_counting()
calculator = FrequentistCalculator(loss, Minuit(), ntoysnull=1000)
poinull = POI(Nsig, 0)
discovery_test = Discovery(calculator, poinull)
pnull, significance = discovery_test.result()
assert significance < 2
def freq_calc():
loss, mean = create_loss()
calculator = FrequentistCalculator.from_yaml(
f"{notebooks_dir}/toys/ci_freq_zfit_toys.yml", loss, Minuit())
return mean, calculator
def freq_calc():
loss, (Nsig, Nbkg) = create_loss()
calculator = FrequentistCalculator.from_yaml(
f"{notebooks_dir}/toys/upperlimit_freq_zfit_toys.yml", loss, Minuit())
return Nsig, calculator