def test_with_gauss_qtilde(n, min_x):
sigma_x = 0.032
minimizer = Minuit()
bounds = (-10, 10)
obs = zfit.Space("x", limits=bounds)
mean = zfit.Parameter("mean", n * sigma_x)
sigma = zfit.Parameter("sigma", 1.0)
model = zfit.pdf.Gauss(obs=obs, mu=mean, sigma=sigma)
data = model.sample(n=1000)
nll = UnbinnedNLL(model=model, data=data)
minimum = minimizer.minimize(loss=nll)
minimum.hesse()
x = minimum.params[mean]["value"]
x_err = minimum.params[mean]["minuit_hesse"]["error"]
x_min = x - x_err * 3
x_max = x + x_err * 3
x_min = max([x_min, min_x])
poinull = POIarray(mean, np.linspace(x_min, x_max, 50))
calculator = AsymptoticCalculator(nll, minimizer)
ci = ConfidenceInterval(calculator, poinull, qtilde=True)
ci.interval(alpha=0.05, printlevel=1)
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_constructor():
with pytest.raises(TypeError):
ConfidenceInterval()
loss, mean = create_loss()
calculator = BaseCalculator(loss, Minuit())
poi_1 = POI(mean, 1.5)
poi_2 = POI(mean, 1.2)
with pytest.raises(TypeError):
ConfidenceInterval(calculator)
with pytest.raises(TypeError):
ConfidenceInterval(calculator, [poi_1], poi_2, qtilde=True)
with pytest.raises(TypeError):
ConfidenceInterval(calculator, [poi_1], [poi_2], qtilde=False)
def test_with_gauss_exp_example(calculator):
mean, calculator = calculator()
scan_values = np.linspace(1.15, 1.26, 50)
poinull = POIarray(mean, scan_values)
ci = ConfidenceInterval(calculator, poinull)
interval = ci.interval()
assert interval["lower"] == pytest.approx(1.1810371356602791, rel=0.1)
assert interval["upper"] == pytest.approx(1.2156701172321935, rel=0.1)
with pytest.raises(POIRangeError):
poinull = POIarray(
mean, scan_values[(scan_values >= 1.2) & (scan_values <= 1.205)])
ci = ConfidenceInterval(calculator, poinull)
ci.interval()
with pytest.raises(POIRangeError):
poinull = POIarray(mean, scan_values[(scan_values >= 1.2)])
ci = ConfidenceInterval(calculator, poinull)
ci.interval()
with pytest.raises(POIRangeError):
poinull = POIarray(mean, scan_values[(scan_values <= 1.205)])
ci = ConfidenceInterval(calculator, poinull)
ci.interval()