"""Example test for a pdf or function"""
import zfit
# Important, do the imports below
from zfit.core.testing import setup_function, teardown_function, tester
import zfit_physics as zphys
# specify globals here. Do NOT add any TensorFlow but just pure python
param1_true = 0.3
param2_true = 1.2
def test_special_property1():
# test special properties here
assert True
# register the pdf here and provide sets of working parameter configurations
def gauss_params_factory():
mu = zfit.Parameter('mu', param1_true)
sigma = zfit.Parameter('sigma', param2_true)
return {"mu": mu, "sigma": sigma}
tester.register_pdf(pdf_class=zfit.pdf.Gauss,
params_factories=gauss_params_factory)
kde = zphys.unstable.pdf.GaussianKDE(data=data, bandwidth=sigma, obs=obs)
probs = kde.pdf(x=data + 0.03)
from zfit.loss import UnbinnedNLL
data = tf.random.normal(shape=(100, 1))
data = zfit.Data.from_tensor(tensor=data, obs=obs)
nll = UnbinnedNLL(model=kde, data=data)
minimizer = zfit.minimize.Minuit()
minimum = minimizer.minimize(loss=nll)
assert minimum.converged
# register the pdf here and provide sets of working parameter configurations
def _kde_params_factory():
data = np.random.normal(size=(100, 3))
sigmas = [0.5, 1., 2]
lower = ((-5, -5, -5), )
upper = ((5, 5, 5), )
obs = zfit.Space(["obs1", "obs2", "obs3"], limits=(lower, upper))
return {"data": data, "sigma": sigmas, "obs": obs}
tester.register_pdf(pdf_class=zphys.unstable.pdf.GaussianKDE,
params_factories=_kde_params_factory())
nr = 4.0
bounds = (-10, 3.0)
lbounds = (bounds[0], mu)
rbounds = (mu, bounds[1])
def _cb_params_factory(name_add=""):
mu_ = zfit.Parameter('mu_cb' + name_add, mu)
sigma_ = zfit.Parameter('sigma_cb' + name_add, sigma)
alphal_ = zfit.Parameter('alphal_cb' + name_add, alphal)
nl_ = zfit.Parameter('nl_cb' + name_add, nl)
return {"mu": mu_, "sigma": sigma_, "alpha": alphal_, "n": nl_}
tester.register_pdf(pdf_class=CrystalBall, params_factories=_cb_params_factory)
def sample_testing(pdf):
sample = pdf.sample(n=1000, limits=(-0.5, 1.5))
sample_np = sample.numpy()
assert not any(np.isnan(sample_np))
def eval_testing(pdf, x):
probs = pdf.pdf(x).numpy()
assert not any(np.isnan(probs))
return probs
def test_cb_dcb():