def test_extended_gauss():
mu1 = Parameter("mu11", 1.0)
mu2 = Parameter("mu21", 12.0)
mu3 = Parameter("mu31", 3.0)
sigma1 = Parameter("sigma11", 1.0)
sigma2 = Parameter("sigma21", 12.0)
sigma3 = Parameter("sigma31", 33.0)
yield1 = Parameter("yield11", 150.0)
yield2 = Parameter("yield21", 550.0)
yield3 = Parameter("yield31", 2500.0)
gauss1 = Gauss(mu=mu1, sigma=sigma1, obs=obs1, name="gauss11")
gauss2 = Gauss(mu=mu2, sigma=sigma2, obs=obs1, name="gauss21")
gauss3 = Gauss(mu=mu3, sigma=sigma3, obs=obs1, name="gauss31")
gauss1 = gauss1.create_extended(yield1)
gauss2 = gauss2.create_extended(yield2)
gauss3 = gauss3.create_extended(yield3)
gauss_dists = [gauss1, gauss2, gauss3]
sum_gauss = SumPDF(pdfs=gauss_dists)
integral_true = (sum_gauss.integrate((-1, 5), ) * sum_gauss.get_yield())
assert zfit.run(integral_true) == pytest.approx(
zfit.run(sum_gauss.ext_integrate((-1, 5), )))
normalization_testing(pdf=sum_gauss, limits=obs1)
def test_extended_gauss():
with tf.name_scope("gauss_params2"):
mu1 = Parameter("mu11", 1.)
mu2 = Parameter("mu21", 12.)
mu3 = Parameter("mu31", 3.)
sigma1 = Parameter("sigma11", 1.)
sigma2 = Parameter("sigma21", 12.)
sigma3 = Parameter("sigma31", 33.)
yield1 = Parameter("yield11", 150.)
yield2 = Parameter("yield21", 550.)
yield3 = Parameter("yield31", 2500.)
sum_yields = 150 + 550 + 2500
gauss1 = Gauss(mu=mu1, sigma=sigma1, obs=obs1, name="gauss11")
gauss2 = Gauss(mu=mu2, sigma=sigma2, obs=obs1, name="gauss21")
gauss3 = Gauss(mu=mu3, sigma=sigma3, obs=obs1, name="gauss31")
gauss1 = gauss1.create_extended(yield1)
gauss2 = gauss2.create_extended(yield2)
gauss3 = gauss3.create_extended(yield3)
gauss_dists = [gauss1, gauss2, gauss3]
sum_gauss = SumPDF(
pdfs=gauss_dists,
obs=obs1,
)
normalization_testing(pdf=sum_gauss, normalization_value=sum_yields)
def create_gauss3ext():
mu, sigma, yield3 = create_params3()
gaussian3 = Gauss(mu, sigma, obs=obs1, name="gaussian3")
gaussian3 = gaussian3.create_extended(yield3)
return gaussian3, mu, sigma, yield3
sigma1 = Parameter("sigma1", ztf.to_real(sigma_true) - 0.3, sigma_true - 2., sigma_true + 2.)
mu2 = Parameter("mu25", ztf.to_real(mu_true) - 0.2, mu_true - 1., mu_true + 1.)
sigma2 = Parameter("sigma25", ztf.to_real(sigma_true) - 0.3, sigma_true - 2., sigma_true + 2.)
mu3 = Parameter("mu35", ztf.to_real(mu_true) - 0.2, mu_true - 1., mu_true + 1.)
sigma3 = Parameter("sigma35", ztf.to_real(sigma_true) - 0.3, sigma_true - 2., sigma_true + 2.)
yield3 = Parameter("yield35", yield_true + 300, 0, yield_true + 20000)
obs1 = 'obs1'
mu_constr = [1.6, 0.2] # mu, sigma
sigma_constr = [3.8, 0.2]
gaussian1 = Gauss(mu1, sigma1, obs=obs1, name="gaussian1")
gaussian2 = Gauss(mu2, sigma2, obs=obs1, name="gaussian2")
gaussian3 = Gauss(mu3, sigma3, obs=obs1, name="gaussian3")
gaussian3 = gaussian3.create_extended(yield3)
def test_extended_unbinned_nll():
test_values = ztf.constant(test_values_np)
test_values = zfit.data.Data.from_tensor(obs=obs1, tensor=test_values)
nll_object = zfit.loss.ExtendedUnbinnedNLL(model=gaussian3,
data=test_values,
fit_range=(-20, 20))
minimizer = MinuitMinimizer()
status = minimizer.minimize(loss=nll_object, params=[mu3, sigma3, yield3])
params = status.params
assert params[mu3]['value'] == pytest.approx(np.mean(test_values_np), rel=0.005)
assert params[sigma3]['value'] == pytest.approx(np.std(test_values_np), rel=0.005)
assert params[yield3]['value'] == pytest.approx(yield_true, rel=0.005)
