def test_analytic_integral():
class DistFunc3(zbasepdf.BasePDF):
def _unnormalized_pdf(self, x):
return func3_2deps(x)
mu_true = 1.4
sigma_true = 1.8
limits = -4.3, 1.9
mu = Parameter("mu_1414", mu_true, mu_true - 2., mu_true + 7.)
sigma = Parameter("sigma_1414", sigma_true, sigma_true - 10., sigma_true + 5.)
gauss_params1 = CustomGaussOLD(mu=mu, sigma=sigma, obs=obs1, name="gauss_params1")
normal_params1 = Gauss(mu=mu, sigma=sigma, obs=obs1, name="gauss_params1")
try:
infinity = mt.inf
except AttributeError: # py34
infinity = float('inf')
gauss_integral_infs = gauss_params1.integrate(limits=(-8 * sigma_true, 8 * sigma_true), norm_range=False)
normal_integral_infs = normal_params1.integrate(limits=(-8 * sigma_true, 8 * sigma_true), norm_range=False)
DistFunc3.register_analytic_integral(func=func3_2deps_fully_integrated,
limits=Space(limits=limits3, axes=(0, 1)))
dist_func3 = DistFunc3(obs=['obs1', 'obs2'])
normal_integral_infs = normal_integral_infs
func3_integrated = dist_func3.integrate(limits=Space(limits=limits3, axes=(0, 1)),
norm_range=False).numpy()
assert func3_integrated == pytest.approx(
func3_2deps_fully_integrated(limits=Space(limits=limits3, axes=(0, 1))).numpy())
assert gauss_integral_infs.numpy() == pytest.approx(np.sqrt(np.pi * 2.) * sigma_true, rel=0.0001)
assert normal_integral_infs.numpy() == pytest.approx(1, rel=0.0001)
def test_product_separation():
mu1, mu2, mu3, sigma1, sigma2, sigma3 = create_params()
gauss1 = Gauss(mu=mu1, sigma=sigma1, obs=obs1, name="gauss1asum")
gauss2 = Gauss(mu=mu2, sigma=sigma2, obs=obs2, name="gauss2asum")
gauss3 = Gauss(mu=mu3, sigma=sigma3, obs=obs1, name="gauss3asum")
gauss4 = Gauss(mu=mu3, sigma=sigma3, obs=obs3, name="gauss3asum")
gauss5 = Gauss(mu=mu3, sigma=sigma3, obs=obs4, name="gauss3asum")
prod12 = ProductPDF(pdfs=[gauss1, gauss2, gauss3])
assert not prod12._prod_is_same_obs_pdf
prod13 = ProductPDF(pdfs=[gauss3, gauss4])
assert not prod13._prod_is_same_obs_pdf
prod123 = ProductPDF([prod12, prod13])
assert prod123._prod_is_same_obs_pdf
npoints = 2000
data3 = zfit.Data.from_numpy(array=np.linspace(0, 1, npoints), obs=obs3)
data2 = zfit.Data.from_numpy(array=np.linspace(0, 1, npoints), obs=obs2)
data1 = zfit.Data.from_numpy(array=np.linspace(0, 1, npoints), obs=obs1)
data4 = zfit.Data.from_numpy(array=np.linspace(0, 1, npoints), obs=obs4)
integral13 = prod13.partial_integrate(x=data3, limits=obs1, norm=False)
assert integral13.shape[0] == npoints
trueint3 = gauss4.pdf(data3, norm=False) * gauss3.integrate(obs1,
norm=False)
np.testing.assert_allclose(integral13, trueint3)
assert (prod12.partial_integrate(
x=data2,
limits=obs1,
).shape[0] == npoints)
assert (prod123.partial_integrate(
x=data3,
limits=obs1 * obs2,
).shape[0] == npoints)
assert (prod123.partial_integrate(
x=data2,
limits=obs1 * obs3,
).shape[0] == npoints)
prod1234 = ProductPDF(pdfs=[gauss1, gauss2, gauss4, gauss5])
integ = prod1234.partial_integrate(data1,
limits=obs2 * obs3 * obs4,
norm=False)
assert integ.shape[0] == npoints
obs13 = obs1 * obs3
analytic_int = zfit.run(prod13.analytic_integrate(limits=obs13,
norm=False))
numeric_int = zfit.run(prod13.numeric_integrate(limits=obs13, norm=False))
assert pytest.approx(analytic_int, rel=1e-3) == numeric_int
def test_analytic_integral():
class DistFunc3(BasePDF):
def _unnormalized_pdf(self, x):
return func3_2deps(x)
class CustomGaussOLD(BasePDF):
def __init__(self, mu, sigma, obs, name="Gauss"):
super().__init__(name=name,
obs=obs,
params=dict(mu=mu, sigma=sigma))
def _unnormalized_pdf(self, x):
x = x.unstack_x()
mu = self.params["mu"]
sigma = self.params["sigma"]
gauss = znp.exp(-0.5 * tf.square((x - mu) / sigma))
return gauss
def _gauss_integral_from_inf_to_inf(limits, params, model):
return tf.sqrt(2 * znp.pi) * params["sigma"]
CustomGaussOLD.register_analytic_integral(
func=_gauss_integral_from_inf_to_inf,
limits=Space(limits=(-np.inf, np.inf), axes=(0, )),
)
mu_true = 1.4
sigma_true = 1.8
mu = Parameter("mu_1414", mu_true, mu_true - 2.0, mu_true + 7.0)
sigma = Parameter("sigma_1414", sigma_true, sigma_true - 10.0,
sigma_true + 5.0)
gauss_params1 = CustomGaussOLD(mu=mu,
sigma=sigma,
obs=obs1,
name="gauss_params1")
normal_params1 = Gauss(mu=mu, sigma=sigma, obs=obs1, name="gauss_params1")
gauss_integral_infs = gauss_params1.integrate(limits=(-8 * sigma_true,
8 * sigma_true),
norm=False)
normal_integral_infs = normal_params1.integrate(
limits=(-8 * sigma_true, 8 * sigma_true),
norm=False,
)
DistFunc3.register_analytic_integral(func=func3_2deps_fully_integrated,
limits=Space(limits=limits3,
axes=(0, 1)))
dist_func3 = DistFunc3(obs=["obs1", "obs2"])
normal_integral_infs = normal_integral_infs
func3_integrated = dist_func3.integrate(
limits=Space(limits=limits3, axes=(0, 1)),
norm=False,
).numpy()
assert func3_integrated == pytest.approx(
func3_2deps_fully_integrated(
limits=Space(limits=limits3, axes=(0, 1))).numpy())
assert gauss_integral_infs.numpy() == pytest.approx(np.sqrt(np.pi * 2.0) *
sigma_true,
rel=0.0001)
assert normal_integral_infs.numpy() == pytest.approx(1, rel=0.0001)
