probnum.quad

Quadrature / Numerical Integration of Functions.

This package implements Bayesian quadrature rules used for numerical integration of functions on a given domain. Such methods integrate a function by iteratively building a probabilistic model and adaptively choosing points to evaluate the integrand based on said model.

Functions

bayesquad(fun, input_dim[, kernel, domain, ...])	Infer the solution of the uni- or multivariate integral \(\int_\Omega f(x) d \mu(x)\) on a hyper-rectangle \(\Omega = [a_1, b_1] \times \cdots \times [a_D, b_D]\) or \(\Omega = \mathbb{R}^D\).
bayesquad_from_data(nodes, fun_evals[, ...])	Infer the value of an integral from a given set of nodes and function evaluations.

Classes

BayesianQuadrature(kernel, measure, policy, ...)	The Bayesian quadrature method.
ImmediateStop()	Dummy stopping criterion that always stops.
IntegrationMeasure(domain, input_dim)	An abstract class for a measure against which a target function is integrated.
ImmediateStop()	Dummy stopping criterion that always stops.
KernelEmbedding(kernel, measure)	Integrals over kernels against integration measures.
GaussianMeasure(mean, cov[, input_dim])	Gaussian measure on Euclidean space with given mean and covariance.
LebesgueMeasure(domain[, input_dim, normalized])	Lebesgue measure on a hyper-rectangle.
BQStoppingCriterion()	Stopping criterion of a Bayesian quadrature method.
IntegralVarianceTolerance(var_tol)	Stop once the integral variance is below some tolerance.
MaxNevals(max_nevals)	Stop once a maximum number of integrand evaluations is reached.
RandomPolicy(sample_func, batch_size[, rng])	Random sampling from an objective.
RelativeMeanChange(rel_tol)	Stop once the relative change of consecutive integral estimates are smaller than a tolerance.

Class Inheritance Diagram