BQStandardBeliefUpdate

class probnum.quad.solvers.belief_updates.BQStandardBeliefUpdate(jitter, scale_estimation)

Bases: BQBeliefUpdate

Updates integral belief and state using standard Bayesian quadrature based on standard Gaussian process inference.

Parameters
  • jitter (FloatLike) – Non-negative jitter to numerically stabilise kernel matrix inversion.

  • scale_estimation (Optional[str]) – Estimation method to use to compute the scale parameter.

Return type

None

Methods Summary

__call__(bq_state, new_nodes, new_fun_evals, ...)

Updates integral belief and BQ state according to the new data given.

Methods Documentation

__call__(bq_state, new_nodes, new_fun_evals, *args, **kwargs)[source]

Updates integral belief and BQ state according to the new data given.

Parameters
  • bq_state (BQState) – Current state of the Bayesian quadrature loop.

  • new_nodes (ndarray) – shape=(n_eval_new, input_dim) – New nodes that have been added.

  • new_fun_evals (ndarray) – shape=(n_eval_new,) – Function evaluations at the given node.

Returns

  • updated_belief – Gaussian integral belief after conditioning on the new nodes and evaluations.

  • updated_state – Updated version of bq_state that contains all updated quantities.

Return type

Tuple[Normal, BQState]