piglot.optimisers.botorch.bayes.BayesianBoTorch

class BayesianBoTorch(objective: Objective, n_initial: int | None = None, n_test: int = 0, acquisition: str | None = None, beta: float = 1.0, noisy: float = False, q: int = 1, seed: int = 1, load_file: str | None = None, export: str | None = None, device: str | None = None, reference_point: List[float] | None = None, nadir_scale: float = 0.1, skip_initial: bool = False, pca_variance: float | None = None, num_restarts: int | None = None, raw_samples: int | None = None, mc_samples: int | None = None, batch_size: int | None = None, num_fantasies: int | None = None, sequential: bool = False)

Bases: Optimiser

Driver for optimisation using BoTorch.

Methods

optimise

Optimiser for the outside world.

optimise(n_iter: int, parameters: ~piglot.parameter.ParameterSet, output_dir: str, stop_criteria: ~piglot.optimiser.StoppingCriteria = <piglot.optimiser.StoppingCriteria object>, verbose: bool = True) → Tuple[float, ndarray]

Optimiser for the outside world.

Parameters

objectiveObjective

Objective function to optimise.

n_iterint

Maximum number of iterations.

parametersParameterSet

Set of parameters to optimise.

output_dirstr

Whether to write output to the output directory, by default None.

stop_criteriaStoppingCriteria

List of stopping criteria, by default none attributed.

verbosebool

Whether to output progress status, by default True.

Returns

float

Best observed objective value.

np.ndarray

Observed optimum of the objective.