saealib.MeanPrediction

class saealib.MeanPrediction(weights=None, reference=None, direction=None)

ベースクラス: PointwiseAcquisition

Acquisition function based on predicted mean value (exploitation).

For single-objective problems, returns the predicted mean directly. For multi-objective problems, returns a weighted scalarization of the predicted mean.

A higher score indicates a more promising candidate. The sign convention follows the weight: use a negative weight for minimization (e.g., weights=np.array([-1.0])) so that lower objective values yield higher scores.

パラメータ:

• weights (np.ndarray or None) -- Weights for magnitude-aware scalarization of multi-objective predictions. shape: (n_obj,). If None and direction is also None, uses the first objective only.

• direction (np.ndarray or None) -- Per-objective optimization directions (+1 = maximize, -1 = minimize). Used for direction-only scalarization when magnitude does not matter. Takes precedence over weights when both are provided. When unset, it is auto-injected from problem.direction at run start.

• reference (Any)

Methods

__init__
compute_reference	Return fixed reference if set, otherwise None.
contract	Return the pointwise acquisition contract.
evaluate	Reject prediction is None, resolve the reference, then score().
prepare	Delegate to compute_reference(archive, rng=ctx.rng if ctx else None).
score	Compute scores based on predicted mean.

Method Details

MeanPrediction.__init__(weights=None, reference=None, direction=None)

パラメータ:

• weights (ndarray | None)

• reference (Any)

• direction (ndarray | None)

MeanPrediction.compute_reference(archive, rng=None)

Return fixed reference if set, otherwise None.

パラメータ:

• archive (Archive)

• rng (np.random.Generator | None)

戻り値の型:

Any

MeanPrediction.contract()

Return the pointwise acquisition contract.

戻り値の型:

ComponentContract

MeanPrediction.evaluate(candidates_x, prediction, archive, ctx=None, *, prepared=<object object>)

Reject prediction is None, resolve the reference, then score().

See AcquisitionFunction.evaluate() for the shared parameter contract, including the _UNSET vs. explicit prepared=None distinction.

パラメータ:

• candidates_x (np.ndarray)

• prediction (SurrogatePrediction | None)

• archive (Archive)

• ctx (OptimizationState | None)

• prepared (Any)

戻り値の型:

AcquisitionResult

MeanPrediction.prepare(archive, ctx=None)

Delegate to compute_reference(archive, rng=ctx.rng if ctx else None).

パラメータ:

• archive (Archive)

• ctx (OptimizationState | None)

戻り値の型:

Any

MeanPrediction.score(prediction, reference=None, rng=None)

Compute scores based on predicted mean.

パラメータ:

• prediction (SurrogatePrediction) -- Surrogate predictions. prediction.value shape: (n_samples, n_obj)

• reference (Any) -- Not used. Accepted for interface compatibility.

• rng (Generator | None)

戻り値:

Scores. shape: (n_samples,)

戻り値の型:

np.ndarray