Evaluation Classes

ropt.evaluation

The data exchanged between ropt and a user evaluation function.

An EvaluationBatchContext describes which rows must be evaluated, an EvaluationBatchResult carries the objective and constraint values back, and EvaluationBatchCallback is the protocol such a callable must follow. For the Evaluator classes that wrap them, see Evaluators.

See Writing Evaluation Callbacks for usage.

ropt.evaluation.EvaluationBatchContext dataclass

Per-batch metadata passed to evaluator functions.

See Writing Evaluation Callbacks for usage details and examples.

Attributes:

Name	Type	Description
context	EnOptContext	The EnOptContext for the run.
active	NDArray[bool_]	Boolean array indicating which rows require evaluation.
realizations	NDArray[intc]	Realization index for each row.
perturbations	NDArray[intc] | None	Perturbation index for each row (< 0 means unperturbed).
batch_id	int	Integer identifying the current evaluation batch.
metadata	dict[str, Any] | None	The metadata the run was started with, if any.

get_active_evaluations

get_active_evaluations(array: NDArray[T]) -> NDArray[T]

Return only the rows of array where active is True.

Parameters:

Name	Type	Description	Default
array	NDArray[T]	A 1-D or 2-D array with one entry/row per variable vector.	required

Returns:

Type	Description
NDArray[T]	The subset of rows corresponding to active evaluations.

insert_inactive_results

insert_inactive_results(
    array: NDArray[T], *, fill_value: float = 0.0
) -> NDArray[T]

Expand a filtered array back to full size, filling inactive rows.

Inserts fill_value at positions where active is False, restoring the array to its original number of rows.

Parameters:

Name	Type	Description	Default
array	NDArray[T]	The filtered array (output of get_active_evaluations).	required
fill_value	float	The value to insert for inactive entries.	0.0

Returns:

Type	Description
NDArray[T]	An expanded array matching the original number of rows.

ropt.evaluation.EvaluationBatchResult dataclass

Results of a function evaluation batch.

Stores objective values (and optional constraint values) for a batch of variable vectors. Inactive rows should be set to zero; failed active rows should be set to numpy.nan.

See Writing Evaluation Callbacks for batch_id management and other conventions.

Parameters:

Name	Type	Description	Default
objectives	NDArray[float64]	Objective values, shape (n_rows, n_objectives).	required
constraints	NDArray[float64] | None	Optional constraint values, shape (n_rows, n_constraints).	None
batch_id	int	Integer identifying this evaluation batch.	0
metadata	dict[str, NDArray[Any]]	Optional dict of per-row metadata (not used internally by ropt).	dict()

ropt.evaluation.EvaluationBatchCallback

Bases: Protocol

Defines the call signature for batch evaluation callbacks.

__call__

__call__(
    variables: NDArray[float64],
    context: EvaluationBatchContext,
) -> EvaluationBatchResult

Evaluate the given variables within the provided context.

Parameters:

Name	Type	Description	Default
variables	NDArray[float64]	The variables to pass to the evaluation function.	required
context	EvaluationBatchContext	The evaluator context to pass.	required

Returns:

Type	Description
EvaluationBatchResult	The results of the evaluation.