ShiftedRotatedLevy#

class ShiftedRotatedLevy(n_dim: int = 10, objective: str = 'minimize', modifiers: List[BaseModifier] | None = None, memory: bool = False, collect_data: bool = True, callbacks: Callable | List[Callable] | None = None, catch_errors: Dict[type, float] | None = None)[source]#

F9: Shifted and Rotated Levy Function.

Properties: - Multimodal - Non-separable - Scalable

__call__(params: Dict[str, Any] | ndarray | list | tuple | None = None, **kwargs)[source]#

Evaluate the objective function.

Args:: params: Parameter values as dict, array, list, or tuple **kwargs: Parameters as keyword arguments (only with dict input)
Returns:: The objective function value

batch(X: ArrayLike) → ArrayLike[source]#

Evaluate multiple parameter sets in a single call.

Parameters:

X (ArrayLike) – 2D array of shape (n_points, n_dim) where each row is a parameter set.

Returns:

1D array of shape (n_points,) with evaluation results.

Return type:

ArrayLike

Raises:

NotImplementedError – If the function does not implement _batch_objective.
ValueError – If X has wrong number of dimensions or wrong n_dim.

property callbacks[source]#: Callback management (CallbackAccessor).

property data[source]#: Evaluation data (DataAccessor).

property errors[source]#: Error handler management (ErrorAccessor).

property f_global: float[source]#

Global optimum value for this function.

CEC 2017 formula: f* = func_id * 100

property func_id: int | None[source]#: Function ID within the CEC suite.

property memory[source]#: Memory cache management (MemoryAccessor).

property meta[source]#: Function metadata (MetaAccessor).

property modifiers[source]#: Modifier management (ModifierAccessor).

property plot[source]#: Access plotting methods for this function.

pure(params: Dict[str, Any] | ndarray | list | tuple | None = None, **kwargs)[source]#

Evaluate the function without modifiers.

Returns the true (deterministic) function value, bypassing any configured modifiers. Does not update search_data, n_evaluations, or callbacks. Ignores memory caching.

Parameters:

params (dict, array, list, or tuple) – Parameter values to evaluate.
**kwargs (dict) – Parameters as keyword arguments.

Returns:

The true function value without modifiers, with direction applied.

Return type:

float or np.ndarray

reset() → None[source]#: Reset all state including collected data and memory cache.

property search_space: Dict[str, Any][source]#: Search space for this function (read-only public API).

property spec[source]#: Function characteristics (SpecAccessor).

property x_global: ndarray | None[source]#: Global optimum location (the shift vector).