deephyper.skopt.optimizer.acq_optimizer.pymoo_mixedga.Real

class deephyper.skopt.optimizer.acq_optimizer.pymoo_mixedga.Real(value: object | None = None, bounds: Tuple[object | None, object | None] = (None, None), strict: Tuple[object | None, object | None] | None = None, **kwargs: Any)

Bases: BoundedVariable

Class for the representation of bounded, real decision variables.

Methods

get	Get the value of a decision variable.
sample	Randomly sample n instances of a decision variable.
set	Set the value of a decision variable.

Attributes

lb	Lower bound of the decision variable.
ub	Upper bound of the decision variable.

get(**kwargs: Any) → object

Get the value of a decision variable.

Parameters:

kwargs (Any) – Additional keyword arguments.

Returns:

out – The value of the decision variable.

Return type:

object

property lb: object

Lower bound of the decision variable.

Returns:

out – The decision variable lower bound.

Return type:

object

sample(n: int | None = None) → object | ndarray

Randomly sample n instances of a decision variable.

Parameters:

n (int, None) – Number of decision variable samples which to draw. If int, sample n decision variables. If None, sample a single decision variables.

Returns:

out – If n is int, return a np.ndarray of shape (n,) containing sampled decision variables. If n is None, return an object of a sampled decision variable.

Return type:

object, np.ndarray

set(value: object) → None

Set the value of a decision variable.

Parameters:

value (object) – Value to assign to the decision variable.

property ub: object

Upper bound of the decision variable.

Returns:

out – The decision variable upper bound.

Return type:

object

vtype

alias of float