ContinuousLinearConstraint¶

class baybe.constraints.continuous.ContinuousLinearConstraint[source]¶

Class for continuous linear constraints.

Continuous linear constraints use parameter lists and coefficients to define in-/equality constraints over a continuous parameter space.

Public methods

`__init__`(parameters, operator[, ...])	Method generated by attrs for class ContinuousLinearConstraint.
`from_dict`(dictionary)	Create an object from its dictionary representation.
`from_json`(string)	Create an object from its JSON representation.
`summary`()	Return a custom summarization of the constraint.
`to_botorch`(parameters[, idx_offset])	Cast the constraint in a format required by botorch.
`to_dict`()	Create an object's dictionary representation.
`to_json`()	Create an object's JSON representation.

Public attributes and properties

`operator`	Defines the operator used in the equation.
`coefficients`	In-/equality coefficient for each entry in `parameters`.
`rhs`	Right-hand side value of the in-/equality.
`eval_during_augmentation`	Class variable encoding whether the constraint could be considered during data augmentation.
`eval_during_creation`	Class variable encoding whether the condition is evaluated during creation.
`eval_during_modeling`	Class variable encoding whether the condition is evaluated during modeling.
`is_continuous`	Boolean indicating if this is a constraint over continuous parameters.
`is_discrete`	Boolean indicating if this is a constraint over discrete parameters.
`is_eq`	Whether this constraint models an equality (assumed inequality otherwise).
`numerical_only`	Class variable encoding whether the constraint is valid only for numerical parameters.
`parameters`	The list of parameters used for the constraint.

__init__(parameters: list[str], operator: str, coefficients: list[float] = NOTHING, rhs=0.0)¶

Method generated by attrs for class ContinuousLinearConstraint.

For details on the parameters, see Public attributes and properties.

classmethod from_dict(dictionary: dict)¶

Create an object from its dictionary representation.

classmethod from_json(string: str)¶

Create an object from its JSON representation.

summary()¶

Return a custom summarization of the constraint.

to_botorch(parameters: Sequence[NumericalContinuousParameter], idx_offset: int = 0)[source]¶

Cast the constraint in a format required by botorch.

Parameters:

parameters (Sequence[NumericalContinuousParameter]) – The parameter objects of the continuous space.
idx_offset (int) – Offset to the provided parameter indices.

Return type:

tuple[Tensor, Tensor, float]

Returns:

The tuple required by botorch.

to_dict()¶

Create an object’s dictionary representation.

to_json()¶

Create an object’s JSON representation.

coefficients: list[float]¶: In-/equality coefficient for each entry in parameters.

eval_during_augmentation: ClassVar[bool] = False¶: Class variable encoding whether the constraint could be considered during data augmentation.

eval_during_creation: ClassVar[bool] = False¶: Class variable encoding whether the condition is evaluated during creation.

eval_during_modeling: ClassVar[bool] = True¶: Class variable encoding whether the condition is evaluated during modeling.

property is_continuous: bool¶: Boolean indicating if this is a constraint over continuous parameters.

property is_discrete: bool¶: Boolean indicating if this is a constraint over discrete parameters.

property is_eq¶: Whether this constraint models an equality (assumed inequality otherwise).

numerical_only: ClassVar[bool] = True¶: Class variable encoding whether the constraint is valid only for numerical parameters.

operator: str¶: Defines the operator used in the equation. Internally this will negate rhs and coefficients for <=.