Strategy

class aixd.sampler.strategies.Strategy(features: DataObject | List[DataObject], engine: SamplingEngine | str, **kwargs)[source]

Bases: object

Receives samples from the range [0, 1]^len(features) and maps them to the feature-space according to some strategy. NOTE: currently, there is no seeding mechanism, as we expect full randomness when sampling new points. Before it ocurred that the same points were sampled, which is not desirable.

Parameters:

features (Union[DataObject, List[DataObject]]) – The features refer to the data objects, which contain the information about the domain of the features.
engine (Union[SamplingEngine, str]) – The different engines, such as GridamplingEngine, SobolSamplingEngine, RandomSamplingEngine, LHCSamplingEngine, etc.

Methods

`fit`	Fit the strategy to the data, also using some vectors of objectives and validity values.
`reset_states`	Reset the state of the engine.
`sample`
`update`	Updates the state of the sampling methods by providing the performance of the generated samples in the form of objectives and validity.