affine

Affine transformation for probability distributions.

class pysatl_core.transformations.operations.distributions.affine.AffineDistribution(base_distribution, *, scale, shift=0.0, methods=None, sampling_strategy=None, computation_strategy=None)[source]

Bases: DerivedDistribution

Distribution obtained from the affine transformation Y = aX + b.

Parameters:

  • base_distribution (pysatl_core.distributions.distribution.Distribution) – Source distribution being transformed.

  • scale (float) – Multiplicative coefficient a.

  • shift (float) – Additive coefficient b.

  • methods (Mapping[str, Mapping[str, GenericAlias[Any, Any]]] | None) – Transformation methods for building derived characteristics. When None, built-in methods are used.

  • sampling_strategy (Optional[pysatl_core.distributions.strategies.SamplingStrategy]) – Sampling strategy exposed by the transformed distribution.

  • computation_strategy (Optional[pysatl_core.distributions.strategies.ComputationStrategy]) – Computation strategy exposed by the transformed distribution.

__init__(base_distribution, *, scale, shift=0.0, methods=None, sampling_strategy=None, computation_strategy=None)[source]
Parameters:
Return type:

None

property base_distribution: LightweightDistribution

Get the lightweight snapshot of the source distribution.

property parent_roles: tuple[ParentRole, ...]

Return parent role sequence for affine transformation.

property scale: float

Get the multiplicative coefficient a.

property shift: float

Get the additive coefficient b.

sample(n, **options)[source]

Generate affine samples from transformed base-distribution samples.

Return type:

GenericAlias[floating[Any] | integer[Any]]

Parameters:
pysatl_core.transformations.operations.distributions.affine.affine(distribution, *, scale, shift=0.0, methods=None)[source]

Apply the affine transformation Y = aX + b to a distribution.

Return type:

AffineDistribution

Parameters: