computation

Computation Primitives and Conversions

Core building blocks for computing distribution characteristics and conversions between them (e.g., PDF to CDF, CDF to PPF).

class pysatl_core.distributions.computation.Computation(*args, **kwargs)[source]

Bases: Protocol, Generic

Protocol for computations that evaluate a single characteristic.

target

Name of the characteristic this computation produces.

Type:: str

property target: GenericCharacteristicName

__init__(*args, **kwargs)

class pysatl_core.distributions.computation.AnalyticalComputation(target, func)[source]

Bases: Generic

Analytical computation provided directly by a distribution.

Parameters:

target (str) – Characteristic name (e.g., “pdf”, “cdf”).
func (ComputationFunc[In, Out]) – Analytical function that computes the characteristic.

target: TypeAliasType

func: GenericAlias[TypeVar(In), TypeVar(Out)]

__call__(*args, **options)[source]

Evaluate the analytical function.

Return type:

typing.Any

Parameters:

args (Any)
options (Any)

__init__(target, func)

Parameters:

target (GenericCharacteristicName)
func (ComputationFunc[Any, Any])

Return type:

None

class pysatl_core.distributions.computation.FittedComputationMethod(target, sources, func)[source]

Bases: Generic

Fitted conversion method ready for use.

Parameters:

target (str) – Destination characteristic name.
sources (Sequence[str]) – Source characteristic names (typically length 1 for unary conversions).
func (ComputationFunc[In, Out]) – Callable implementing the fitted conversion.

target: TypeAliasType

sources: Sequence[TypeAliasType]

func: GenericAlias[TypeVar(In), TypeVar(Out)]

__call__(*args, **options)[source]

Evaluate the fitted conversion.

Return type:

typing.Any

Parameters:

args (Any)
options (Any)

__init__(target, sources, func)

Parameters:

target (GenericCharacteristicName)
sources (Sequence[GenericCharacteristicName])
func (ComputationFunc[Any, Any])

Return type:

None

class pysatl_core.distributions.computation.ComputationMethod(target, sources, fitter=None, evaluator=None)[source]

Bases: Generic

Factory for creating fitted computation methods.

This class represents a conversion method that needs to be fitted to a specific distribution before it can be used.

Parameters:

target (str) – Destination characteristic name.
sources (Sequence[str]) – Source characteristic names (typically length 1 for unary conversions).
fitter (Fitter[In, Out] | None) – Function that fits the computation method to a distribution. If provided, the method is considered cacheable (fitting may perform expensive precomputation).
evaluator (Evaluator[In, Out] | None) – Direct evaluator that performs the computation in one step, without a separate fitting stage. If provided, the method is considered non-cacheable at the strategy level.

target: TypeAliasType

sources: Sequence[TypeAliasType]

fitter: GenericAlias[TypeVar(In), TypeVar(Out)] | None

evaluator: GenericAlias[TypeVar(In), TypeVar(Out)] | None

__init__(target, sources, fitter=None, evaluator=None)

Parameters:

target (GenericCharacteristicName)
sources (Sequence[GenericCharacteristicName])
fitter (Fitter[Any, Any] | None)
evaluator (Evaluator[Any, Any] | None)

Return type:

None

property cacheable: bool: Whether it makes sense to cache the prepared method at strategy level.

prepare(distribution, **options)[source]

Prepare a callable method for a specific distribution. :rtype: FittedComputationMethod[typing.Any, typing.Any]

If fitter is provided, run the fitting stage and return the fitted method.
If evaluator is provided, bind the distribution and return a lightweight fitted wrapper.

Parameters: