refactor: strategies now is one per distribution

Author: LeonidElkin

src/pysatl_core/distributions/distribution.py

@@ -48,9 +48,10 @@ class Distribution(Protocol):
     analytical_computations : Mapping[str, AnalyticalComputation]
         Direct analytical computations provided by the distribution.
     sampling_strategy : SamplingStrategy
-        Strategy for generating random samples.
+        Strategy for generating random samples. Such an object is unique for each distribution.
     computation_strategy : ComputationStrategy
         Strategy for computing characteristics and conversions.
+        Such an object is unique for each distribution.
     support : Support or None
         Support of the distribution, if defined.
     """

src/pysatl_core/families/distribution.py

@@ -11,11 +11,13 @@
 __copyright__ = "Copyright (c) 2025 PySATL project"
 __license__ = "SPDX-License-Identifier: MIT"
 
-
-from dataclasses import dataclass
 from typing import TYPE_CHECKING, cast
 
 from pysatl_core.distributions.distribution import Distribution
+from pysatl_core.distributions.strategies import (
+    DefaultComputationStrategy,
+    DefaultSamplingUnivariateStrategy,
+)
 from pysatl_core.families.registry import ParametricFamilyRegister
 from pysatl_core.types import NumericArray
 
@@ -40,8 +42,9 @@
         ParametrizationName,
     )
 
+_KEEP: object = object()
+
 
-@dataclass(slots=True)
 class ParametricFamilyDistribution(Distribution):
     """
     A specific distribution instance from a parametric family.
@@ -53,18 +56,45 @@ class ParametricFamilyDistribution(Distribution):
     ----------
     family_name : str
         Name of the distribution family.
-    _distribution_type : DistributionType
+    distribution_type : DistributionType
         Type of this distribution.
-    _parametrization : Parametrization
+    parametrization : Parametrization
         Parameter values for this distribution.
-    _support : Support or None
+    support : Support or None
         Support of this distribution.
+    sampling_strategy : SamplingStrategy
+        Strategy for generating random samples. Such an object is unique for each distribution.
+    computation_strategy : ComputationStrategy
+        Strategy for computing characteristics and conversions.
+        Such an object is unique for each distribution.
     """
 
-    family_name: str
-    _distribution_type: DistributionType
-    _parametrization: Parametrization
-    _support: Support | None
+    def __init__(
+        self,
+        family_name: str,
+        distribution_type: DistributionType,
+        parametrization: Parametrization,
+        support: Support | None,
+        sampling_strategy: SamplingStrategy | None = None,
+        computation_strategy: ComputationStrategy[Any, Any] | None = None,
+    ):
+        self._distribution_type = distribution_type
+        self._family_name = family_name
+        self._parametrization = parametrization
+        self._support = support
+
+        self._computation_strategy = computation_strategy or DefaultComputationStrategy()
+        self._sampling_strategy = sampling_strategy or DefaultSamplingUnivariateStrategy()
+
+        self._analytical_cache_key: tuple[int, GenericCharacteristicName] | None = None
+        self._analytical_cache_val: (
+            Mapping[GenericCharacteristicName, AnalyticalComputation[Any, Any]] | None
+        ) = None
+
+    @property
+    def family_name(self) -> str:
+        "Get the name of the family this distribution belongs to."
+        return self._family_name
 
     @property
     def distribution_type(self) -> DistributionType:
@@ -142,25 +172,110 @@ def analytical_computations(
         parametrization object or name changes.
         """
         key = (id(self.parametrization), self.parametrization_name)
-        cache_key = getattr(self, "_analytical_cache_key", None)
-        cache_val = getattr(self, "_analytical_cache_val", None)
 
-        if cache_key != key or cache_val is None:
-            cache_val = self.family._build_analytical_computations(self.parametrization)
+        if self._analytical_cache_key != key or self._analytical_cache_val is None:
+            self._analytical_cache_val = self.family.build_analytical_computations(
+                self.parametrization
+            )
             self._analytical_cache_key = key
-            self._analytical_cache_val = cache_val
 
-        return cache_val
+        return self._analytical_cache_val
 
     @property
     def sampling_strategy(self) -> SamplingStrategy:
         """Get the sampling strategy for this distribution."""
-        return self.family.sampling_strategy
+        return self._sampling_strategy
 
     @property
     def computation_strategy(self) -> ComputationStrategy[Any, Any]:
         """Get the computation strategy for this distribution."""
-        return self.family.computation_strategy
+        return self._computation_strategy
+
+    def with_sampling_strategy(
+        self, sampling_strategy: SamplingStrategy | None
+    ) -> ParametricFamilyDistribution:
+        """
+        Return a copy of this distribution with an updated sampling strategy.
+
+        Parameters
+        ----------
+        sampling_strategy : SamplingStrategy | None
+            New sampling strategy. If ``None``, the default sampling strategy is used.
+
+        Returns
+        -------
+        ParametricFamilyDistribution
+            New distribution instance with the same parameters and updated strategy.
+        """
+        return ParametricFamilyDistribution(
+            family_name=self._family_name,
+            distribution_type=self._distribution_type,
+            parametrization=self._parametrization,
+            support=self._support,
+            sampling_strategy=sampling_strategy,
+            computation_strategy=self._computation_strategy,
+        )
+
+    def with_computation_strategy(
+        self, computation_strategy: ComputationStrategy[Any, Any] | None
+    ) -> ParametricFamilyDistribution:
+        """
+        Return a copy of this distribution with an updated computation strategy.
+
+        Parameters
+        ----------
+        computation_strategy : ComputationStrategy[Any, Any] | None
+            New computation strategy. If ``None``, the default computation strategy is used.
+
+        Returns
+        -------
+        ParametricFamilyDistribution
+            New distribution instance with the same parameters and updated strategy.
+        """
+        return ParametricFamilyDistribution(
+            family_name=self._family_name,
+            distribution_type=self._distribution_type,
+            parametrization=self._parametrization,
+            support=self._support,
+            sampling_strategy=self._sampling_strategy,
+            computation_strategy=computation_strategy,
+        )
+
+    def with_strategies(
+        self,
+        *,
+        sampling_strategy: SamplingStrategy | None = None,
+        computation_strategy: ComputationStrategy[Any, Any] | None = None,
+    ) -> ParametricFamilyDistribution:
+        """
+        Return a copy of this distribution with updated strategies.
+
+        Parameters
+        ----------
+        sampling_strategy : SamplingStrategy | None | object, optional
+            New sampling strategy. If not provided, the current strategy is preserved.
+            If explicitly set to ``None``, the default sampling strategy is used.
+        computation_strategy : ComputationStrategy[Any, Any] | None | object, optional
+            New computation strategy. If not provided, the current strategy is preserved.
+            If explicitly set to ``None``, the default computation strategy is used.
+
+        Returns
+        -------
+        ParametricFamilyDistribution
+            New distribution instance with the same parameters and updated strategies.
+        """
+        new_sampling = self._sampling_strategy if sampling_strategy is _KEEP else sampling_strategy
+        new_computation = (
+            self._computation_strategy if computation_strategy is _KEEP else computation_strategy
+        )
+        return ParametricFamilyDistribution(
+            family_name=self._family_name,
+            distribution_type=self._distribution_type,
+            parametrization=self._parametrization,
+            support=self._support,
+            sampling_strategy=new_sampling,
+            computation_strategy=new_computation,
+        )
 
     @property
     def support(self) -> Support | None: