Multiplicative additive sobo objectives (#481)

* added MultiplicativeAdditive data model

* added actual multiplicative model (callable is missing)

* added torch functions

* added test for objective

* added test for sobo stategy: multiplicative_additive

* changed additive/multiplicative calculations:
- Removed scaling by x**(1/(....)) to avoid numerical errors, if x<0
- included weight transformation for multiplicative objectives from (0, 1] to [1, inf) scale to avoid numerical errors at weights != 1.0
- added tests for weights != 1.0

* added notebook for comparison of merging objectives

* after hooks

* addet .idea/ folder (pycharm) to gitignore

* after hooks

* Apply pre-commit fixes

* Delete .idea directory

* corrected tests for multiplicative_additive_botorch_objective

* after pre-commit

* lint specifications

* corrected weightings calc in test for multiplicative objective

* after hooks

* changed docstrings to google docstring format

* easy fixes, spelling errors

* forgot linting

* easy fixes, spelling errors

* removed denominator additive from multiplicative_additive_sobo strategy

* after hooks

* fixed typing

* tensor initialization of objectives

* after hooks

* avoiding torch size error

* avoid linting error

* after hooks

* reverting test-renaming

* revert isinstance list comprehension to tuple.... solution

* testing copilot suggestions for linting errors

* reverting wrong copilot suggestions

* added test for _callables_and_weights

* after hooks

* added test for SOBO strategy data model

* added test for SOBO strategy data model

* added new sobo strategy to a mysterious list

* after hooks

* still trying to get rid of the linting error, expecting tuple(types)

* WIP

* WIP

* WIP

* WIP

* WIP

* minor corrections

.gitignore

@@ -118,6 +118,9 @@ venv.bak/
 .vscode/
 .devcontainer
 
+# pycharm project settings
+.idea/
+
 # Rope project settings
 .ropeproject
 

bofire/data_models/strategies/actual_strategy_type.py

@@ -19,6 +19,7 @@
 from bofire.data_models.strategies.predictives.sobo import (
     AdditiveSoboStrategy,
     CustomSoboStrategy,
+    MultiplicativeAdditiveSoboStrategy,
     MultiplicativeSoboStrategy,
     SoboStrategy,
 )
@@ -32,6 +33,7 @@
     AdditiveSoboStrategy,
     ActiveLearningStrategy,
     MultiplicativeSoboStrategy,
+    MultiplicativeAdditiveSoboStrategy,
     CustomSoboStrategy,
     MultiFidelityStrategy,
     QehviStrategy,

bofire/data_models/strategies/api.py

@@ -26,6 +26,7 @@
 from bofire.data_models.strategies.predictives.sobo import (
     AdditiveSoboStrategy,
     CustomSoboStrategy,
+    MultiplicativeAdditiveSoboStrategy,
     MultiplicativeSoboStrategy,
     SoboStrategy,
 )
@@ -61,6 +62,7 @@
     ActiveLearningStrategy,
     AdditiveSoboStrategy,
     MultiplicativeSoboStrategy,
+    MultiplicativeAdditiveSoboStrategy,
     CustomSoboStrategy,
     QehviStrategy,
     QnehviStrategy,

bofire/data_models/strategies/predictives/sobo.py

@@ -1,6 +1,7 @@
-from typing import Literal, Optional, Type
+from typing import List, Literal, Optional, Type
 
-from pydantic import Field, field_validator
+import pydantic
+from pydantic import Field, field_validator, model_validator
 
 from bofire.data_models.acquisition_functions.api import (
     AnySingleObjectiveAcquisitionFunction,
@@ -74,7 +75,25 @@ def validate_is_multiobjective(cls, v, info):
         return v
 
 
-class MultiplicativeSoboStrategy(SoboBaseStrategy):
+class _CheckAdaptableWeightsMixin:
+    """
+    Contains an additional validator for weights in multiplicative objective merging.
+
+    Additional validation of weights for adaptable weights, in multiplicative calculations. Adaption to (1, inf)
+    requires w>=1e-8
+    """
+
+    @model_validator(mode="after")
+    def check_adaptable_weights(cls, self):
+        for obj in self.domain.outputs.get_by_objective():
+            if obj.objective.w < 1e-8:
+                raise pydantic.ValidationError(
+                    f"Weight transformation to (1, inf) requires w>=1e-8 . Violated by feature {obj.key}."
+                )
+        return self
+
+
+class MultiplicativeSoboStrategy(SoboBaseStrategy, _CheckAdaptableWeightsMixin):
     type: Literal["MultiplicativeSoboStrategy"] = "MultiplicativeSoboStrategy"
 
     @field_validator("domain")
@@ -86,6 +105,36 @@ def validate_is_multiobjective(cls, v, info):
         return v
 
 
+class MultiplicativeAdditiveSoboStrategy(SoboBaseStrategy, _CheckAdaptableWeightsMixin):
+    """
+    Mixed, weighted multiplicative (primary, strict) and additive (secondary, non-strict) objectives.
+
+    The formular for a mixed objective with two multiplicative features (f1, and f2 with weights w1 and w2) and two
+    additive features (f3 and f4 with weights w3 and w4) is:
+
+        additive_objective = 1 + f3*w3 + f4*w4
+
+        objective = f1^w1 * f2^w2 * additive_objective
+
+    """
+
+    type: Literal["MultiplicativeAdditiveSoboStrategy"] = (
+        "MultiplicativeAdditiveSoboStrategy"
+    )
+    use_output_constraints: bool = True
+    additive_features: List[str] = Field(default_factory=list)
+
+    @field_validator("additive_features")
+    def validate_additive_features(cls, v, values):
+        domain = values.data["domain"]
+        for feature in v:
+            if feature not in domain.outputs.get_keys():
+                raise ValueError(
+                    f"Feature {feature} is not an output feature of the domain."
+                )
+        return v
+
+
 class CustomSoboStrategy(SoboBaseStrategy):
     type: Literal["CustomSoboStrategy"] = "CustomSoboStrategy"
     use_output_constraints: bool = True

bofire/strategies/mapper_actual.py

@@ -14,6 +14,7 @@
 from bofire.strategies.predictives.sobo import (
     AdditiveSoboStrategy,
     CustomSoboStrategy,
+    MultiplicativeAdditiveSoboStrategy,
     MultiplicativeSoboStrategy,
     SoboStrategy,
 )
@@ -29,6 +30,7 @@
     data_models.SoboStrategy: SoboStrategy,
     data_models.AdditiveSoboStrategy: AdditiveSoboStrategy,
     data_models.MultiplicativeSoboStrategy: MultiplicativeSoboStrategy,
+    data_models.MultiplicativeAdditiveSoboStrategy: MultiplicativeAdditiveSoboStrategy,
     data_models.CustomSoboStrategy: CustomSoboStrategy,
     data_models.MultiFidelityStrategy: MultiFidelityStrategy,
     data_models.QehviStrategy: QehviStrategy,

bofire/strategies/predictives/sobo.py

@@ -20,6 +20,9 @@
 from bofire.data_models.objectives.api import ConstrainedObjective, Objective
 from bofire.data_models.strategies.api import AdditiveSoboStrategy as AdditiveDataModel
 from bofire.data_models.strategies.api import CustomSoboStrategy as CustomDataModel
+from bofire.data_models.strategies.api import (
+    MultiplicativeAdditiveSoboStrategy as MultiplicativeAdditiveDataModel,
+)
 from bofire.data_models.strategies.api import (
     MultiplicativeSoboStrategy as MultiplicativeDataModel,
 )
@@ -28,6 +31,7 @@
 from bofire.utils.torch_tools import (
     get_additive_botorch_objective,
     get_custom_botorch_objective,
+    get_multiplicative_additive_objective,
     get_multiplicative_botorch_objective,
     get_objective_callable,
     get_output_constraints,
@@ -240,13 +244,46 @@ def _get_objective_and_constraints(
                 objective=get_multiplicative_botorch_objective(  # type: ignore
                     outputs=self.domain.outputs,
                     experiments=self.experiments,
+                    adapt_weights_to_1_inf=True,
                 ),
             ),
             None,
             1e-3,
         )
 
 
+class MultiplicativeAdditiveSoboStrategy(SoboStrategy):
+    def __init__(
+        self,
+        data_model: MultiplicativeAdditiveDataModel,
+        **kwargs,
+    ):
+        self.additive_features = data_model.additive_features
+        super().__init__(data_model=data_model, **kwargs)
+
+    def _get_objective_and_constraints(
+        self,
+    ) -> Tuple[
+        GenericMCObjective,
+        Union[List[Callable[[torch.Tensor], torch.Tensor]], None],
+        Union[List, float],
+    ]:
+        # we absorb all constraints into the objective
+        assert self.experiments is not None, "No experiments available."
+        return (
+            GenericMCObjective(
+                objective=get_multiplicative_additive_objective(  # type: ignore
+                    outputs=self.domain.outputs,
+                    experiments=self.experiments,
+                    additive_features=self.additive_features,
+                    adapt_weights_to_1_inf=True,
+                )
+            ),
+            None,
+            1e-3,
+        )
+
+
 class CustomSoboStrategy(SoboStrategy):
     def __init__(
         self,