Add missing inversion of best_f in minimization mode

emdgroup · Jan 21, 2025 · fdeb2da · fdeb2da
1 parent 79a94eb
commit fdeb2da
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -45,6 +45,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   between constraints and dropped parameters yielding empty parameter sets
 - Minimizing a single `NumericalTarget` with specified bounds/transformation via
   `SingleTargetObjective` no longer erroneously maximizes it
+- Improvement-based Monte Carlo acquisition functions now use the correct
+  reference value in minimization mode
 
 ### Removed
 - `botorch_function_wrapper` utility for creating lookup callables

diff --git a/baybe/acquisition/base.py b/baybe/acquisition/base.py
@@ -115,6 +115,7 @@ def to_botorch(
                 if issubclass(acqf_cls, bo_acqf.AnalyticAcquisitionFunction):
                     additional_params["maximize"] = False
                 elif issubclass(acqf_cls, bo_acqf.MCAcquisitionFunction):
+                    additional_params["best_f"] *= -1.0
                     additional_params["objective"] = LinearMCObjective(
                         torch.tensor([-1.0])
                     )