Avoid use of is_mc due to yet unclear semantics

#467
emdgroup · Jan 23, 2025 · 1505cd6 · 1505cd6
1 parent 23445ab
commit 1505cd6
Showing 1 changed file with 2 additions and 2 deletions.
diff --git a/baybe/acquisition/base.py b/baybe/acquisition/base.py
@@ -111,15 +111,15 @@ def to_botorch(
                     additional_params["best_f"] = (
                         bo_surrogate.posterior(train_x).mean.min().item()
                     )
-                    if self.is_mc:
+                    if issubclass(acqf_cls, bo_acqf.MCAcquisitionFunction):
                         additional_params["best_f"] *= -1.0
 
                 if issubclass(acqf_cls, bo_acqf.AnalyticAcquisitionFunction):
                     additional_params["maximize"] = False
                 elif issubclass(acqf_cls, bo_acqf.qNegIntegratedPosteriorVariance):
                     # qNIPV is valid but does not require any adjusted params
                     pass
-                elif self.is_mc:
+                elif issubclass(acqf_cls, bo_acqf.MCAcquisitionFunction):
                     additional_params["objective"] = LinearMCObjective(
                         torch.tensor([-1.0])
                     )