From fca00f084e87271d1fafaa9d93221ba1cf0a5531 Mon Sep 17 00:00:00 2001 From: Thomas Morris Date: Sat, 28 Oct 2023 14:46:11 -0400 Subject: [PATCH] access table by device name and not dof name --- bloptools/bayesian/agent.py | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/bloptools/bayesian/agent.py b/bloptools/bayesian/agent.py index 9b29deb..ca1fb89 100644 --- a/bloptools/bayesian/agent.py +++ b/bloptools/bayesian/agent.py @@ -117,7 +117,7 @@ def tell(self, new_table=None, append=True, train=True, **kwargs): if self.initialized: cached_hypers = self.hypers - inputs = self.table.loc[:, self.dofs.subset(active=True).names].values.astype(float) + inputs = self.table.loc[:, self.dofs.subset(active=True).device_names].values.astype(float) for i, obj in enumerate(self.objectives): self.table.loc[:, f"{obj.key}_fitness"] = targets = self._get_objective_targets(i) @@ -297,7 +297,7 @@ def acquire(self, acquisition_inputs): if not self.allow_acquisition_errors: raise error logging.warning(f"Error in acquisition/digestion: {repr(error)}") - products = pd.DataFrame(acquisition_inputs, columns=self.dofs.subset(active=True, read_only=False).names) + products = pd.DataFrame(acquisition_inputs, columns=self.dofs.subset(active=True, read_only=False).device_names) for obj in self.objectives: products.loc[:, obj.key] = np.nan @@ -615,14 +615,16 @@ def active_inputs(self): @property def acquisition_inputs(self): - return self.table.loc[:, self.dofs.subset(active=True, read_only=False).names].astype(float) + return self.table.loc[:, self.dofs.subset(active=True, read_only=False).device_names].astype(float) @property def best_inputs(self): """ Returns a value for each currently active and non-read-only degree of freedom """ - return self.table.loc[np.nanargmax(self.scalarized_objectives), self.dofs.subset(active=True, read_only=False).names] + return self.table.loc[ + np.nanargmax(self.scalarized_objectives), self.dofs.subset(active=True, read_only=False).device_names + ] def go_to(self, positions): args = []