Fix merge

pybop/costs/design_costs.py

@@ -26,37 +26,6 @@ def __init__(self, problem):
         """
         super().__init__(problem)
         self.problem = problem
-        if update_capacity is True:
-            nominal_capacity_warning = (
-                "The nominal capacity is approximated for each iteration."
-            )
-        else:
-            nominal_capacity_warning = (
-                "The nominal capacity is fixed at the initial model value."
-            )
-        warnings.warn(nominal_capacity_warning, UserWarning, stacklevel=2)
-        self.update_capacity = update_capacity
-        self.parameter_set = problem.model.parameter_set
-        self.update_simulation_data(self.parameters.as_dict("initial"))
-
-    def update_simulation_data(self, inputs: Inputs):
-        """
-        Updates the simulation data based on the initial parameter values.
-
-        Parameters
-        ----------
-        inputs : Inputs
-            The initial parameter values for the simulation.
-        """
-        if self.update_capacity:
-            self.problem.model.approximate_capacity(inputs)
-        solution = self.problem.evaluate(inputs)
-
-        if "Time [s]" not in solution:
-            raise ValueError("The solution does not contain time data.")
-        self.problem.domain_data = solution["Time [s]"]
-        self.problem.target = {key: solution[key] for key in self.problem.signal}
-        self.dt = solution["Time [s]"][1] - solution["Time [s]"][0]
 
 
 class GravimetricEnergyDensity(DesignCost):

pybop/problems/base_problem.py

@@ -173,7 +173,7 @@ def set_target(self, dataset: Dataset):
         if not isinstance(dataset, Dataset):
             raise ValueError("Dataset must be a pybop Dataset object.")
 
-        self._time_data = dataset["Time [s]"]
+        self._domain_data = dataset[self.domain]
         self._target = {signal: dataset[signal] for signal in self.signal}
 
     @property