Remove redundant is_equilibrated method

a3fe/run/_simulation_runner.py

@@ -697,30 +697,6 @@ def failed_simulations(self) -> _List[SimulationRunner]:
             for failure in sub_sim_runner.failed_simulations
         ]
 
-    def is_equilibrated(self, run_nos: _Optional[_List[int]] = None) -> bool:
-        f"""
-        Whether the {self.__class__.__name__} is equilibrated. This updates
-        the _equilibrated and _equil_time attributes of the lambda windows,
-        which are accessed by the equilibrated and equil_time properties.
-
-        Parameters
-        ----------
-        run_nos : List[int], Optional, default=None
-            A list of the run numbers to check for equilibration. If None, all runs are analysed.
-
-        Returns
-        -------
-        equilibrated : bool
-            Whether the {self.__class__.__name__} is equilibrated.
-        """
-        run_nos = self._get_valid_run_nos(run_nos)
-        return all(
-            [
-                sub_sim_runner.is_equilibrated(run_nos=run_nos)
-                for sub_sim_runner in self._sub_sim_runners
-            ]
-        )
-
     @property
     def equilibrated(self) -> float:
         f"""Whether the {self.__class__.__name__} is equilibrated."""
@@ -807,6 +783,8 @@ def recursively_set_attr(
                 attr=attr, value=value, force=force, silent=silent
             )
 
+    def set_
+
     def update_paths(self, old_sub_path: str, new_sub_path: str) -> None:
         """
         Replace the old sub-path with the new sub-path in the base, input, and output directory

a3fe/run/lambda_window.py

@@ -260,26 +260,6 @@ def get_tot_gpu_time(self, run_nos: _Optional[_List[int]] = None) -> float:
         run_nos = self._get_valid_run_nos(run_nos)
         return sum([self.sims[run_no - 1].get_tot_gpu_time() for run_no in run_nos])
 
-    def is_equilibrated(self, run_nos: _Optional[_List[int]] = None) -> bool:
-        """
-        Check if the ensemble of simulations at the lambda window is
-        equilibrated, based on the run numbers specified and the
-        equilibration detection method. Store the equilibration status
-        and time in private variables if so.
-
-        Parameters
-        ----------
-        run_nos : List[int], Optional, default: None
-            The run numbers to equilibration detection. If None, all runs will be used.
-
-        Returns
-        -------
-        equilibrated : bool
-            True if the simulation is equilibrated, False otherwise.
-        """
-        self._equilibrated, self._equil_time = self.check_equil(self, run_nos=run_nos)
-        return self._equilibrated
-
     @property
     def equilibrated(self) -> bool:
         """Whether equilibration has been achieved."""