🚧 Attempt at feed through

bluemira/equilibria/optimisation/problem/_breakdown.py

@@ -223,7 +223,15 @@ def __init__(
         max_currents = np.atleast_1d(max_currents)
         self.bounds = (-max_currents / self.scale, max_currents / self.scale)
 
-    def optimise(self, x0=None, *, fixed_coils=True):
+    def optimise(
+        self,
+        x0=None,
+        *,
+        fixed_coils: bool = True,
+        keep_history: bool = False,
+        check_constraints: bool = False,
+        verbose: bool = False,
+    ):
         """
         Solve the optimisation problem.
         """
@@ -246,6 +254,9 @@ def optimise(self, x0=None, *, fixed_coils=True):
             bounds=self.bounds,
             eq_constraints=eq_constraints,
             ineq_constraints=ineq_constraints,
+            keep_history=keep_history,
+            check_constraints=check_constraints,
+            check_constraints_warn=verbose,
         )
 
         opt_currents = opt_result.x

bluemira/equilibria/optimisation/problem/_nested_position.py

@@ -194,6 +194,8 @@ def __init__(
         initial_currents=None,
         *,
         debug: bool = False,
+        keep_history: bool = True,
+        check_constraints: bool = True,
     ):
         self.coilset = coilset
         self.position_mapper = position_mapper
@@ -214,6 +216,9 @@ def __init__(
         opt_dimension = self.position_mapper.dimension
         self.bounds = (np.zeros(opt_dimension), np.ones(opt_dimension))
 
+        self.keep_history = keep_history
+        self.check_constraints = check_constraints
+
     @staticmethod
     def _run_reporting(itern, max_fom, verbose):
         """
@@ -248,7 +253,10 @@ def _run_diagnostics(
             debug[entry].append([lcfs, value])
 
     def sub_opt_objective(
-        self, vector: npt.NDArray[np.float64], *, verbose: bool = False
+        self,
+        vector: npt.NDArray[np.float64],
+        *,
+        verbose: bool = False,
     ) -> float:
         """Run the sub-optimisations and return the largest figure of merit."""
         pos_map = self.position_mapper.to_xz_dict(vector)
@@ -262,7 +270,12 @@ def sub_opt_objective(
         for sub_opt_prob in self.sub_opt_problems:
             sub_opt_prob.coilset.set_optimisation_state(coil_position_map=pos_map)
 
-            result = sub_opt_prob.optimise(x0=self.initial_currents, fixed_coils=False)
+            result = sub_opt_prob.optimise(
+                x0=self.initial_currents,
+                fixed_coils=False,
+                keep_history=self.keep_history,
+                check_constraints=self.check_constraints,
+            )
 
             self._run_diagnostics(self.debug, sub_opt_prob, result)
             fom_values.append(result.f_x)
@@ -275,7 +288,10 @@ def objective(
         self, vector: npt.NDArray[np.float64], *, verbose: bool = False
     ) -> float:
         """The objective function of the parent optimisation."""
-        return self.sub_opt_objective(vector, verbose=verbose)
+        return self.sub_opt_objective(
+            vector,
+            verbose=verbose,
+        )
 
     def _get_initial_vector(self) -> npt.NDArray[np.float64]:
         """
@@ -287,7 +303,12 @@ def _get_initial_vector(self) -> npt.NDArray[np.float64]:
         return self.position_mapper.to_L(cs_opt_state.xs, cs_opt_state.zs)
 
     def optimise(
-        self, x0: npt.NDArray | None = None, *, verbose: bool = False
+        self,
+        x0: npt.NDArray | None = None,
+        *,
+        verbose: bool = False,
+        keep_history: bool = False,
+        check_constraints: bool = False,
     ) -> CoilsetOptimiserResult:
         """
         Run the PulsedNestedPositionCOP
@@ -304,6 +325,8 @@ def optimise(
         coilset:
             Optimised CoilSet
         """
+        keep_history = keep_history or self.keep_history
+        check_constraints = check_constraints or self.check_constraints
         if x0 is None:
             x0 = self._get_initial_vector()
 
@@ -318,12 +341,15 @@ def optimise(
             bounds=self.bounds,
             eq_constraints=eq_constraints,
             ineq_constraints=ineq_constraints,
+            keep_history=keep_history,
+            check_constraints=check_constraints,
+            check_constraints_warn=verbose,
         )
 
         optimal_positions = opt_result.x
         # Call the objective one last time, makes sure the coilset state
         # is set to the optimum
-        self.sub_opt_objective(optimal_positions)
+        self.sub_opt_objective(optimal_positions, verbose=verbose)
 
         # Clean up state of Equilibrium objects
         for sub_opt in self.sub_opt_problems:

bluemira/equilibria/optimisation/problem/_tikhonov.py

@@ -86,7 +86,15 @@ def __init__(
         )
         self._constraints = [] if constraints is None else constraints
 
-    def optimise(self, x0=None, *, fixed_coils=True) -> CoilsetOptimiserResult:
+    def optimise(
+        self,
+        x0=None,
+        *,
+        fixed_coils=True,
+        keep_history: bool = False,
+        check_constraints: bool = False,
+        verbose: bool = False,
+    ) -> CoilsetOptimiserResult:
         """
         Solve the optimisation problem
 
@@ -129,6 +137,9 @@ def optimise(self, x0=None, *, fixed_coils=True) -> CoilsetOptimiserResult:
             opt_parameters=self.opt_parameters,
             eq_constraints=eq_constraints,
             ineq_constraints=ineq_constraints,
+            keep_history=keep_history,
+            check_constraints=check_constraints,
+            check_constraints_warn=verbose,
         )
 
         opt_currents = opt_result.x

bluemira/equilibria/run.py

@@ -282,7 +282,9 @@ def _get_psi_premag(self):
         bluemira_warn("Premagnetisation not calculated")
         return np.inf
 
-    def run_premagnetisation(self):
+    def run_premagnetisation(
+        self, *, keep_history: bool = False, check_constraints: bool = False
+    ):
         """Run the breakdown optimisation problem.
 
         Raises
@@ -323,7 +325,11 @@ def run_premagnetisation(self):
                 opt_conditions=self.bd_settings.opt_conditions,
                 constraints=constraints,
             )
-            result = problem.optimise(fixed_coils=False)
+            result = problem.optimise(
+                fixed_coils=False,
+                keep_history=keep_history,
+                check_constraints=check_constraints,
+            )
             breakdown.set_breakdown_point(*strategy.breakdown_point)
             psi_premag = breakdown.breakdown_psi
 
@@ -383,6 +389,8 @@ def run_reference_equilibrium(self):
             relaxation=self.eq_settings.relaxation,
             fixed_coils=True,
             plot=False,
+            keep_history=True,
+            check_constraints=True,
         )
         program()
 
@@ -631,7 +639,13 @@ def _prepare_coilset(self, coilset: CoilSet) -> CoilSet:
         )
         return coilset
 
-    def optimise(self, *, verbose: bool = False) -> CoilSet:
+    def optimise(
+        self,
+        *,
+        verbose: bool = False,
+        keep_history: bool = False,
+        check_constraints: bool = False,
+    ) -> CoilSet:
         """
         Optimise the coil positions for the start and end of the current flat-top.
         """
@@ -649,7 +663,11 @@ def optimise(self, *, verbose: bool = False) -> CoilSet:
             self.pos_settings.opt_conditions,
             constraints=None,
         )
-        result = pos_opt_problem.optimise(verbose=verbose)
+        result = pos_opt_problem.optimise(
+            verbose=verbose,
+            keep_history=keep_history,
+            check_constraints=check_constraints,
+        )
         optimised_coilset = self._consolidate_coilset(result.coilset, sub_opt_problems)
 
         self.converge_and_snapshot(sub_opt_problems)

bluemira/equilibria/solve.py

@@ -468,6 +468,8 @@ def __init__(
         gif: bool = False,
         figure_folder: str | None = None,
         plot_name: str = "default_0",
+        keep_history: bool = False,
+        check_constraints: bool = False,
     ):
         self.eq = eq
         self.coilset = self.eq.coilset
@@ -482,7 +484,8 @@ def __init__(
                 " ConvergenceCriterion."
             )
         self.fixed_coils = fixed_coils
-
+        self.keep_history = keep_history
+        self.check_constraints = check_constraints
         self.relaxation = relaxation
         self.maxiter = maxiter
         self.plot_flag = plot or (gif and not plot)
@@ -501,7 +504,11 @@ def __init__(
     def _optimise_coilset(self):
         self.result = None
         try:
-            self.result = self.opt_prob.optimise(fixed_coils=self.fixed_coils)
+            self.result = self.opt_prob.optimise(
+                fixed_coils=self.fixed_coils,
+                keep_history=self.keep_history,
+                check_constraints=self.check_constraints,
+            )
             self.coilset = self.result.coilset
         except OptimisationError:
             self.coilset = self.store[-1]