Tidy up of options ready in using JHC suggestions

Author: atb1995

gusto/solvers/preconditioners.py

@@ -479,14 +479,9 @@ def initialize(self, pc):
 
         self._process_context(pc)
         prefix = pc.getOptionsPrefix()
-        opts = PETSc.Options()
 
         # Unpack sub-solver parameters from the options prefix
-        self.theta_solver_parameters = self._get_sub_params(opts, prefix + "theta_backsub")
-        self.exner_avg_solver_parameters = self._get_sub_params(opts, prefix + "exner_ave")
-        self.rho_avg_solver_parameters = self._get_sub_params(opts, prefix + "rho_ave")
-        self.riesz_map_parameters = self._get_sub_params(opts, prefix + "riesz_map")
-        self.scpc_solve_parameters = self._get_sub_params(opts, prefix + "scpc_solve")
+        self.riesz_map_parameters = PETSc.Options(prefix + "riesz_map_").getAll()
 
         if logger.isEnabledFor(DEBUG):
             self.scpc_solve_parameters['ksp_monitor_true_residual'] = None
@@ -612,12 +607,12 @@ def L_tr(f):
                                                  constant_jacobian=True)
 
         self.rho_avg_solver = LinearVariationalSolver(
-            rho_avg_prb, solver_parameters=self.rho_avg_solver_parameters,
-            options_prefix=pc.getOptionsPrefix()+'rhobar_avg_solver'
+            rho_avg_prb,
+            options_prefix=pc.getOptionsPrefix()+'rhobar_avg'
         )
         self.exner_avg_solver = LinearVariationalSolver(
-            exner_avg_prb, solver_parameters=self.exner_avg_solver_parameters,
-            options_prefix=pc.getOptionsPrefix()+'exnerbar_avg_solver'
+            exner_avg_prb,
+            options_prefix=pc.getOptionsPrefix()+'exnerbar_avg'
         )
 
         # "broken" u, rho, and trace system
@@ -671,8 +666,9 @@ def L_tr(f):
             aeqn, Leqn, self.y_hybrid, constant_jacobian=True
         )
         self.hybridized_solver = LinearVariationalSolver(
-            hybridized_prb, solver_parameters=self.scpc_solve_parameters,
-            options_prefix=pc.getOptionsPrefix()+self._prefix, appctx=appctx
+            hybridized_prb,
+            options_prefix=pc.getOptionsPrefix()+self._prefix,
+            appctx=appctx
         )
 
         if logger.isEnabledFor(DEBUG):
@@ -705,8 +701,8 @@ def L_tr(f):
         )
 
         self.theta_solver = LinearVariationalSolver(
-            theta_problem, solver_parameters=self.theta_solver_parameters,
-            options_prefix=pc.getOptionsPrefix()+'thetabacksubstitution'
+            theta_problem,
+            options_prefix=pc.getOptionsPrefix()+'theta_backsub'
         )
 
         if logger.isEnabledFor(DEBUG):
@@ -793,13 +789,3 @@ def applyTranspose(self, pc, x, y):
         """
 
         raise NotImplementedError("The transpose application of the PC is not implemented.")
-
-    def _get_sub_params(self, opts, prefix):
-        result = {}
-        for key, val in opts.getAll().items():
-            if key.startswith(prefix):
-                stripped = key[len(prefix):]
-                # Remove leading underscore
-                stripped = stripped.lstrip('_')
-                result[stripped] = val if val != "" else None
-        return result

gusto/solvers/solver_presets.py

@@ -78,15 +78,15 @@ def trace_nullsp(T):
             'ksp_atol': a_tol,
         }
 
-        exner_ave_settings = {
+        exnerbar_avg_settings = {
             'ksp_type': 'cg',
             'pc_type': 'bjacobi',
             'sub_pc_type': 'ilu',
             'ksp_rtol': r_tol,
             'ksp_atol': a_tol,
         }
 
-        rho_ave_settings = {
+        rhobar_avg_settings = {
             'ksp_type': 'cg',
             'pc_type': 'bjacobi',
             'sub_pc_type': 'ilu',
@@ -132,10 +132,10 @@ def trace_nullsp(T):
             'pc_type': 'python',
             'pc_python_type': 'gusto.CompressibleHybridisedSCPC',
             'theta_backsub': theta_backsub_settings,
-            'exner_ave': exner_ave_settings,
-            'rho_ave': rho_ave_settings,
+            'exnerbar_avg': exnerbar_avg_settings,
+            'rhobar_avg': rhobar_avg_settings,
             'riesz_map': riesz_map_settings,
-            'scpc_solve': scpc_solve_settings,
+            'compressible_hybrid_scpc': scpc_solve_settings,
         }
 
         # We pass the implicit weighting parameter (alpha) and tau_values to the