..

python/parpe/hdf5_pe_input.py

@@ -355,13 +355,18 @@ def _generate_simulation_to_optimization_parameter_mapping(self) -> None:
 
             logger.debug(cond_par_map)
 
+            def _get_par(mapped_parameter: str, mapping, default=None):
+                """Resolve parameter mapping."""
+                mapped_parameter = mapping.get(mapped_parameter, default)
+                while ((maps_to := mapping.get(mapped_parameter, mapped_parameter)) != mapped_parameter
+                       and isinstance(maps_to, str)):
+                    mapped_parameter = maps_to
+                return mapped_parameter
+
             # update mapping matrix
             for model_parameter_idx, model_parameter_id \
                     in enumerate(variable_par_ids):
-                mapped_parameter = cond_par_map.map_sim_var[model_parameter_id]
-                while ((maps_to := cond_par_map.map_sim_var.get(mapped_parameter, mapped_parameter)) != mapped_parameter
-                       and isinstance(maps_to, str)):
-                    mapped_parameter = maps_to
+                mapped_parameter = _get_par(model_parameter_id, cond_par_map.map_sim_var)
                 try:
                     (mapped_idx, override) = self.get_index_mapping_for_par(
                         mapped_parameter, optimization_parameter_name_to_index)
@@ -383,8 +388,10 @@ def _generate_simulation_to_optimization_parameter_mapping(self) -> None:
                 for amici_id in variable_par_ids)
 
             fixed_parameter_matrix[:, self.condition_map[condition_idx, 1]] = \
-                np.array([cond_par_map.map_sim_fix[par_id]
-                          for par_id in fixed_par_ids])
+                np.array([
+                    _get_par(par_id, cond_par_map.map_sim_fix)
+                    for par_id in fixed_par_ids
+                ])
 
             if cond_par_map.map_preeq_fix:
                 fixed_parameter_matrix[:,
@@ -394,7 +401,7 @@ def _generate_simulation_to_optimization_parameter_mapping(self) -> None:
                     # in this case. only NaN is problematic, because it will
                     # propagate through multiplication with the indicator
                     # variable.
-                    np.array([cond_par_map.map_preeq_fix.get(par_id, 0.0)
+                    np.array([_get_par(par_id, cond_par_map.map_preeq_fix, 0.0)
                               for par_id in fixed_par_ids])
                 )