..

Author: dweindl

python/sdist/amici/petab/petab_importer.py

@@ -706,6 +706,10 @@ def __init__(
         self._fixed_pid_to_idx: dict[str, int] = {
             id_: i for i, id_ in enumerate(self._fixed_parameter_ids)
         }
+        # maps PEtab observable IDs to petab Observable instances
+        self._petab_id_to_obs: dict[str, v2.Observable] = {
+            obs.id: obs for obs in self._petab_problem.observables
+        }
 
         # create a new model instance from the model module from which
         #  we can get the default parameters
@@ -926,8 +930,7 @@ def apply_parameters(
 
         Update the parameter-dependent values of the given `ExpData` instance
         according to the provided problem parameters (i.e., values of the
-        parameters in the PEtab
-        :external+petab:ref:`parameter table <v2_parameter_table>`).
+        parameters in the PEtab parameter table).
 
         This assumes that:
 
@@ -941,10 +944,11 @@ def apply_parameters(
             In case of errors, the state of `edata` is undefined.
         :param problem_parameters: Problem parameters to be applied.
         """
+        # FIXME: xref
+        #  :external+petab:label:`parameter table <v2_parameter_table>`).
         # TODO: support ndarray in addition to dict?
         # TODO: use the original or the current parameters
         #   if only a subset is provided?
-        # TODO: must handle output overrides here, or add them to the events
 
         # get the original parameter values
         #  (model parameters set during model creation)
@@ -984,24 +988,43 @@ def apply_parameters(
                     fixed_par_vals[p_idx] = p_val
             edata.fixed_parameters_pre_equilibration = fixed_par_vals
 
-        # apply problem parameter values to identical model parameters
-        #  any other parameter mapping is handled by events
+        # Apply problem parameter values to identical model parameters.
+        #  Any other parameter mapping, except for output parameter
+        #  placeholders, is handled by events.
         for k, v in problem_parameters.items():
             if (idx := pid_to_idx.get(k)) is not None:
                 par_vals[idx] = v
 
+        # Handle measurement-specific mappings to placeholders
+        # TODO: must handle output overrides here, or add them to the events
         # TODO handle placeholders
         #  check that all periods use the same overrides (except for numeric sigmas)
         #  see do_import() for details
-        # TODO extract function
         measurements = self._petab_problem.get_measurements_for_experiment(
             experiment
         )
-        # encountered placeholders and their overrides
+
+        def apply_override(placeholder: str, override: sp.Basic):
+            """Apply a single placeholder override."""
+            if (idx := pid_to_idx.get(placeholder)) is not None:
+                if override.is_Number:
+                    par_vals[idx] = float(override)
+                elif override.is_Symbol:
+                    par_vals[idx] = problem_parameters[str(override)]
+                else:
+                    raise AssertionError(
+                        f"Unexpected override type: {override} for {placeholder} in experiment {experiment_id}"
+                    )
+            else:
+                raise NotImplementedError(
+                    f"Cannot handle override `{placeholder}' => '{override}'"
+                )
+
+        # tracks encountered placeholders and their overrides
         # (across all observables -- placeholders IDs are globally unique)
         overrides = {}
         for m in measurements:
-            obs: Observable = self._petab_problem[m.observable_id]
+            obs = self._petab_id_to_obs[m.observable_id]
             if obs.observable_placeholders:
                 for placeholder, override in zip(
                     obs.observable_placeholders,
@@ -1016,21 +1039,7 @@ def apply_parameters(
                             "Timepoint-specific observable placeholder "
                             "overrides are not supported"
                         )
-
-                    if (idx := pid_to_idx.get(placeholder)) is not None:
-                        if override.is_Number:
-                            par_vals[idx] = float(override)
-                        elif override.is_Symbol:
-                            par_vals[idx] = problem_parameters[str(override)]
-                        else:
-                            raise AssertionError(
-                                f"Unexpected override type: {override} for {placeholder} in experiment {experiment_id}"
-                            )
-                    else:
-                        raise NotImplementedError(
-                            f"Cannot handle override `{placeholder}' => '{override}'"
-                        )
-
+                    apply_override(placeholder, override)
             # TODO: set sigmas via parameters or .sigmay
             if obs.noise_placeholders:
                 for placeholder, override in zip(
@@ -1045,22 +1054,13 @@ def apply_parameters(
                             "Timepoint-specific observable placeholder "
                             "overrides are not supported"
                         )
-                    if (idx := pid_to_idx.get(placeholder)) is not None:
-                        if override.is_Number:
-                            par_vals[idx] = float(override)
-                        else:
-                            par_vals[idx] = problem_parameters[str(override)]
-                    else:
-                        raise NotImplementedError(
-                            f"Cannot handle override `{placeholder}' => '{override}'"
-                        )
-            # print("ExperimentManager.apply_parameters:")
-            # print(m)
-            # print(dict(zip(self._parameter_ids, map(float, par_vals))))
+                    apply_override(placeholder, override)
+
         # TODO: set all unused placeholders to NaN to make it easier to spot problems?
         edata.parameters = par_vals
 
         # TODO debug, remove
+        # print("ExperimentManager.apply_parameters:")
         # print(
         #     f"Parameters: {dict(zip(self._parameter_ids, map(float, par_vals)))}"
         # )