add warning for fixed parameters with prior in petab

pypesto/objective/priors.py

@@ -1,7 +1,7 @@
 import logging
 import math
 from collections.abc import Sequence
-from typing import Callable, Optional, Union
+from typing import Callable, Union
 
 import numpy as np
 
@@ -51,7 +51,7 @@ class NegLogParameterPriors(ObjectiveBase):
     def __init__(
         self,
         prior_list: list[dict],
-        x_names: Optional[Sequence[str]] = None,
+        x_names: Sequence[str] = None,
     ):
         """
         Initialize.

pypesto/objective/roadrunner/petab_importer_roadrunner.py

@@ -6,6 +6,7 @@
 """
 from __future__ import annotations
 
+import logging
 import numbers
 import re
 from collections.abc import Iterable
@@ -32,6 +33,8 @@
 from .roadrunner_calculator import RoadRunnerCalculator
 from .utils import ExpData
 
+logger = logging.getLogger(__name__)
+
 
 class PetabImporterRR:
     """
@@ -279,6 +282,13 @@ def create_prior(self) -> NegLogParameterPriors | None:
                 isinstance(prior_type_entry, str)
                 and prior_type_entry != petab.PARAMETER_SCALE_UNIFORM
             ):
+                # check if parameter for which prior is defined is a fixed parameter
+                if x_id in self.petab_problem.x_fixed_ids:
+                    logger.warning(
+                        f"Parameter {x_id} is marked as fixed but has a "
+                        f"prior defined. This might be unintended."
+                    )
+
                 prior_params = [
                     float(param)
                     for param in self.petab_problem.parameter_df.loc[

pypesto/petab/importer.py

@@ -667,6 +667,13 @@ def create_prior(self) -> NegLogParameterPriors | None:
                     isinstance(prior_type_entry, str)
                     and prior_type_entry != petab.PARAMETER_SCALE_UNIFORM
                 ):
+                    # check if parameter for which prior is defined is a fixed parameter
+                    if x_id in self.petab_problem.x_fixed_ids:
+                        logger.warning(
+                            f"Parameter {x_id} is marked as fixed but has a "
+                            f"prior defined. This might be unintended."
+                        )
+
                     prior_params = [
                         float(param)
                         for param in self.petab_problem.parameter_df.loc[