validation and handling of cond ids specified in array files

Author: BSnelling

petab/v2/converters.py

@@ -249,6 +249,12 @@ def _convert_experiment(self, experiment: Experiment) -> None:
             #  single-period experiments.
             if i_period == 0:
                 exp_ind_id = self.get_experiment_indicator(experiment.id)
+                # If condition ids are set by array data, skip as importers handle this
+                if set(period.condition_ids).issubset(
+                    self._new_problem._get_array_data_condition_ids()
+                ):
+                    continue
+
                 for change in self._new_problem.get_changes_for_period(period):
                     period0_assignments.setdefault(
                         change.target_id, []

petab/v2/core.py

@@ -2288,6 +2288,14 @@ def add_experiment(self, id_: str, *args):
             Experiment(id=id_, periods=periods)
         )
 
+    def _get_array_data_condition_ids(self) -> set[str]:
+        """Get the set of condition IDs that are referenced in the array data files."""
+        condition_ids = set()
+        for array_data in self.array_data_files:
+            for input in array_data.inputs.values():
+                condition_ids.update(input.keys())
+        return condition_ids
+
     def __iadd__(self, other):
         """Add Observable, Parameter, Measurement, Condition, or Experiment"""
         from .core import (

petab/v2/lint.py

@@ -532,6 +532,13 @@ class CheckExperimentConditionsExist(ValidationTask):
     def run(self, problem: Problem) -> ValidationIssue | None:
         messages = []
         available_conditions = {c.id for c in problem.conditions}
+        if problem.array_data_files:
+            available_conditions |= {
+                key
+                for array_data in problem.array_data_files
+                for input_array in array_data.inputs.values()
+                for key in input_array.keys()
+            }
         for experiment in problem.experiments:
             missing_conditions = (
                 set(
@@ -972,6 +979,14 @@ def run(self, problem: Problem) -> ValidationIssue | None:
         return None
 
 
+class CheckExperimentalConditionsDefined(ValidationTask):
+    """A task to check that all conditions referenced by the experiments
+    are defined."""
+
+    def run(self, problem: Problem) -> ValidationIssue | None:
+        return None
+
+
 def get_valid_parameters_for_parameter_table(
     problem: Problem,
 ) -> set[str]:
@@ -1189,4 +1204,5 @@ def get_placeholders(
 #: Validation tasks that should be run PEtab SciML problems
 sciml_validation_tasks = default_validation_tasks + [
     CheckHybridizationTable(),
+    CheckExperimentalConditionsDefined(),
 ]

tests/v2/test_sciml.py

@@ -48,9 +48,9 @@ def _get_test_problem():
       -> B; gamma_;
     end
     """)
-    problem.add_experiment("e1", 0, "")
+    problem.add_experiment("e1", 0, "cond1")
     problem.add_mapping("net1_input1", "net1.inputs[0][0]")
-    problem.add_mapping("net1_input2", "net1.inputs[0][1]")
+    problem.add_mapping("net1_input2", "net1.inputs[1]")
     problem.add_mapping("net1_output1", "net1.outputs[0][0]")
     problem.add_mapping("net1_ps", "net1.parameters")
     problem.add_measurement("B_obs", time=1, measurement=1, experiment_id="e1")
@@ -62,7 +62,7 @@ def _get_test_problem():
         "net1_ps", estimate=True, lb=-np.inf, ub=np.inf, nominal_value="array"
     )
     problem.extensions.sciml.add_hybridization("net1_input1", "A")
-    problem.extensions.sciml.add_hybridization("net1_input2", "B")
+    problem.extensions.sciml.add_hybridization("net1_input2", "array")
     problem.extensions.sciml.add_hybridization("gamma_", "net1_output1")
     problem.extensions.sciml.add_neural_network_from_dict(
         "net1",
@@ -106,7 +106,11 @@ def _get_test_problem():
     problem.extensions.sciml.add_array_data_from_dict(
         {
             "metadata": {"pytorch_format": True},
-            "inputs": {},
+            "inputs": {
+                "net1_input2": {
+                    "cond1": np.random.randn(2),
+                }
+            },
             "parameters": {
                 "net1": {
                     "layer1": {