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v2: linter doesn't check that placeholder IDs are unique

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Évaluation

Difficulté
3/5
Temps estimé
1-2 jours
Accessibilité débutants
48/100
Type d'issue
Fonctionnalité
Clarté
Plutôt claire
Activité
Active
Stack technique
python
Domaine
data

Piste de recherche

Start from Problem.validate() in the petab.v2 Problem class and the reproducer in the issue, which adds two observables sharing the placeholder a. Add a check that collects placeholder IDs from both placeholder columns across all observables and reports duplicates, plus IDs that collide with model species, observable, parameter, condition or experiment IDs. Done when the reproducer reports an issue and the existing validation tests still pass.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Description

The PEtab v2 spec requires the IDs in observablePlaceholders and noisePlaceholders to be "valid PEtab identifiers that have not been introduced elsewhere", and all identifiers to be globally unique within the problem. This was discussed in PEtab-dev/PEtab#594 (starting at https://github.com/PEtab-dev/PEtab/issues/594#issuecomment-2850839215) and specified in PEtab-dev/PEtab#625.

Problem.validate() doesn't check this. Tested on main (5fb4066), adding observables and measurements to an otherwise valid problem (Boehm_JProteomeRes2014 from Benchmark-Models-PEtab):

Case Result
Same placeholder a in observablePlaceholders of two observables no issues
a as observable placeholder of one observable and noise placeholder of another no issues
Placeholder ID = model species ID (STAT5A) no issues
Placeholder ID = observable ID no issues
Placeholder ID = parameter table ID (ratio) reported, but only indirectly: "Extraneous parameter(s) in parameter table" / "is not allowed to occur in the parameters table"

Reproducer for the first case:

from petab.v2 import Problem

p = Problem.from_yaml("Boehm_JProteomeRes2014/v2/problem.yaml")
p.add_observable("o1", "a * STAT5A", noise_formula="1", observable_placeholders=["a"])
p.add_observable("o2", "a + STAT5A", noise_formula="1", observable_placeholders=["a"])
p.add_measurement("o1", time=1, measurement=1, observable_parameters=[2])
p.add_measurement("o2", time=1, measurement=1, observable_parameters=[3])
print(p.validate())  # no issues

I'd suggest a validation task that collects all placeholder IDs, from both columns and all observables, and reports:

  • duplicates among placeholders, including the same ID within one observable's observable and noise placeholders;
  • placeholders that coincide with any other ID in the problem: model entities, parameter/observable/condition/experiment IDs, mapping table petabEntityIds, and so on.

The parameter table case could then get a clearer message than "Extraneous parameter(s)".

Drafted with AI assistance. 🤖

Langage dominant
Python
Étoiles
18
Forks
9
Merge moyen
1 j 21 h
PR mergées (30 j)
25

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