Internal gufunc names accepted as estimator with backend="numba"
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Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 76/100
Research direction
Start by locating the estimator validation used by the Numba backend and compare it with the array path, which already rejects these internal names. Check the validation for es_ensemble, vs_ensemble, gksuv_ensemble, and gksmv_ensemble; done means each listed internal name raises the usual ValueError with backend="numba" instead of reaching a gufunc and raising TypeError.
Written by the indexing model from the issue text.
Description
With backend="numba", the estimator check accepts the keys used internally for the outcome- and vertically re-scaled gufuncs, which then fail with a confusing TypeError instead of the usual ValueError.
obs, fct = np.random.randn(2, 3), np.random.randn(2, 5, 3)
sr.es_ensemble(obs, fct, estimator="ownrg", backend="numba")
# TypeError: Too few arguments for function '_owenergy_score_gufunc'
The same happens for vrnrg in es_ensemble, ownrg in vs_ensemble, and ow/vr in gksuv_ensemble and gksmv_ensemble. The array path rejects them correctly.
- Dominant language
- Python
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- 15
- Avg merge
- 1h 42m
- Merged PRs (30d)
- 9
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