Type checking - #301
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KriSun95
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Aug 27, 2026
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Adding types to be explicit is a great idea. I'd imagine this is something we'll continue to edit and adopt as we keep building too.
| data_y: NDArray[np.float64], | ||
| model_x: NDArray[np.float64], | ||
| model_func: Any, | ||
| statistic_func: Callable[[NDArray[np.float64], NDArray[np.float64]], float], |
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How does this work if the Callable can have keyword arguments other varying inputs?
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| p: Any = p.default, | ||
| break_energy: Any = u.Quantity(break_energy.default, break_energy.unit), # pyright: ignore[reportArgumentType] | ||
| q: Any = q.default, | ||
| low_e_cutoff: Any = u.Quantity(low_e_cutoff.default, low_e_cutoff.unit), # pyright: ignore[reportArgumentType] | ||
| high_e_cutoff: Any = u.Quantity(high_e_cutoff.default, high_e_cutoff.unit), # pyright: ignore[reportArgumentType] | ||
| total_eflux: Any = u.Quantity(total_eflux.default, total_eflux.unit), # pyright: ignore[reportArgumentType] | ||
| integrator: Any = None, | ||
| **kwargs: Any, | ||
| ) -> None: |
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I think all of these in __init__ should be Astropy quantities even if dimensionless.
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PR Description
If we're want to this it would be good to agree and merge sooner rather than later as touches nearly every file.
If we don't want the types inline could move them to stubs files
AI Assistance Disclosure
Help figure out some of the types and specific inline ignores and configuration
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