Fix: importance_sampling=None produces error #427
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… "none" or None - Moved importance sampling logic from `multipath_pathfinder` to `fit_pathfinder` to fix error method is "none" or None - Update docstrings to clarify importance sampling method behavior - Use match statement for method selection in importance_sampling
- Test different importance sampling approaches (psis, psir, identity, None)
fonnesbeck
approved these changes
Feb 18, 2025
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| if importance_sampling is not None: | ||
| importance_sampling = importance_sampling.lower() | ||
| importance_sampling = None if importance_sampling == "none" else importance_sampling |
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I thought you had globally removed the use of "none"?
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Good point. I thought about allowing a string for None as "none" to keep it consistent with the other importance_sampling options (i.e., "psis", "psir", "identity"). Come to think of it, None would be consistent with Python APIs in general with mixed argument types (str | None, int | None, etc).
I'll send another commit to remove the use of "none".
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Is this good to merge? |
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Yes I believe so. @fonnesbeck ? |
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I just went ahead and merged this. Thanks @aphc14 ! |
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Thanks @zaxtax ! |
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Fix handling of
importance_sampling="none"orNoneoptionChanges
"none"andNoneconsistentlyAdded/Modified Tests
(num_paths, num_draws_per_path, N)(whereNare the number of model parameters)(num_draws, N)np.testing.assert_allclosetolerance as increasingjitterbrings parameter estimates closer to the reference value