Hotfix: overflow error in correct LSB#4610
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chrishalcrow merged 1 commit intoJun 10, 2026
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| # cast to int64 to avoid integer overflow in np.diff when consecutive | ||
| # unique values are farther apart than the dtype range (e.g. int16) | ||
| unique_values = np.unique(data[:, ch]).astype(np.int64) |
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Never thought about this gross bug before - nice!
chrishalcrow
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Works on my local data, and looks sensible.
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I found this bug in some sessions...when the LSB estimation overlflows, everything gets messed up.
This PR takes care of overflow errors and it also uses a mode approach to estimate LSB from channels, since LSB is set at the acquisition level. This approach is more robust against rounding errors.