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Careless actually runs and produces (pathological) output when there are SIGI values of 0 in the input. There should be a way to deal with this by either
(3) I'm guessing you meant np.abs(I) / max_isigi? I think this might be worth adding a flag for allowing that in cases of known low-intensity data, but I would personally prefer (2) with a warning label in the logs.
Careless actually runs and produces (pathological) output when there are SIGI values of 0 in the input. There should be a way to deal with this by either
SIGI = maximum(SIGI, np.abs(I) / max_isigi)
I have a slight preference for (3), because i think in general we should discount reported I/SIGI values that are greater than about 100 or so.
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