Outlier detection and outlier exclusion - adjusted#10
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oof I also just see I messed up |
From: #5 (comment) Need to think through it again/and or check some more samples and test it against that. Getting different bounds/outliers right now although I think they're right.
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MUCH better. |
* Remove the limiting of bounds with min/max * consult and get some more samples * include R samples as some authorative examples
There could be an argument made that if we have few outliers, reversing the lists twice could be faster than passing through the entire list once with 2 conditions. We can probably optimize & benchmark on this later.
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argh coveralls why... it reports as failing but getting rid of that I'd need to allow list all the CI ones and that is just too much of a drag. |
Since we changed the rules for outlier bounds we don't need them any more. Helps simplify the code quite a bit.
Also cracked down on some of the too flexbile code surrounding `get_percentile` - there were layers of get lazies here because the API we promised is almost too forgiving. Hence, made it easier - if the percentiles we need are there take them, if not calculate them without some layers to it that I also found too hard to follow now :)
I think that's a dangerous assumption and our code should be resilient to it :)
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Alrighty, that was some more work than I anticipated but I included a whole swath of cleanup all over the place. Should probably be ready to merge 👀 🚀 Thanks again @NickNeck for all the work on it and sorry it took me so long to get it. Should be able to release it soon :) |
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Follow up on #5 / me trying to finish it up :)
Gotta run right now for other responsibilities, likely to continue tomorrow!
Thanks @NickNeck 💚
edit: I also know tests are currently failing that's why that commit is "WIP"