Skipping time windows in outlier test

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I have a large dataset of 1second time-series data in a timetable. In the dataset I also have a binary flag for when there is a filter in place for backgrounding the measurement. I would like to detect outliers for the signal measurement to remove erroneous points before doing any calculations on the data. Is there a simple way to incorporate the filter flag using isoutlier() so that I can ignore those points without the moving median incorporating the last sample time?
The data set has ~10 million points which makes me want to avoid looping through.
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Poison Idea fan
Poison Idea fan 2023-11-1
So, what I found was that I was not re-synchronizing the outlier flag output from the isoutlier function with the initial flag I used for sample points rather than background points. Mistake by me.
Thanks for your response.

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