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  • dcherian · 1 ✖

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  • Optimize ndrolling nanreduce · 1 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1507213204 https://github.com/pydata/xarray/issues/4325#issuecomment-1507213204 https://api.github.com/repos/pydata/xarray/issues/4325 IC_kwDOAMm_X85Z1j-U dcherian 2448579 2023-04-13T15:56:51Z 2023-04-13T15:56:51Z MEMBER

Over in https://github.com/pydata/xarray/issues/7344#issuecomment-1336299057 @shoyer

That said -- we could also switch to smarter NumPy based algorithms to implement most moving window calculations, e.g,. using np.nancumsum for moving window means.

After some digging, this would involve using "summed area tables" which have been generalized to nD, and can be used to compute all our built-in reductions (except median). Basically we'd store the summed area table (repeated np.cumsum) and then calculate reductions using binary ops (mostly subtraction) on those tables.

This would be an intermediate level project but we could implement it incrementally (start with sum for example). One downside is the potential for floating point inaccuracies because we're taking differences of potentially large numbers.

cc @aulemahal 

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   Optimize ndrolling nanreduce 675482176

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