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  • arongergely · 1 ✖

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  • Aggregating a dimension using the Quantiles method with `skipna=True` is very slow · 1 ✖

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  • CONTRIBUTOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1359023892 https://github.com/pydata/xarray/issues/7377#issuecomment-1359023892 https://api.github.com/repos/pydata/xarray/issues/7377 IC_kwDOAMm_X85RAQ8U arongergely 7316393 2022-12-20T08:53:34Z 2022-12-20T08:57:52Z CONTRIBUTOR

Hi, this is a known issue coming from numpy.nanquantile / numpy.nanpercentile. I had the same problem - AFAIK the workaround is to implement your own nanpercentiles calculation.

If you want to take that route:

There is a blog post about the issue + a numpy workaround for 3D arrays: https://krstn.eu/np.nanpercentile()-there-has-to-be-a-faster-way/

I also turned to the numpy mailing list. Abel Aoun had a suggestion to look into the algo used at the xclim project. See our thread here: https://mail.python.org/archives/list/numpy-discussion@python.org/message/EKQIS4KNOHS6ZAU5OSYTLNOOH7U2Y5TW/

I ended up taking that one and rewrote it to suit my needs. I achieved >100x speedup in my case Good luck!

 
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   Aggregating a dimension using the Quantiles method with `skipna=True` is very slow 1497031605

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