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  • jbbutler · 2 ✖

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  • How should xarray use/support sparse arrays? · 2 ✖

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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
1544952425 https://github.com/pydata/xarray/issues/3213#issuecomment-1544952425 https://api.github.com/repos/pydata/xarray/issues/3213 IC_kwDOAMm_X85cFhpp jbbutler 41593244 2023-05-12T01:01:21Z 2023-05-12T01:01:21Z NONE

Thank you all so much for the feedback and resources! I agree (1) testing the limits of xArray's API compatibility with sparse and (2) developing some documentation for what is/isn't supported are great places to start, so I'll get on that while I think about the other I/O issues (serialization, etc.)

 
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   How should xarray use/support sparse arrays? 479942077
1533842816 https://github.com/pydata/xarray/issues/3213#issuecomment-1533842816 https://api.github.com/repos/pydata/xarray/issues/3213 IC_kwDOAMm_X85bbJWA jbbutler 41593244 2023-05-03T22:40:32Z 2023-05-03T22:40:32Z NONE

Hi all! As part of a research project, I'm looking to contribute to xArray's sparse capabilities, with an emphasis on sparse support for use-cases in the geosciences. I'm wondering if anyone in the geosciences (or adjacent disciplines!) has encountered problems with xArray's current level of sparse support, and what kinds of improvements they'd like to see to address those issues. From playing around, it seems the current strategy of backing DataArrays with COO sparse arrays takes care of a lot of use cases, but I have the following ideas that may (or may not) be useful to implement further:

  • Functions/methods to convert from geopandas GeoDataframes of vector data to rasterized, potentially sparse ndarrays in an xArray Dataset/DataArray (reverse direction too); this is related to the issue of converting from sparse arrays back to multi-indexed pandas objects at the top of this issue (which I believe has yet to be solved)
  • Loading sparse data from a netcdf() file directly into a Dataset/Array backed by sparse ndarray(s) (seems like the only way to get sparse backings is to either unstack or call '.from_dataframe()/series()' with the sparse flag set to True?)
  • Support for other sparse array conventions (for ex, GCXS in the sparse package for better memory efficiency; I can't find any improvements to make on the current COO backing in terms of supported arithmetic operations, merges/joins, etc.)

I'd appreciate any feedback on these ideas, as well as any other things that would be nice to have implemented!

 
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   How should xarray use/support sparse arrays? 479942077

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