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  • djhoese · 1 ✖

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  • Does interp() work on curvilinear grids (2D coordinates) ? · 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
508078893 https://github.com/pydata/xarray/issues/2281#issuecomment-508078893 https://api.github.com/repos/pydata/xarray/issues/2281 MDEyOklzc3VlQ29tbWVudDUwODA3ODg5Mw== djhoese 1828519 2019-07-03T12:49:20Z 2019-07-03T12:49:20Z CONTRIBUTOR

@kmuehlbauer Thanks for the ping. I don't have time to read this whole thread, but based on your comment I have a few things I'd like to point out. First, the pykdtree package is a good alternative to the scipy kdtree implementation. It has been shown to be much faster and uses openmp for parallel processing. Second, the pyresample library is my main way of resampled geolocated data. We use it in Satpy for resampling, but right now we haven't finalized the interfaces so things are kind of spread between satpy and pyresample as far as easy xarray handling. Pyresample uses SwathDefinition and AreaDefinition objects to define the geolocation of the data. In Satpy the same KDTree is used for every in-memory gridding, but we also allow a cache_dir which will save the indexes for every (source, target) area pair used in the resampling.

I'm hoping to sit down and get some geoxarray stuff implemented during SciPy next week, but usually get distracted by all the talks so no promises. I'd like geoxarray to provide a low level interface for getting and converting CRS and geolocation information on xarray objects and leave resampling and other tasks to libraries like pyresample and rioxarray.

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  Does interp() work on curvilinear grids (2D coordinates) ?  340486433

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