issue_comments: 657206070

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https://github.com/pydata/xarray/issues/4213#issuecomment-657206070 https://api.github.com/repos/pydata/xarray/issues/4213 657206070 MDEyOklzc3VlQ29tbWVudDY1NzIwNjA3MA== 35968931 2020-07-12T10:56:36Z 2020-07-12T10:56:36Z MEMBER

Thanks. The problem is I don't really know where the common coordinates are. However, since I know the extent of each tile, with some preprocessing I should be able to find/trim them.

Great. Let me know if you still have problems (on here, SO - I just answered your original question there, or on the xarray mailing list).

What really happened was I had a large area, then I used xarray to clip it into smaller tiles to make calculations more feasible.

I wonder if you could have avoided having to do this by applying your analysis in chunks using dask? That might be complicated if your analysis is a complicated algorithm though.

It would be great if mosaicing dataset with common coordinate was added to the xarray (like mosacing rasters). ... having it as part of xarray definitely helps many geospatial applications where, for many reasons, we deal with tiles of data with common coordinates.

This sounds like something that might be useful for lots of geoscientists, so it would be good to discuss this further. However, I don't really know exactly what you mean by "mosaicing rasters" (I don't work in geoscience). Briefly reading about it here it seems that there isn't one universal way to do it... What would be really great is if you could give me a more precise specification of the behaviour you're imagining, and how it would be used in practice (either here on in a new issue). Then we can see if it's (a) feasible, (b) commonly-useful, and (c) should live in xarray or another package. Another good place to ask about the best way to approach this problem in general would be the pangeo discourse.

 
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