issue_comments: 155698426

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https://github.com/pydata/xarray/issues/644#issuecomment-155698426 https://api.github.com/repos/pydata/xarray/issues/644 155698426 MDEyOklzc3VlQ29tbWVudDE1NTY5ODQyNg== 13906519 2015-11-11T08:02:56Z 2015-11-11T08:02:56Z NONE

Ah, ok, cool.

Thanks for the pointers and getting back to me. Looking forward to any future xray improvements. It’s really becoming my goto to for netcdf stuff (in addition to cdo).

Christian

On 11 Nov 2015, at 01:27, Stephan Hoyer notifications@github.com wrote:

This is tricky to put into .sel because that method currently works by only looking at coordinate labels, not at data values.

One way to fix this would be to unravel your two dimensions corresponding to latitude and longitude into a single "lat_lon" dimension. At this point, you could apply a sea mask, to produce a compressed lat_lon coordinate corresponding to only unmasked points. Now, it's relatively straightforward to imagine doing nearest neighbor lookups on this set of labels.

This later solution will require a few steps (all of which are on the "to do" list, but without any immediate timelines): 1. support for multi-level indexes in xray 2. support for "unraveling" multiple dimensions into 1-dimension 3. support for looking up nearest locations in multiple dimensions via some sort of spatial index (e.g., a KD tree)

— Reply to this email directly or view it on GitHub https://github.com/xray/xray/issues/644#issuecomment-155611625.

 
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