html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/644#issuecomment-1150280375,https://api.github.com/repos/pydata/xarray/issues/644,1150280375,IC_kwDOAMm_X85Ej-K3,1217238,2022-06-08T18:56:17Z,2022-06-08T18:56:17Z,MEMBER,"This might fit more naturally into interp() as a new method like ""nearest-valid"" rather than in sel().
The difference is that sel() only looks at indexes (and not the data) to select out a single value, whereas interp() can combine adjacent values in arbitrary ways.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,114773593
https://github.com/pydata/xarray/issues/644#issuecomment-721440664,https://api.github.com/repos/pydata/xarray/issues/644,721440664,MDEyOklzc3VlQ29tbWVudDcyMTQ0MDY2NA==,1217238,2020-11-04T00:10:41Z,2020-11-04T00:10:41Z,MEMBER,"There hasn't been any progress on this to my knowledge, unfortunately","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,114773593
https://github.com/pydata/xarray/issues/644#issuecomment-155611625,https://api.github.com/repos/pydata/xarray/issues/644,155611625,MDEyOklzc3VlQ29tbWVudDE1NTYxMTYyNQ==,1217238,2015-11-11T00:27:10Z,2015-11-11T00:27:10Z,MEMBER,"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)
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,114773593