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  • .sel(...., method='nearest') fails for large requests. · 8 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
740320785 https://github.com/pydata/xarray/issues/4630#issuecomment-740320785 https://api.github.com/repos/pydata/xarray/issues/4630 MDEyOklzc3VlQ29tbWVudDc0MDMyMDc4NQ== EricKeenan 44210245 2020-12-08T02:32:42Z 2020-12-08T02:32:42Z CONTRIBUTOR

Thanks for sharing! I'll give this a first shot before the end of the year. 

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   .sel(...., method='nearest') fails for large requests.  753874419
736892959 https://github.com/pydata/xarray/issues/4630#issuecomment-736892959 https://api.github.com/repos/pydata/xarray/issues/4630 MDEyOklzc3VlQ29tbWVudDczNjg5Mjk1OQ== keewis 14808389 2020-12-01T23:46:18Z 2020-12-01T23:46:18Z MEMBER

sure. #4621 added examples for interp / interpolate_na. For the narrative documentation I don't have a example PR but I think it's fine to just extend the Vectorized indexing section (thoughts, @dcherian?).

 
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   .sel(...., method='nearest') fails for large requests.  753874419
736869263 https://github.com/pydata/xarray/issues/4630#issuecomment-736869263 https://api.github.com/repos/pydata/xarray/issues/4630 MDEyOklzc3VlQ29tbWVudDczNjg2OTI2Mw== EricKeenan 44210245 2020-12-01T22:48:34Z 2020-12-01T22:48:34Z CONTRIBUTOR

I'd be happy to give this a shot. But I'm not sure where to start... Can you point me to an example PR that has done something similar? 

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   .sel(...., method='nearest') fails for large requests.  753874419
736853065 https://github.com/pydata/xarray/issues/4630#issuecomment-736853065 https://api.github.com/repos/pydata/xarray/issues/4630 MDEyOklzc3VlQ29tbWVudDczNjg1MzA2NQ== keewis 14808389 2020-12-01T22:12:37Z 2020-12-01T22:12:37Z MEMBER

this trick is not mentioned in the narrative documentation (or rather: I can't find it), and the docstrings of isel and sel don't contain any examples at all.

Since I believe it should be documented somewhere I'm reopening this to make sure we don't forget. Also, we would definitely welcome a PR adding this, if you're up for it.

 
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   .sel(...., method='nearest') fails for large requests.  753874419
736758627 https://github.com/pydata/xarray/issues/4630#issuecomment-736758627 https://api.github.com/repos/pydata/xarray/issues/4630 MDEyOklzc3VlQ29tbWVudDczNjc1ODYyNw== EricKeenan 44210245 2020-12-01T19:09:52Z 2020-12-01T19:09:52Z CONTRIBUTOR

👏 👍 I didn't realize I needed to do that. Thanks for letting me know. Problem solved - marking this as closed. 

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   .sel(...., method='nearest') fails for large requests.  753874419
736755070 https://github.com/pydata/xarray/issues/4630#issuecomment-736755070 https://api.github.com/repos/pydata/xarray/issues/4630 MDEyOklzc3VlQ29tbWVudDczNjc1NTA3MA== dcherian 2448579 2020-12-01T19:03:12Z 2020-12-01T19:03:12Z MEMBER

TO use "vectorized indexing", tgt_lat and tgt_lon need to be DataArrays with a common dimension name that is not a dimenion in ds

``` python import xarray as xr import numpy as np

ds = xr.tutorial.open_dataset("air_temperature")

Define taget latitude and longitude

tgt_lat = xr.DataArray(np.linspace(0, 100, num=10), dims="points") # <--- tgt_lon = xr.DataArray(np.linspace(0, 100, num=10), dims="points") # <---

Retrieve data at target latitude and longitude

tgt_data = ds['air'].sel(lon=tgt_lon, lat=tgt_lat, method='nearest') tgt_data ```

 
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   .sel(...., method='nearest') fails for large requests.  753874419
736752768 https://github.com/pydata/xarray/issues/4630#issuecomment-736752768 https://api.github.com/repos/pydata/xarray/issues/4630 MDEyOklzc3VlQ29tbWVudDczNjc1Mjc2OA== EricKeenan 44210245 2020-12-01T18:59:18Z 2020-12-01T18:59:18Z CONTRIBUTOR

@dcherian Thanks for pointing me in the right direction. I'm trying to implement this with vectorized indexing, but it seems that my queries need to exactly match the xarray object lat/lon, which is why I tried method='nearest'. Am I missing something? 

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   .sel(...., method='nearest') fails for large requests.  753874419
736117204 https://github.com/pydata/xarray/issues/4630#issuecomment-736117204 https://api.github.com/repos/pydata/xarray/issues/4630 MDEyOklzc3VlQ29tbWVudDczNjExNzIwNA== dcherian 2448579 2020-11-30T23:28:58Z 2020-11-30T23:28:58Z MEMBER

You should be able to do this with "vectorized indexing": https://xarray.pydata.org/en/stable/indexing.html#vectorized-indexing

 
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   .sel(...., method='nearest') fails for large requests.  753874419

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