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  • Dask friendly check in `.weighted()` · 15 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
724119273 https://github.com/pydata/xarray/pull/4559#issuecomment-724119273 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyNDExOTI3Mw== mathause 10194086 2020-11-09T16:22:51Z 2020-11-09T16:22:51Z MEMBER

Thanks @jbusecke 

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   Dask friendly check in `.weighted()` 733789095
719975332 https://github.com/pydata/xarray/pull/4559#issuecomment-719975332 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcxOTk3NTMzMg== pep8speaks 24736507 2020-10-31T19:11:40Z 2020-11-09T15:24:49Z NONE

Hello @jbusecke! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

There are currently no PEP 8 issues detected in this Pull Request. Cheers! :beers:

Comment last updated at 2020-11-09 15:24:48 UTC
 
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   Dask friendly check in `.weighted()` 733789095
723170944 https://github.com/pydata/xarray/pull/4559#issuecomment-723170944 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMzE3MDk0NA== keewis 14808389 2020-11-06T16:25:46Z 2020-11-06T18:44:35Z MEMBER

this CI is sometimes flaky, but it's usually enough to just rerun it. I'll do that for you once the other CI finished.

 
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   Dask friendly check in `.weighted()` 733789095
723197430 https://github.com/pydata/xarray/pull/4559#issuecomment-723197430 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMzE5NzQzMA== jbusecke 14314623 2020-11-06T17:15:33Z 2020-11-06T17:15:33Z CONTRIBUTOR

Seems like all the other test are passing (minus the two upstream problems discussed before).

 
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   Dask friendly check in `.weighted()` 733789095
723168106 https://github.com/pydata/xarray/pull/4559#issuecomment-723168106 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMzE2ODEwNg== jbusecke 14314623 2020-11-06T16:20:04Z 2020-11-06T16:20:04Z CONTRIBUTOR

I am not understanding why that MinimumVersionPolicy test is failing (or what it does haha). Is this something upstream, or should I fix?

 
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   Dask friendly check in `.weighted()` 733789095
722513714 https://github.com/pydata/xarray/pull/4559#issuecomment-722513714 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMjUxMzcxNA== jbusecke 14314623 2020-11-05T17:12:06Z 2020-11-05T17:12:06Z CONTRIBUTOR

Ok I think this should be good to go. I have implemented all the requested changes. The remaining failures are related to other problems upstream (I think). Anything else I should add here?

 
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   Dask friendly check in `.weighted()` 733789095
721833586 https://github.com/pydata/xarray/pull/4559#issuecomment-721833586 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMTgzMzU4Ng== keewis 14808389 2020-11-04T16:26:05Z 2020-11-04T16:56:49Z MEMBER

the TestDask.test_save_mfdataset_compute_false_roundtrip failure should be #4539, and the failing upstream-dev CI shouldn't be related, either (my guess is that a dependency – most likely numpy – added a new warning). I'll investigate and open a new issue for that (edit: see #4565).

 
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   Dask friendly check in `.weighted()` 733789095
721831543 https://github.com/pydata/xarray/pull/4559#issuecomment-721831543 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMTgzMTU0Mw== jbusecke 14314623 2020-11-04T16:22:43Z 2020-11-04T16:22:43Z CONTRIBUTOR

Similarly on MacOSX py38 this fails: TestDask.test_save_mfdataset_compute_false_roundtrip

 
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   Dask friendly check in `.weighted()` 733789095
721830832 https://github.com/pydata/xarray/pull/4559#issuecomment-721830832 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMTgzMDgzMg== jbusecke 14314623 2020-11-04T16:21:35Z 2020-11-04T16:21:35Z CONTRIBUTOR

I am getting some failures for py38-upstream (TestDataset.test_polyfit_warnings) that seem unrelated?

 
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   Dask friendly check in `.weighted()` 733789095
721362748 https://github.com/pydata/xarray/pull/4559#issuecomment-721362748 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMTM2Mjc0OA== jbusecke 14314623 2020-11-03T20:39:31Z 2020-11-03T20:39:31Z CONTRIBUTOR

Do you think this works or are further changes needed? Many thanks for the guidance so far!

 
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   Dask friendly check in `.weighted()` 733789095
720166781 https://github.com/pydata/xarray/pull/4559#issuecomment-720166781 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMDE2Njc4MQ== jbusecke 14314623 2020-11-01T23:11:51Z 2020-11-01T23:11:51Z CONTRIBUTOR

I did have to fiddle with this a bit. I did change .isnull() to np.isnan() and replace the data of weights, otherwise the error would not be raised for the dask array at all. This does not look terribly elegant to me, but passes tests locally. Waiting for the CI to see if the others pass aswell. Happy to make further changes, and thanks for all the input already.

 
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   Dask friendly check in `.weighted()` 733789095
720164541 https://github.com/pydata/xarray/pull/4559#issuecomment-720164541 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMDE2NDU0MQ== mathause 10194086 2020-11-01T22:53:24Z 2020-11-01T22:53:24Z MEMBER

I think you need to do someting along the lines of:

python if dask_duck_array(weights): import dask.array as dsa dsa.map_blocks(_weight_check, weights.data, dtype=weights.dtype) else: _weight_check()

 
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   Dask friendly check in `.weighted()` 733789095
720090586 https://github.com/pydata/xarray/pull/4559#issuecomment-720090586 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMDA5MDU4Ng== keewis 14808389 2020-11-01T13:42:04Z 2020-11-01T13:42:04Z MEMBER

since the test you added requires dask it definitely should get a @requires_dask.

That won't fix all the failing tests, though: map_blocks is only valid if we operate on dask arrays. I guess you either have to apply the function directly on other arrays, or we have to make DataArray.map_blocks on non-dask arrays call to DataArray.map.

 
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   Dask friendly check in `.weighted()` 733789095
720022225 https://github.com/pydata/xarray/pull/4559#issuecomment-720022225 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMDAyMjIyNQ== max-sixty 5635139 2020-11-01T03:46:37Z 2020-11-01T03:46:37Z MEMBER

Yes, @requires_dask on the test

 
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   Dask friendly check in `.weighted()` 733789095
720020006 https://github.com/pydata/xarray/pull/4559#issuecomment-720020006 https://api.github.com/repos/pydata/xarray/issues/4559 MDEyOklzc3VlQ29tbWVudDcyMDAyMDAwNg== jbusecke 14314623 2020-11-01T03:16:06Z 2020-11-01T03:16:06Z CONTRIBUTOR

The Ci environments without dask are failing. Should I add some pytest skip logic, or what is the best way to handle this?

 
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   Dask friendly check in `.weighted()` 733789095

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