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  • apply_ufunc(dask='parallelized') with multiple outputs · 12 ✖

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  • MEMBER · 12 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
628088800 https://github.com/pydata/xarray/issues/1815#issuecomment-628088800 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDYyODA4ODgwMA== dcherian 2448579 2020-05-13T16:04:20Z 2020-05-13T16:04:20Z MEMBER

So would you be re-doing the same computation by running .compute() separately on these objects?

Yes. but you can do dask.compute(xarray_obj1, xarray_obj2,...) or combine those objects appropriately into a Dataset and then call compute on that.

 
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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
628050521 https://github.com/pydata/xarray/issues/1815#issuecomment-628050521 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDYyODA1MDUyMQ== dcherian 2448579 2020-05-13T15:02:01Z 2020-05-13T15:02:01Z MEMBER

Still needs to be implemented. Stephan's comment suggests a path forward (https://github.com/pydata/xarray/issues/1815#issuecomment-440089606) 

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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
627869278 https://github.com/pydata/xarray/issues/1815#issuecomment-627869278 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDYyNzg2OTI3OA== kmuehlbauer 5821660 2020-05-13T09:33:59Z 2020-05-13T09:33:59Z MEMBER

I think ideally it would be nice to return multiple DataArrays or a Dataset of variables.

What's the current status of this? I've similar requirements, single DataArray as input, multiple DataArrays as output.

 
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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
614221197 https://github.com/pydata/xarray/issues/1815#issuecomment-614221197 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDYxNDIyMTE5Nw== andersy005 13301940 2020-04-15T18:59:23Z 2020-04-15T18:59:23Z MEMBER

I imagine you're far past this now. And this might have been related to discussions with Genevieve and I anyways.

Thank you for the update, @bradyrx! Yes, it was related to discussions with @gelsworth

 
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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
539134912 https://github.com/pydata/xarray/issues/1815#issuecomment-539134912 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDUzOTEzNDkxMg== rabernat 1197350 2019-10-07T18:06:03Z 2019-10-07T18:06:03Z MEMBER

I definitely don't have bandwidth! I'm happy to see you working on it.

On Mon, Oct 7, 2019 at 2:01 PM Anderson Banihirwe notifications@github.com wrote:

is what you are working on related to #3349 https://github.com/pydata/xarray/issues/3349?

@rabernat https://github.com/rabernat, indeed! Let me know if you have bandwidth to take on the polyfit implementation in xarray. Otherwise, I'd be happy to help out/work on it late October.

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/pydata/xarray/issues/1815?email_source=notifications&email_token=AAJEKJWGRLZODWGS57UF6I3QNN2RJA5CNFSM4ELBUQLKYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEARIK5I#issuecomment-539133301, or mute the thread https://github.com/notifications/unsubscribe-auth/AAJEKJQSAPJ3DAOTH24T7RTQNN2RJANCNFSM4ELBUQLA . 

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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
539133301 https://github.com/pydata/xarray/issues/1815#issuecomment-539133301 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDUzOTEzMzMwMQ== andersy005 13301940 2019-10-07T18:01:55Z 2019-10-07T18:01:55Z MEMBER

is what you are working on related to #3349?

@rabernat, indeed! Let me know if you have bandwidth to take on the polyfit implementation in xarray. Otherwise, I'd be happy to help out/work on it late October. 

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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
539025502 https://github.com/pydata/xarray/issues/1815#issuecomment-539025502 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDUzOTAyNTUwMg== rabernat 1197350 2019-10-07T14:00:01Z 2019-10-07T14:00:01Z MEMBER

@andersy005 - is what you are working on related to #3349? 

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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
536847249 https://github.com/pydata/xarray/issues/1815#issuecomment-536847249 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDUzNjg0NzI0OQ== andersy005 13301940 2019-10-01T03:39:15Z 2019-10-01T03:39:15Z MEMBER

Any updates or progress here? I’m trying to use xarray.apply_ufunc with scipy.stats.linregress which returns - slope - intercept - rvalue - pvalue - stderr

 
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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
440089606 https://github.com/pydata/xarray/issues/1815#issuecomment-440089606 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDQ0MDA4OTYwNg== shoyer 1217238 2018-11-20T00:16:31Z 2018-11-20T00:16:31Z MEMBER

I think we can do this inside the existing xarray.apply_ufunc, simply by using apply_gufunc instead of atop for the case where signature.num_outputs > 1 (which current raises NotImplementedError): https://github.com/pydata/xarray/blob/master/xarray/core/computation.py#L601

 
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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
440064660 https://github.com/pydata/xarray/issues/1815#issuecomment-440064660 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDQ0MDA2NDY2MA== mrocklin 306380 2018-11-19T22:27:31Z 2018-11-19T22:27:31Z MEMBER

FYI @magonser 

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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
440061760 https://github.com/pydata/xarray/issues/1815#issuecomment-440061760 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDQ0MDA2MTc2MA== jhamman 2443309 2018-11-19T22:17:00Z 2018-11-19T22:17:39Z MEMBER

@shoyer - dask now has a apply_gufunc. Is this something we should try to include in xr.apply_ufunct or a new function xr.apply_gufunc?

xref: https://github.com/dask/dask/pull/3109

 
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   apply_ufunc(dask='parallelized') with multiple outputs 287223508
356410108 https://github.com/pydata/xarray/issues/1815#issuecomment-356410108 https://api.github.com/repos/pydata/xarray/issues/1815 MDEyOklzc3VlQ29tbWVudDM1NjQxMDEwOA== shoyer 1217238 2018-01-09T20:51:18Z 2018-01-09T20:51:18Z MEMBER

We need atop to support multiple output arguments (https://github.com/dask/dask/issues/702), or potentially a specialized wrapper for generalized ufuncs in dask (https://github.com/dask/dask/issues/1176).

 
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   apply_ufunc(dask='parallelized') with multiple outputs 287223508

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