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  • max-sixty · 12 ✖

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  • rolling_exp (nee ewm) · 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
505059812 https://github.com/pydata/xarray/pull/2650#issuecomment-505059812 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDUwNTA1OTgxMg== max-sixty 5635139 2019-06-24T15:26:55Z 2019-06-24T15:26:55Z MEMBER

Thanks for all the help!

 
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   rolling_exp (nee ewm) 396084551
505056728 https://github.com/pydata/xarray/pull/2650#issuecomment-505056728 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDUwNTA1NjcyOA== max-sixty 5635139 2019-06-24T15:19:26Z 2019-06-24T15:19:26Z MEMBER

Updated! Let me know any final changes!

 
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   rolling_exp (nee ewm) 396084551
504490536 https://github.com/pydata/xarray/pull/2650#issuecomment-504490536 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDUwNDQ5MDUzNg== max-sixty 5635139 2019-06-21T16:37:31Z 2019-06-21T16:37:31Z MEMBER

Great - updated! Let me know any final comments!

 
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   rolling_exp (nee ewm) 396084551
502934591 https://github.com/pydata/xarray/pull/2650#issuecomment-502934591 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDUwMjkzNDU5MQ== max-sixty 5635139 2019-06-18T03:48:17Z 2019-06-18T03:48:17Z MEMBER

The gentlest of reminders that I think this is ready to merge (mea culpa for leaving it at 90% for so long)

 
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   rolling_exp (nee ewm) 396084551
500608059 https://github.com/pydata/xarray/pull/2650#issuecomment-500608059 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDUwMDYwODA1OQ== max-sixty 5635139 2019-06-10T21:49:13Z 2019-06-10T21:49:13Z MEMBER

This is updated! Could put an "Experimental" label on if we want (or maybe that's implicit).

Let me know any final changes. Will be good to get this merged at last.

 
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   rolling_exp (nee ewm) 396084551
457372793 https://github.com/pydata/xarray/pull/2650#issuecomment-457372793 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDQ1NzM3Mjc5Mw== max-sixty 5635139 2019-01-24T21:56:18Z 2019-01-24T21:56:18Z MEMBER

Any thoughts on the API?

@shoyer is making some updates to numbagg so as soon as those are complete, we could point the dependencies at that release and merge this

 
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   rolling_exp (nee ewm) 396084551
454213540 https://github.com/pydata/xarray/pull/2650#issuecomment-454213540 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDQ1NDIxMzU0MA== max-sixty 5635139 2019-01-15T00:15:28Z 2019-01-15T00:15:28Z MEMBER

I made an attempt to add the "skip variables without the dimension" to apply_ufunc, but it's much harder than I expected - there are more cases than I expected (e.g. multiple datasets).

I may be missing something - let me know if there's an reasonable approach

Otherwise I'll do the close thing for this PR, and potentially we can have a look at the general solution later

 
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   rolling_exp (nee ewm) 396084551
454161008 https://github.com/pydata/xarray/pull/2650#issuecomment-454161008 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDQ1NDE2MTAwOA== max-sixty 5635139 2019-01-14T21:05:17Z 2019-01-14T21:05:17Z MEMBER

That said, if EWM preserves the dimension size/labels you probably don't nee any special logic for coordinates

The error is when applying over a dimension on a dataset where only some of the variables have the dimension; e.g. applying over time on this:

python <xarray.Dataset> Dimensions: (time: 10, x: 8, y: 2) Coordinates: * x (x) float64 0.0 0.1429 0.2857 0.4286 0.5714 0.7143 0.8571 1.0 * time (time) float64 0.0 0.1111 0.2222 0.3333 ... 0.7778 0.8889 1.0 c (y) <U1 'a' 'b' * y (y) int64 0 1 Data variables: z1 (y, x) float64 -0.1035 -0.8153 -1.583 ... 1.447 0.7768 -0.2699 z2 (time, y) float64 0.968 0.7156 -1.64 ... 0.1889 -1.142 0.7172

...rather than any issues applying on coords. I think the solution is easy - only apply on variables where the dimension exists.

If it's helpful to add that functionality directly to apply_ufunc, lmk. I'll focus on getting this working, though

 
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   rolling_exp (nee ewm) 396084551
453896690 https://github.com/pydata/xarray/pull/2650#issuecomment-453896690 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDQ1Mzg5NjY5MA== max-sixty 5635139 2019-01-14T03:50:09Z 2019-01-14T03:50:45Z MEMBER

I think this is in a reasonable state for DataArray, excluding docs. Let me know any feedback on the APi

Does anyone have a view on the canonical way to implement these for Dataset, given potentially only a subset of the variables will have the dimension? Tests fail when naively using apply_ufunc; .reduce looks like it has some functionality for skipping those variables. Or I could do it manually in a couple of lines.

 
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   rolling_exp (nee ewm) 396084551
453842477 https://github.com/pydata/xarray/pull/2650#issuecomment-453842477 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDQ1Mzg0MjQ3Nw== max-sixty 5635139 2019-01-13T16:12:26Z 2019-01-13T16:12:26Z MEMBER

Tests seem to be failing on a different issue? https://travis-ci.org/pydata/xarray/jobs/479042667#L7759

 
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   rolling_exp (nee ewm) 396084551
452343420 https://github.com/pydata/xarray/pull/2650#issuecomment-452343420 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDQ1MjM0MzQyMA== max-sixty 5635139 2019-01-08T15:39:43Z 2019-01-08T15:39:43Z MEMBER

BTW, does ewm computes the window mean based on index or coordinate value?

Index, currently.

Would be great to have an algo that dealt with coord value, and I think not too difficult

 
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   rolling_exp (nee ewm) 396084551
451837195 https://github.com/pydata/xarray/pull/2650#issuecomment-451837195 https://api.github.com/repos/pydata/xarray/issues/2650 MDEyOklzc3VlQ29tbWVudDQ1MTgzNzE5NQ== max-sixty 5635139 2019-01-07T06:44:25Z 2019-01-07T06:44:25Z MEMBER

I know the name ewm matches pandas, but I find it rather inscrutable if you don't already know the acronym.

👍

What about something a little longer, maybe exp_rolling()?

Yes, that works. One alternative is to add a window_type / weighting argument to Rolling - Exponentially weighted is one of many alternatives

I'm fairly balanced between them - others' thoughts?

 
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   rolling_exp (nee ewm) 396084551

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