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  • niowniow · 3 ✖

issue 1

  • Feature Request: Efficient rolling with strides · 3 ✖

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  • CONTRIBUTOR · 3 ✖
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888250482 https://github.com/pydata/xarray/issues/3608#issuecomment-888250482 https://api.github.com/repos/pydata/xarray/issues/3608 IC_kwDOAMm_X8408aBy niowniow 5802846 2021-07-28T11:58:28Z 2021-07-28T11:58:28Z CONTRIBUTOR

You are right. It's quite confusing. I've already added a stride parameter in my PR #3607 I didn't follow through with it and at the moment the checks are not successful anymore. Maybe someone else could give an opinion on the pro/cons of a stride parameter in rolling? 

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   Feature Request: Efficient rolling with strides 535703663
851469496 https://github.com/pydata/xarray/issues/3608#issuecomment-851469496 https://api.github.com/repos/pydata/xarray/issues/3608 MDEyOklzc3VlQ29tbWVudDg1MTQ2OTQ5Ng== niowniow 5802846 2021-05-31T12:50:37Z 2021-05-31T12:50:37Z CONTRIBUTOR

Quickly glancing over sliding_window_view I didn't immediately understand how to use it with stride. Would I need to 1. transform the DataArray to dask array using chunk (which may involve an overhead!?), 2. then use rolling which itself uses sliding_window_view because its a dask array!? 3. Then use isel with stride on the new dimension?

reduce can easily support stride by passing it on here:

I think that's what I did in #3607. It's been a while

 
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   Feature Request: Efficient rolling with strides 535703663
564023352 https://github.com/pydata/xarray/issues/3608#issuecomment-564023352 https://api.github.com/repos/pydata/xarray/issues/3608 MDEyOklzc3VlQ29tbWVudDU2NDAyMzM1Mg== niowniow 5802846 2019-12-10T13:05:10Z 2019-12-10T13:05:10Z CONTRIBUTOR 
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   Feature Request: Efficient rolling with strides 535703663

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