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  • fujiisoup · 1 ✖

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  • Efficient rolling 'trick' · 1 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
371989690 https://github.com/pydata/xarray/issues/1978#issuecomment-371989690 https://api.github.com/repos/pydata/xarray/issues/1978 MDEyOklzc3VlQ29tbWVudDM3MTk4OTY5MA== fujiisoup 6815844 2018-03-10T01:18:11Z 2018-03-10T01:18:11Z MEMBER

Yes. ```python In [7]: da.rolling(date=3).construct('rolling_date') Out[7]: <xarray.DataArray (item: 2, date: 6, rolling_date: 3)> array([[[nan, nan, 0.], [nan, 0., 1.], [ 0., 1., 2.], [ 1., 2., 3.], [ 2., 3., 4.], [ 3., 4., 5.]],

   [[nan, nan,  6.],
    [nan,  6.,  7.],
    [ 6.,  7.,  8.],
    [ 7.,  8.,  9.],
    [ 8.,  9., 10.],
    [ 9., 10., 11.]]])

Dimensions without coordinates: item, date, rolling_date `` does the similar thing (rolling_window` in your example).

FYI, using sum without skipna option for such a strided DataArray (in your test_rolling_window_values) is not a good idea. We internally use np.nansum and this copies the entire array once. It throws away the advantage of the strided trick. sum(skipna=False) is memory efficient.

 
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   Efficient rolling 'trick' 304021813

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