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  • burnpanck · 2 ✖

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  • Performance degradation: `DataArray` with `dtype=object` of `DataArray` gets very slow indexing · 2 ✖

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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
260704684 https://github.com/pydata/xarray/issues/1121#issuecomment-260704684 https://api.github.com/repos/pydata/xarray/issues/1121 MDEyOklzc3VlQ29tbWVudDI2MDcwNDY4NA== burnpanck 1310437 2016-11-15T17:15:25Z 2016-11-15T17:15:25Z CONTRIBUTOR

I think I found it (#1122). I guess whenever a non-scalar assignment is made (as in result[:] = [value]), something like np.asanyarray is performed on the new value. Luckily, numpy is perfectly happy with indexing of a 0d array with a 0d index (i.e. an empty tuple). Thinking about it, result[0] = value would probably have worked too.

 
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   Performance degradation: `DataArray` with `dtype=object` of `DataArray` gets very slow indexing 189415576
260697960 https://github.com/pydata/xarray/issues/1121#issuecomment-260697960 https://api.github.com/repos/pydata/xarray/issues/1121 MDEyOklzc3VlQ29tbWVudDI2MDY5Nzk2MA== burnpanck 1310437 2016-11-15T16:52:41Z 2016-11-15T16:52:41Z CONTRIBUTOR

Well, xarrays are way too useful not to nest them, even if that involves the scary dtype=object :-). Thanks for pointing me in the right direction, I'll try to find a fix.

 
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   Performance degradation: `DataArray` with `dtype=object` of `DataArray` gets very slow indexing 189415576

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