issue_comments: 413779588

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https://github.com/pydata/xarray/issues/2370#issuecomment-413779588 https://api.github.com/repos/pydata/xarray/issues/2370 413779588 MDEyOklzc3VlQ29tbWVudDQxMzc3OTU4OA== 6815844 2018-08-17T07:16:43Z 2018-08-17T07:16:43Z MEMBER

Does it work to simply specify an explicit dtype in the sum?

Yes. If the original array is in np.float32 and we specify dtype=np.float64, then the calculation will be performed with np.nansum, so we can avoid using bottleneck. But if we set dtype=np.float32 (the same with the input dtype), then bottleneck will be used.

But I do think it still probably offers a meaningful speedup in many cases....

How about making numpy function default and we use bottleneck only when it is specified explicitly? It does not simplify our code though...

 
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