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  • matteodefelice · 2 ✖

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  • bottleneck : Wrong mean for float32 array · 2 ✖

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  • NONE · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
290822179 https://github.com/pydata/xarray/issues/1346#issuecomment-290822179 https://api.github.com/repos/pydata/xarray/issues/1346 MDEyOklzc3VlQ29tbWVudDI5MDgyMjE3OQ== matteodefelice 6360066 2017-03-31T20:31:56Z 2017-03-31T20:31:56Z NONE

Thanks all guys for the replies. @Aegaeon I get the same your results with bottleneck... @shoyer The point is that I haven't decided the use of float32 and — yes — using .astype(np.float64) solves the issue...the point is that is not an expected behaviour, with such standard dataset I would not expect any problem related to numerical precision...

 
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   bottleneck : Wrong mean for float32 array 218459353
290692479 https://github.com/pydata/xarray/issues/1346#issuecomment-290692479 https://api.github.com/repos/pydata/xarray/issues/1346 MDEyOklzc3VlQ29tbWVudDI5MDY5MjQ3OQ== matteodefelice 6360066 2017-03-31T11:53:12Z 2017-03-31T11:53:12Z NONE

Ok, I am on MacOS: - Python 2.7.13 from Macports - Dask 0.14.1 from Macports - xarray from GitHub 

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   bottleneck : Wrong mean for float32 array 218459353

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