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  • shoyer · 2 ✖

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  • problems with big endian DataArrays · 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
124199070 https://github.com/pydata/xarray/issues/489#issuecomment-124199070 https://api.github.com/repos/pydata/xarray/issues/489 MDEyOklzc3VlQ29tbWVudDEyNDE5OTA3MA== shoyer 1217238 2015-07-23T18:28:32Z 2015-07-23T18:28:32Z MEMBER

This is a bug in bottleneck: https://github.com/kwgoodman/bottleneck/issues/104

You can work around this issue for now by uninstalling bottleneck. This will have a slight performance cost for little endian arrays, but it shouldn't be a big deal.

I'll also add a check to ensure we never try to pass big endian arrays to bottleneck.

 
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   problems with big endian DataArrays 96732359
124002256 https://github.com/pydata/xarray/issues/489#issuecomment-124002256 https://api.github.com/repos/pydata/xarray/issues/489 MDEyOklzc3VlQ29tbWVudDEyNDAwMjI1Ng== shoyer 1217238 2015-07-23T07:13:26Z 2015-07-23T07:13:26Z MEMBER

Do have bottleneck installed?

I've seen error messages from summing big endian arrays before, but never silently wrong results.

We resolved many of these issues for netcdf3 files by coercing arrays to little endian upon reading them from disk. We might even extend this to all arrays loaded into xray. 

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   problems with big endian DataArrays 96732359

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