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  • Bottleneck bug with unusual strides - causes segfault or wrong number · 4 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
862579076 https://github.com/pydata/xarray/issues/5424#issuecomment-862579076 https://api.github.com/repos/pydata/xarray/issues/5424 MDEyOklzc3VlQ29tbWVudDg2MjU3OTA3Ng== dcherian 2448579 2021-06-16T17:42:34Z 2021-06-16T17:42:34Z MEMBER

there's a config for disabling bottleneck — assuming that's correct, we'd take a PR for one.

Yeah I think it'd be nice to opt-in/out to bottleneck and maybe even support numbagg somehow.

 
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   Bottleneck bug with unusual strides - causes segfault or wrong number 908464731
852355465 https://github.com/pydata/xarray/issues/5424#issuecomment-852355465 https://api.github.com/repos/pydata/xarray/issues/5424 MDEyOklzc3VlQ29tbWVudDg1MjM1NTQ2NQ== max-sixty 5635139 2021-06-01T18:36:04Z 2021-06-01T18:36:04Z MEMBER

I don't think there's a config for disabling bottleneck — assuming that's correct, we'd take a PR for one.

FYI one does seem to work is setting the type to float:

python ...: xarr.astype(float).max() Out[1]: <xarray.DataArray ()> array(0.)

 
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   Bottleneck bug with unusual strides - causes segfault or wrong number 908464731
852334068 https://github.com/pydata/xarray/issues/5424#issuecomment-852334068 https://api.github.com/repos/pydata/xarray/issues/5424 MDEyOklzc3VlQ29tbWVudDg1MjMzNDA2OA== lusewell 3801015 2021-06-01T18:01:05Z 2021-06-01T18:01:05Z CONTRIBUTOR

Annoyingly the bug affects pretty much every bottleneck function, not just max, and I'm dealing with a large codebase where lots of the code just uses the methods attached to the xr.DataArrays.

Is there a way of disabling use of bottleneck inside xarray without uninstalling bottleneck? And if so do you know if this is expected to give the same results? Pandas (probably a few versions ago now) had a situation where if you uninstalled bottleneck it would use some other routine, but the nan-handling was then different - I think it caused the all-nan sum to flick between nan and zero if I recall.

Quick response appreciated though, and I might have a delve into fixing bottleneck myself if I get the free time.

 
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   Bottleneck bug with unusual strides - causes segfault or wrong number 908464731
852265735 https://github.com/pydata/xarray/issues/5424#issuecomment-852265735 https://api.github.com/repos/pydata/xarray/issues/5424 MDEyOklzc3VlQ29tbWVudDg1MjI2NTczNQ== max-sixty 5635139 2021-06-01T16:33:09Z 2021-06-01T16:33:16Z MEMBER

Thanks @lusewell . Unfortunately — as you suggest — I don't think there's much we can do — but this does seem like a bad bug.

It might be worth checking out numbagg — https://github.com/numbagg/numbagg — which we use for fast operations that bottleneck doesn't include. Disclaimer that it comes from @shoyer , and I've recently given it a spring cleaning. To the extent this isn't fixed in bottleneck, we could offer an option to use numbagg, though it would probably require a contribution.

If you need this working for now, you could probably write a workaround for yourself using numbagg fairly quickly; e.g.

```python In [6]: numbagg.nanmax(xarr.values) Out[6]: 0.0

or, more generally:

In [12]: xr.apply_ufunc(numbagg.nanmax, xarr, input_core_dims=(('A','B','C'),)) Out[12]: <xarray.DataArray ()> array(0.) ```

 
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   Bottleneck bug with unusual strides - causes segfault or wrong number 908464731

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