html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/6002#issuecomment-973971543,https://api.github.com/repos/pydata/xarray/issues/6002,973971543,IC_kwDOAMm_X846DaBX,14808389,2021-11-19T10:56:32Z,2021-11-19T10:56:32Z,MEMBER,"It's just a simple `numpy.ndarray.transpose`:
```python
In [1]: import numpy as np
   ...: import bottleneck as bn
   ...: 
   ...: n_time = 1
   ...: spec_data = np.random.random(size=(n_time,192,121))
   ...: 
   ...: bn.nanmax(spec_data.transpose(0, 2, 1))
Segmentation fault
```
`numpy.transpose` returns a view, so I guess that's what causes `bottleneck` to segfault? Not sure, though, especially since changing the order does not trigger the segfault: `spec_data.transpose(1, 0, 2)`... maybe `bottleneck` doesn't like views with a first dimension of size `1`?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057335460
https://github.com/pydata/xarray/issues/6002#issuecomment-973229567,https://api.github.com/repos/pydata/xarray/issues/6002,973229567,IC_kwDOAMm_X846Ak3_,5635139,2021-11-18T20:19:59Z,2021-11-18T20:19:59Z,MEMBER,"Thanks for the detail @RubendeBruin . I'm guessing this a bottleneck issue — would you be up for trying to run bottleneck's `nanmax` function on the underlying numpy array (`xdata.data`), and seeing whether that has the same effect?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057335460