issue_comments: 973971543

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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?

 
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