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  • `axis` keyword ignored when applying `np.squeeze` to `DataArray` · 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
318119534 https://github.com/pydata/xarray/issues/1487#issuecomment-318119534 https://api.github.com/repos/pydata/xarray/issues/1487 MDEyOklzc3VlQ29tbWVudDMxODExOTUzNA== shoyer 1217238 2017-07-26T17:08:12Z 2017-07-26T17:08:12Z MEMBER

I was under the impression that xarray.DataArrays behave the same as numpy.ndarrays when applying numpy functions, so that I didn't have to change any of my code.

We do attempt to make this work when feasible, but unfortunately it isn't always the case. In this case I do think this is doable, so I'm marking this issue as "Contributions welcome."

 
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   `axis` keyword ignored when applying `np.squeeze` to `DataArray` 245468219
317871442 https://github.com/pydata/xarray/issues/1487#issuecomment-317871442 https://api.github.com/repos/pydata/xarray/issues/1487 MDEyOklzc3VlQ29tbWVudDMxNzg3MTQ0Mg== shoyer 1217238 2017-07-25T21:02:59Z 2017-07-25T21:02:59Z MEMBER

This is (somewhat) expected. Basically, you should use the DataArray.squeeze() method instead.

The long story is that some but not all NumPy functions define themselves by (attempting) to call methods, e.g., np.squeeze(array) -> array.squeeze().

squeeze is a special and somewhat surprising case. Apparently np.squeeze(array, axis) -> array.squeeze(axis) -> array.squeeze() if the axis argument isn't handled. But we didn't bother to define an axis argument for DataArray.squeeze(), so this results in an error.

I suppose we could fix this by defining an axis argument, like we do for some methods like .mean(). But the short answer is that using xarray methods should be preferred.

 
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   `axis` keyword ignored when applying `np.squeeze` to `DataArray` 245468219

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