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  • max-sixty · 4 ✖

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  • DataArray.unstack() leaving dimensions 'in order' · 4 ✖

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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
590012159 https://github.com/pydata/xarray/issues/3786#issuecomment-590012159 https://api.github.com/repos/pydata/xarray/issues/3786 MDEyOklzc3VlQ29tbWVudDU5MDAxMjE1OQ== max-sixty 5635139 2020-02-23T00:18:34Z 2020-02-23T00:18:34Z MEMBER

I think it should be pretty reasonable to do that in a few lines, for numpy-backed arrays at least! Get the underlying numpy array, sort the .strides to get the memory order, map to dimension names, and pass them to transpose?

 
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   DataArray.unstack() leaving dimensions 'in order' 568968607
589985055 https://github.com/pydata/xarray/issues/3786#issuecomment-589985055 https://api.github.com/repos/pydata/xarray/issues/3786 MDEyOklzc3VlQ29tbWVudDU4OTk4NTA1NQ== max-sixty 5635139 2020-02-22T18:31:56Z 2020-02-22T18:31:56Z MEMBER

I think I see your point @takluyver — that by returning the new axes at the end it's both surprising and no longer a contiguous array.

But then +1 re your final point about unstack being unable to return a view on missing data.

I don't think it's impossible to carefully manage the dimensions order & contiguous-ness in this case. It may take someone who can champion it, though

 
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   DataArray.unstack() leaving dimensions 'in order' 568968607
589762619 https://github.com/pydata/xarray/issues/3786#issuecomment-589762619 https://api.github.com/repos/pydata/xarray/issues/3786 MDEyOklzc3VlQ29tbWVudDU4OTc2MjYxOQ== max-sixty 5635139 2020-02-21T17:53:51Z 2020-02-21T17:53:51Z MEMBER

So I'm understanding correctly: does numpy's behavior even satisfy your reqs? https://docs.scipy.org/doc/numpy/reference/generated/numpy.swapaxes.html

then a view of a is returned

i.e. the array's underlying layout doesn't change, only the view...

 
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   DataArray.unstack() leaving dimensions 'in order' 568968607
589687492 https://github.com/pydata/xarray/issues/3786#issuecomment-589687492 https://api.github.com/repos/pydata/xarray/issues/3786 MDEyOklzc3VlQ29tbWVudDU4OTY4NzQ5Mg== max-sixty 5635139 2020-02-21T14:55:05Z 2020-02-21T14:55:05Z MEMBER

Thanks for the issue @takluyver

I mostly think (others should weigh in) that we don't spend much effort on dimension order. (Would a dimension order change always be a regression?). That's mostly because of one of xarray's great strengths: you don't need to worry about the order, because you can reference dimensions by name.

I imagine that unstack dimension order wasn't carefully chosen to be at the end vs in place; and we'd take a PR to make that change.

 
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   DataArray.unstack() leaving dimensions 'in order' 568968607

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