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  • shoyer · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
525427300 https://github.com/pydata/xarray/pull/3258#issuecomment-525427300 https://api.github.com/repos/pydata/xarray/issues/3258 MDEyOklzc3VlQ29tbWVudDUyNTQyNzMwMA== shoyer 1217238 2019-08-27T18:30:34Z 2019-08-27T18:30:34Z MEMBER

apply_ufunc is extremely powerful, and when you need to cope with all possible shape transformations, I suspect its verbosity is quite necessary. It's just that, when all you need to do is apply an elementwise, embarassingly parallel function (80% of the times in my real life experience), apply_ufunc is overkill.

Yes, 100% agreed! There is a real need for a simpler version of apply_ufunc.

The thing I have against the name map_blocks is that backends other than dask have no notion of blocks...

I think the functionality in this PR is fundamentally dask specific. We shouldn't make a habit of adding backend specific features, but it makes sense in limited cases.

 
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   [WIP] Add map_blocks. 484752930
525384446 https://github.com/pydata/xarray/pull/3258#issuecomment-525384446 https://api.github.com/repos/pydata/xarray/issues/3258 MDEyOklzc3VlQ29tbWVudDUyNTM4NDQ0Ng== shoyer 1217238 2019-08-27T16:40:32Z 2019-08-27T16:40:32Z MEMBER
  • could we call it just "map"? It makes sense as this thing would be very useful for non-dask based arrays too. Working routinely with scipy (chiefly with scipy.stats transforms), I tire a lot of writing very verbose xarray.apply_ufunc calls.

I agree that apply_ufunc is overly verbose. See https://github.com/pydata/xarray/issues/1074 and https://github.com/pydata/xarray/issues/1618 (and issues linked therein) for discussion about alternative APIs.

I still think this particular set of functionality should be called map_blocks, because it works by applying functions over each block, very similar to dask's map_blocks.

 
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   [WIP] Add map_blocks. 484752930

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