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  • crusaderky · 2 ✖

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  • [WIP] Add map_blocks. · 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
525425560 https://github.com/pydata/xarray/pull/3258#issuecomment-525425560 https://api.github.com/repos/pydata/xarray/issues/3258 MDEyOklzc3VlQ29tbWVudDUyNTQyNTU2MA== crusaderky 6213168 2019-08-27T18:26:17Z 2019-08-27T18:26:17Z MEMBER

@shoyer let me rephrase it - 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.

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

 
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   [WIP] Add map_blocks. 484752930
525298264 https://github.com/pydata/xarray/pull/3258#issuecomment-525298264 https://api.github.com/repos/pydata/xarray/issues/3258 MDEyOklzc3VlQ29tbWVudDUyNTI5ODI2NA== crusaderky 6213168 2019-08-27T13:21:44Z 2019-08-27T13:21:44Z MEMBER

Hi,

A few design opinions:

  1. 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.

  2. could we have it as a method of DataArray and Dataset, to allow for method chaining?

e.g. python myarray.map(func1).chunk().map(func2).sum().compute()

 
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   [WIP] Add map_blocks. 484752930

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