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  • Some simple broadcast_dim method? · 4 ✖

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  • NONE · 4 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
405950145 https://github.com/pydata/xarray/issues/2267#issuecomment-405950145 https://api.github.com/repos/pydata/xarray/issues/2267 MDEyOklzc3VlQ29tbWVudDQwNTk1MDE0NQ== Hoeze 1200058 2018-07-18T14:26:58Z 2018-07-18T14:27:35Z NONE

Maybe related:

Consider the following example to calculate pairwise distances: x = np.array([[1,2,3,4]]) dist = x.T - x numpy automatically broadcasts the one-dimensions to get 4x4 matrices and substracts them.

As far as I can see, this example is really hard to recreate with xarray, since there is nearly no possibility to add a new dimension to x and broadcast it properly.

 
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   Some simple broadcast_dim method? 338226520
402528134 https://github.com/pydata/xarray/issues/2267#issuecomment-402528134 https://api.github.com/repos/pydata/xarray/issues/2267 MDEyOklzc3VlQ29tbWVudDQwMjUyODEzNA== Hoeze 1200058 2018-07-04T17:06:51Z 2018-07-04T17:06:51Z NONE

@shoyer so there is no direct xarray equivalent to np.broadcast_to?

 
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   Some simple broadcast_dim method? 338226520
402524911 https://github.com/pydata/xarray/issues/2267#issuecomment-402524911 https://api.github.com/repos/pydata/xarray/issues/2267 MDEyOklzc3VlQ29tbWVudDQwMjUyNDkxMQ== Hoeze 1200058 2018-07-04T16:45:39Z 2018-07-04T16:45:39Z NONE

As an explanation: I'd like to change my program to only use lazy / chunked calculations in order to save RAM.

I recognized that np.broadcast_to converts the DataArray into a numpy one. Therefore I needed some xarray way to solve this.

I tried: python DataArray.expand_dims("new_dim").isel("new_dim", np.repeat(0, target_dim_size)) but this really looks ugly and I'm not sure about the performance implications of this.

 
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   Some simple broadcast_dim method? 338226520
402459865 https://github.com/pydata/xarray/issues/2267#issuecomment-402459865 https://api.github.com/repos/pydata/xarray/issues/2267 MDEyOklzc3VlQ29tbWVudDQwMjQ1OTg2NQ== Hoeze 1200058 2018-07-04T12:07:49Z 2018-07-04T12:18:54Z NONE

No, I'd need something like np.tile. expand_dims inserts only a dimension of length '1'

 
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   Some simple broadcast_dim method? 338226520

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