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  • Support __matmul__ operator (@) · 5 ✖

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505992633 https://github.com/pydata/xarray/issues/1053#issuecomment-505992633 https://api.github.com/repos/pydata/xarray/issues/1053 MDEyOklzc3VlQ29tbWVudDUwNTk5MjYzMw== max-sixty 5635139 2019-06-26T18:28:31Z 2019-06-26T18:28:31Z MEMBER

Closed by #2987

 
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   Support __matmul__ operator (@) 184238633
405645739 https://github.com/pydata/xarray/issues/1053#issuecomment-405645739 https://api.github.com/repos/pydata/xarray/issues/1053 MDEyOklzc3VlQ29tbWVudDQwNTY0NTczOQ== shoyer 1217238 2018-07-17T16:32:45Z 2018-07-17T16:32:45Z MEMBER

Yes, we could definitely make @ between two xarray objects equivalent to xarray.dot().

 
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   Support __matmul__ operator (@) 184238633
290954513 https://github.com/pydata/xarray/issues/1053#issuecomment-290954513 https://api.github.com/repos/pydata/xarray/issues/1053 MDEyOklzc3VlQ29tbWVudDI5MDk1NDUxMw== shoyer 1217238 2017-04-01T23:40:06Z 2017-04-01T23:40:06Z MEMBER

My intuition was that we use @ on a DataArray in cases where DataArray.values @ numpy.ndarray or numpy.ndarray @ DataArray.values would work.

Suppose data_array is a DataArray with dimensions ['x', 'y'] and numpy_array is a numpy.ndarray with a compatible shape. What should data_array @ numpy_array look like? The first dimension should be labeled x, but the second dimension doesn't have a name, so we'd need to come up with one somehow (every dimension in an DataArray must have a name).

However, it appears that xarray may do some inference based aligning dimensions/coordinates... and that I need to understand this process a bit more.

Indeed, see http://xarray.pydata.org/en/stable/computation.html#broadcasting-by-dimension-name

 
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   Support __matmul__ operator (@) 184238633
290948916 https://github.com/pydata/xarray/issues/1053#issuecomment-290948916 https://api.github.com/repos/pydata/xarray/issues/1053 MDEyOklzc3VlQ29tbWVudDI5MDk0ODkxNg== shoyer 1217238 2017-04-01T21:40:04Z 2017-04-01T21:40:04Z MEMBER

More specifically, I'd like to be able to do matrix multiplication between numpy ndarrays / matrices, scipy sparse matrices, and xarray DataArrays.

I'm intrigued, but how would this work? data_array + numpy_array yields a result with well-defined labels as long as numpy_array broadcasts against data_array.data, but data_array @ numpy_array does not if numpy_array has 2 or more dimensions.

I guess we could prohibit @ with non-vector other arguments, but I still am concerned that the suggested meaning of @ per PEP 465 and numpy depends on the order of array dimensions. Basically, the last dimension of the left-hand-side argument should be matched against the second-to-last (or last, for 1D) dimension of the right-hand-side for the tensor contraction. In xarray terms, we could match the last dimension of the left-hand-side with any matching dimensions (by name) of the right-hand-side, but it's still messily inconsistent with other xarray operations, which are generally agnostic to to dimension order.

It also gets messy on Dataset objects, because the order of dimensions now becomes a bit more ambiguous: there's the order of dimensions on the Dataset itself, and the order on each DataArray in the dataset.

For these reasons, I'm leaning towards thinking that @ should be defined differently for xarray, and work like tensordot over all matching dimensions.

 
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   Support __matmul__ operator (@) 184238633
255126864 https://github.com/pydata/xarray/issues/1053#issuecomment-255126864 https://api.github.com/repos/pydata/xarray/issues/1053 MDEyOklzc3VlQ29tbWVudDI1NTEyNjg2NA== shoyer 1217238 2016-10-20T14:44:58Z 2016-10-20T14:44:58Z MEMBER

For xarray, probably the right choice is for @ to be an alias for .dot(): http://xarray.pydata.org/en/stable/generated/xarray.DataArray.dot.html

The broadcasting semantics of np.matmul don't quite make sense because it broadcasts based on axis position, not name.

 
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   Support __matmul__ operator (@) 184238633

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