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4 rows where author_association = "MEMBER", issue = 128687346 and user = 1217238 sorted by updated_at descending

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  • shoyer · 4 ✖

issue 1

  • Implement tensordot for xarray with dask support · 4 ✖

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  • MEMBER · 4 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
192539434 https://github.com/pydata/xarray/issues/723#issuecomment-192539434 https://api.github.com/repos/pydata/xarray/issues/723 MDEyOklzc3VlQ29tbWVudDE5MjUzOTQzNA== shoyer 1217238 2016-03-05T00:47:49Z 2016-03-05T00:47:49Z MEMBER

Fixed by #731.

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  Implement tensordot for xarray with dask support 128687346
175383509 https://github.com/pydata/xarray/issues/723#issuecomment-175383509 https://api.github.com/repos/pydata/xarray/issues/723 MDEyOklzc3VlQ29tbWVudDE3NTM4MzUwOQ== shoyer 1217238 2016-01-27T04:24:42Z 2016-01-27T04:24:42Z MEMBER

I'm split on whether a function or method makes more sense (a.tensordot(b, dim='x') vs xr.tensordot(a, b, dim='x')). I would be OK with either, so yes, please do go ahead!

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  Implement tensordot for xarray with dask support 128687346
174841301 https://github.com/pydata/xarray/issues/723#issuecomment-174841301 https://api.github.com/repos/pydata/xarray/issues/723 MDEyOklzc3VlQ29tbWVudDE3NDg0MTMwMQ== shoyer 1217238 2016-01-26T05:34:40Z 2016-01-26T05:34:40Z MEMBER

@MaximilianR I do like einsum, but I'm not sure the API would be a good fit for xarray (we already have dimension names), and it also does not exist yet for dask (https://github.com/blaze/dask/issues/732).

That said, I suppose you could make an xarray version of einsum with syntax that looks more like tensordot with *args, e.g., einsum(a, b, c, dims=('x', 'y')).

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  Implement tensordot for xarray with dask support 128687346
174839547 https://github.com/pydata/xarray/issues/723#issuecomment-174839547 https://api.github.com/repos/pydata/xarray/issues/723 MDEyOklzc3VlQ29tbWVudDE3NDgzOTU0Nw== shoyer 1217238 2016-01-26T05:27:36Z 2016-01-26T05:32:02Z MEMBER

Yes, this would be a nice addition!

I spent a little bit of a time futzing around with this to see if there is an elegant way to plug this into our existing dispatching system. The short of it is that the answer appears to be no -- we don't have any elegant equivalent to dask.array's generic atop method.

So, for now I would simply write a function specialized to DataArray objects. Something like the following (barely tested) is a starting point:

``` python from xarray import align, DataArray

note: using private imports (e.g., from xarray.core) is definitely discouraged!

this is not guaranteed to work in future versions of xarray

from xarray.core.ops import _dask_or_eager_func

def tensordot(a, b, dims): if not (isinstance(a, DataArray) and isinstance(b, DataArray)): raise ValueError

a, b = align(a, b, join='inner', copy=False)

axes = (a.get_axis_num(dims), b.get_axis_num(dims))
f = _dask_or_eager_func('tensordot', n_array_args=2)
new_data = f(a.data, b.data, axes=axes)

if isinstance(dims, basestring):
    dims = [dims]

new_coords = a.coords.merge(b.coords).drop(dims)

new_dims = ([d for d in a.dims if d not in dims] +
            [d for d in b.dims if d not in dims])

return DataArray(new_data, new_coords, new_dims)

```

This would be worth cleaning up so we could add it to the codebase (mostly documentation & tests).

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  Implement tensordot for xarray with dask support 128687346

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