html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/723#issuecomment-175378477,https://api.github.com/repos/pydata/xarray/issues/723,175378477,MDEyOklzc3VlQ29tbWVudDE3NTM3ODQ3Nw==,15167171,2016-01-27T03:59:46Z,2016-01-27T04:00:24Z,NONE,"Also that einsum does seem pretty ideal. I'll see if I can get it running in dask, so we can port it over here.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,128687346
https://github.com/pydata/xarray/issues/723#issuecomment-175378292,https://api.github.com/repos/pydata/xarray/issues/723,175378292,MDEyOklzc3VlQ29tbWVudDE3NTM3ODI5Mg==,15167171,2016-01-27T03:58:31Z,2016-01-27T03:58:31Z,NONE,"I wasn't sure where the best place to put the def would be. Currently I have been running it from the xarray class:
`t = da1.tensordot( da2, 'shapes' )`
Let me know if that seems alright, then I'll write some simple tests in test_dataarray for tensor dot.
Maybe make my first pull request!
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,128687346
https://github.com/pydata/xarray/issues/723#issuecomment-175175494,https://api.github.com/repos/pydata/xarray/issues/723,175175494,MDEyOklzc3VlQ29tbWVudDE3NTE3NTQ5NA==,15167171,2016-01-26T18:53:02Z,2016-01-26T18:53:02Z,NONE,"Looks like it can perform tensor dot for dask and straight xarrays! But apparently dask has not implemented tensordot with multiple axes arguments, and it also does not work performing a tensor dot between a dask xarray and an xarray. Neither of these cases worries me too much, hopefully they don't worry you.

``` 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, str):
        dims = [dims]

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

    #drop the dims you are performing the sum product over
    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)

import xarray as xr
import numpy as np

x_trans = np.linspace(-3,3,6)
y_trans = np.linspace(-3,3,5)
imgID = range(4)
da = xr.DataArray( np.ones((6,5,4)), 
coords = [ x_trans, y_trans, imgID ], 
dims = ['x_trans', 'y_trans', 'imgID'] )

models = range(20)
dm = xr.DataArray( np.ones(( 20 , 5, 4 )), 
coords = [ models, y_trans, imgID], 
dims = [ 'models', 'y_trans', 'imgID' ] )

#xarray tensordot
proj_a = tensordot(da, dm, 'imgID')

#dask xarray tensor dot
da = da.chunk()
dm = dm.chunk()
proj_b = tensordot(da, dm, 'imgID')

#errors
#multiple dims
proj_c = tensordot(da, dm, ['imgID', 'y_trans'])

#mixed types
da = da.chunk()
dm = dm.load()
proj_d = tensordot(da, dm, 'imgID')
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,128687346