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  • deanpospisil · 3 ✖

issue 1

  • Implement tensordot for xarray with dask support · 3 ✖

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  • NONE · 3 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
175378477 https://github.com/pydata/xarray/issues/723#issuecomment-175378477 https://api.github.com/repos/pydata/xarray/issues/723 MDEyOklzc3VlQ29tbWVudDE3NTM3ODQ3Nw== deanpospisil 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.

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  Implement tensordot for xarray with dask support 128687346
175378292 https://github.com/pydata/xarray/issues/723#issuecomment-175378292 https://api.github.com/repos/pydata/xarray/issues/723 MDEyOklzc3VlQ29tbWVudDE3NTM3ODI5Mg== deanpospisil 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!

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  Implement tensordot for xarray with dask support 128687346
175175494 https://github.com/pydata/xarray/issues/723#issuecomment-175175494 https://api.github.com/repos/pydata/xarray/issues/723 MDEyOklzc3VlQ29tbWVudDE3NTE3NTQ5NA== deanpospisil 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') ```

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  Implement tensordot for xarray with dask support 128687346

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