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  • rabernat · 2 ✖

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  • Creating a 2D DataArray · 2 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
291544663 https://github.com/pydata/xarray/issues/1351#issuecomment-291544663 https://api.github.com/repos/pydata/xarray/issues/1351 MDEyOklzc3VlQ29tbWVudDI5MTU0NDY2Mw== rabernat 1197350 2017-04-04T15:53:33Z 2017-04-04T15:53:33Z MEMBER

Why not combine all your model arrays into a single Dataset? Since they almost certainly share coordinates, this would make sense.

 
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   Creating a 2D DataArray 219184224
291533765 https://github.com/pydata/xarray/issues/1351#issuecomment-291533765 https://api.github.com/repos/pydata/xarray/issues/1351 MDEyOklzc3VlQ29tbWVudDI5MTUzMzc2NQ== rabernat 1197350 2017-04-04T15:19:20Z 2017-04-04T15:19:20Z MEMBER

There is no such thing as a "multidimensional DataArray" in the xarray data model. DataArrays can have "non-dimension coordinates" which can be used for things like grouping.

This would work python new_array = DataArray(np.zeros((2,2)), dims=['x_logical','y_logical']) new_array.coords['x_physical'] = x_physical new_array.coords['y_physical'] = y_physical new_array.groupby('x_physical').mean()

I don't know how to do this as a one-liner. Probably easier to create a Dataset rather than DataArray for this purpose python ds = xr.Dataset({'testdata': (('y_logical', 'x_logical'), np.zeros((2,2)))}, coords={'x_physical': (('y_logical', 'x_logical'), np.ones((2,2))), 'y_physical': (('y_logical', 'x_logical'), np.ones((2,2)))})

 
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   Creating a 2D DataArray 219184224

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