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  • shoyer · 3 ✖

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  • Use of Xarray instead of np.meshgrid · 3 ✖

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350879291 https://github.com/pydata/xarray/issues/1773#issuecomment-350879291 https://api.github.com/repos/pydata/xarray/issues/1773 MDEyOklzc3VlQ29tbWVudDM1MDg3OTI5MQ== shoyer 1217238 2017-12-11T22:27:58Z 2017-12-11T22:27:58Z MEMBER

It seems that sympy functions returned by lambdfy may not work on arbitrary dimensional inputs, or might not follow broadcasting rules. The workaround might be something like: ```python def vector_func_wrapper(dx, dy, dz, dt): dx, dy, dz, dt = np.broadcast_arrays(dx, dy, dz, dt) # explicitly broadcast args = [a.ravel() for a in [dx, dy, dz, dt]] # convert everything to a vector return vector_funcN(*args).reshape(dx.shape)

xarray.apply_ufunc(vector_func_wrapper, dx, dy, dz, dt) ```

 
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   Use of Xarray instead of np.meshgrid 280899335
350821050 https://github.com/pydata/xarray/issues/1773#issuecomment-350821050 https://api.github.com/repos/pydata/xarray/issues/1773 MDEyOklzc3VlQ29tbWVudDM1MDgyMTA1MA== shoyer 1217238 2017-12-11T18:54:03Z 2017-12-11T18:54:03Z MEMBER

Broadcast allows a variadic number of arguments, so you can write something like: python gx, dy, gz, gt =xr.broadcast(dx, dy, dz, dt)

I'm not very familiar with sympy's lambdify, but I think something like xarray.apply_ufunc(vector_funcN, dx, dy, dz, dt) should work (where dx, dy, dz and dt are all xarray objects, even without manual broadcasting).

 
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   Use of Xarray instead of np.meshgrid 280899335
350806352 https://github.com/pydata/xarray/issues/1773#issuecomment-350806352 https://api.github.com/repos/pydata/xarray/issues/1773 MDEyOklzc3VlQ29tbWVudDM1MDgwNjM1Mg== shoyer 1217238 2017-12-11T18:02:39Z 2017-12-11T18:02:39Z MEMBER

If you make each of your arrays xAxisDomian an xarray.DataArray with appropriate dimensions, you can use xarray.broadcast() to convert all of them to common coordinates. xarray.apply_ufunc may also help.

 
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   Use of Xarray instead of np.meshgrid 280899335

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