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  • max-sixty · 1 ✖

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  • cartesian product of coordinates and using it to index / fill empty dataset · 1 ✖

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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
366791162 https://github.com/pydata/xarray/issues/1914#issuecomment-366791162 https://api.github.com/repos/pydata/xarray/issues/1914 MDEyOklzc3VlQ29tbWVudDM2Njc5MTE2Mg== max-sixty 5635139 2018-02-19T20:05:53Z 2018-02-19T20:05:53Z MEMBER

I think that this shouldn't be too hard to 'get done' but also that xarray may not give you much help natively. (I'm not sure though, so take this as hopefully helpful contribution rather than a definitive answer)

Specifically, can you do (2) by generating a product of the coords? Either using numpy, stacking, or some simple python:

```python

In [3]: list(product(*((data[x].values) for x in data.dims))) Out[3]: [(0.287706062977495, 0.065327131503921), (0.287706062977495, 0.17398282388217068), (0.287706062977495, 0.1455022501442349), (0.42398126102299216, 0.065327131503921), (0.42398126102299216, 0.17398282388217068), (0.42398126102299216, 0.1455022501442349), (0.13357153947234057, 0.065327131503921), (0.13357153947234057, 0.17398282388217068), (0.13357153947234057, 0.1455022501442349), (0.42347765161572537, 0.065327131503921), (0.42347765161572537, 0.17398282388217068), (0.42347765161572537, 0.1455022501442349)] ```

then distribute those out to a cluster if you need, and then unstack them back into a dataset?

 
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   cartesian product of coordinates and using it to index / fill empty dataset 297560256

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