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  • laliberte · 3 ✖

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  • Implementing dask.array.coarsen in xarrays · 3 ✖

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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
305176003 https://github.com/pydata/xarray/issues/1192#issuecomment-305176003 https://api.github.com/repos/pydata/xarray/issues/1192 MDEyOklzc3VlQ29tbWVudDMwNTE3NjAwMw== laliberte 3217406 2017-05-31T12:45:18Z 2017-05-31T12:45:18Z CONTRIBUTOR

The reason I ask is that, ideally, coarsen would work exactly the same with dask.array and np.ndarray data. By using both serial and parallel coarsen methods from dask, we are adding a dependency but we are ensuring forward compatibility. @shoyer, what's your preference? (1) replicate serial coarsen into xarray or (2) point to dask coarsen methods?

 
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   Implementing dask.array.coarsen in xarrays 198742089
305169201 https://github.com/pydata/xarray/issues/1192#issuecomment-305169201 https://api.github.com/repos/pydata/xarray/issues/1192 MDEyOklzc3VlQ29tbWVudDMwNTE2OTIwMQ== laliberte 3217406 2017-05-31T12:00:11Z 2017-05-31T12:00:11Z CONTRIBUTOR

If it's part of dask then it would be almost trivial to implement in xarray. @mrocklin Can we assume that dask/array/chunk.py::coarsen is part of the public API?

 
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   Implementing dask.array.coarsen in xarrays 198742089
270439515 https://github.com/pydata/xarray/issues/1192#issuecomment-270439515 https://api.github.com/repos/pydata/xarray/issues/1192 MDEyOklzc3VlQ29tbWVudDI3MDQzOTUxNQ== laliberte 3217406 2017-01-04T17:59:08Z 2017-01-04T17:59:08Z CONTRIBUTOR

The dask implementation has the following API: dask.array.coarsen(reduction, x, axes, trim_excess=False) so a proposed xarray API could look like: xarray.coarsen(reduction, x, axes, chunks=None, trim_excess=False), resulting in the following implementation: 1. If the underlying data to x is dask.array, yields x.chunks(chunks).array.coarsen(reduction, axes, trim_excess) 2. Else, copy the block_reduce function.

Does that fit with the xarray API?

 
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   Implementing dask.array.coarsen in xarrays 198742089

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