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parallelize conversions/lookup with dask/xarray ufuncs #95

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NiklasPhabian opened this issue Jul 26, 2022 · 0 comments

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NiklasPhabian commented Jul 26, 2022

It would seem like dasks makes things as easy as:

import dask.distributed
import pystare

sids = xarray.apply_ufunc(pystare.from_latlon_2d, lats_x, lons_x, dask="parallelized", kwargs={'level': level})
with dask.distributed.Client(n_workers=60, threads_per_worker=2, memory_limit='2GB') as client:
    sids = compute.compute()
sids = xarray.DataArray.to_numpy(sids)

We might want to wrap all the bottleneck functions

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