Parallelize moving polygon sample from ITS_LIVE datacube

[ahuang11]

I think there’s a couple approaches I would take:

1. simply decorate with @dask.delayed and call dask.compute(scheduler=client) where client = distributed.Client() on the results
2. Or use ds.map_blocks

Here’s an example with plotting

Using Dask to parallelize plotting

@ahuang11 chatted an interesting use case in the pyviz gitter using Dask to parallelize the generation of a bunch of plots. I hadn’t done that before with Dask so I tried it out: import xarray as xr import dask import matplotlib.pyplot as plt ds = xr.tutorial.open_dataset('air_temperature').load() @dask.delayed def plot(ds, time): ds.sel(time=time)['air'].plot() plt.savefig(str(time)[:16]) tasks = [plot(ds, time) for time in ds['time'].values] # just do first few dask.compute(task…