Indexing a dask array with a boolean array

[miguelcarcamov]

Hi everyone,

I've been having this question a long time ago, and I'm not pretty sure about the answer. When indexing a dask array is it better to do it with a numpy array or a dask array? I have a code that calculates valid data -> creates an array of True and False, True for those valid data, and False otherwise. The problem is that if I index the data this way I get (nan,) shape chunks. Is there a way to avoid this? I know a way to fix this is to do a compute_chunk_sizes(), but I guess that takes a lot of computing time. Is there another way to avoid it?

import dask.array as da

a = da.random.random((10,))
c = da.random.randint(low=0, high=1, size=(10,))
a[c.astype(bool)]
dask.array<getitem, shape=(nan,), dtype=float64, chunksize=(nan,), chunktype=numpy.ndarray>

Cheers