What happened:
If I multiply a plain numpy array by a dask array, I get a dask array. But if I multiply a numpy masked array by a dask array, I get a numpy masked array.

What you expected to happen:
I would expect to either get a dask array in both cases, or the type of my first operand in both cases.

Minimal Complete Verifiable Example:

import numpy as np
import dask.array as da

plain_numpy_array = np.arange(5)
masked_numpy_array = np.ma.array(np.arange(5), mask=[0, 1, 1, 0, 0])
dask_array = da.from_array(plain_numpy_array)

print(type(plain_numpy_array * dask_array))
print(type(masked_numpy_array * dask_array))

output:

<class 'dask.array.core.Array'>
<class 'numpy.ma.core.MaskedArray'>

Anything else we need to know?:
This relates to #4441, and I note the advice at #4441 (comment) to explicitly convert the numpy arrays to dask arrays before the arithmetic operation. I am attempting to do this for Iris (SciTools/iris#3790) but, while teasing out the details of that, we noticed this inconsistency between plain numpy arrays and masked numpy arrays. I don't think the inconsistency was noted at #4441, and it possibly throws a new light on it?

Environment:

• Dask version: 2.26.0
• Python version: 3.7.8
• Operating System: RHEL7.8
• Install method (conda, pip, source): miniconda