Comparison with masked array yields object-array with nans for masked values

Code Sample, a copy-pastable example if possible

$ cat mwe.py 
#!/usr/bin/env python3.6
import xarray
import numpy

da = xarray.DataArray(numpy.arange(5))
ma = numpy.ma.masked_array(numpy.arange(5), [True, False, False, False, True])
print(da>ma)
$ ./mwe.py 
<xarray.DataArray (dim_0: 5)>
array([nan, False, False, False, nan], dtype=object)
Dimensions without coordinates: dim_0

Problem description

A comparison between a DataArray and a masked_array results in an array with dtype object instead of an array with dtype bool. This is problematic, because code should be able to assume that x > y returns something with a bool dtype.

Expected Output

I would expect the masked array to be dropped (which it is) and an array to be returned equivalent to the comparison da>ma.data

<xarray.DataArray (dim_0: 5)>
array([False, False, False, False, False], dtype=bool)
Dimensions without coordinates: dim_0

Output of xr.show_versions()

Start by running the supplied mwe.py example with the reported Python, NumPy, and xarray versions, then trace how DataArray comparisons handle a numpy masked_array. Add a regression test for the comparison result and verify that the output has bool dtype with masked values handled as shown in the expected output.