import numpy
data = numpy.array([[ 1, 2, 5 ]])
mask = numpy.array([[0,1,0]])

numpy.ma.masked_array(data, ~mask) 
# note this probably won't work right for non-boolean (T/F) values

# or
numpy.ma.masked_array(data, numpy.logical_not(mask))


# for example

>>> a = numpy.array([False,True,False])
>>> ~a
array([ True, False,  True], dtype=bool)
>>> numpy.logical_not(a)
array([ True, False,  True], dtype=bool)
>>> a = numpy.array([0,1,0])
>>> ~a
array([-1, -2, -1])
>>> numpy.logical_not(a)
array([ True, False,  True], dtype=bool)