Yes you can use numpy.s_
:
Example:
>>> a = np.arange(10).reshape(2, 5)
>>>
>>> m = np.s_[0:2, 3:4]
>>>
>>> a[m]
array([[3],
[8]])
And in this case:
my_slice = np.s_[cpix[1]-50:cpix[1]+50, cpix[0]-50:cpix[0]+50]
a1 = array1[my_slice]
a2 = array2[my_slice]
a3 = array3[my_slice]
You can also use numpy.r_
in order to translates slice objects to concatenation along the first axis.