Adding numpy zero array and masked array

Question

I have foll.. 2 numpy arrays:

arr_a = numpy.zeros(shape=(3, 3))

arr_b is second numpy array, but it is masked with mask value of -9999.0

if I do:

arr_a += arr_b

then the resulting arr_a does not retain the mask. How can I get an array in return that retains the mask?

donkopotamus · Accepted Answer · 2015-11-04 05:23:48Z

3

I'm assuming that arr_b is an instance of numpy.ma.array. In such a case the semantics of numpy mean that arr_a += arr_b is adding the array in-place. Thus, it certainly cannot alter its type from a numpy.array to a numpy.ma.array.

This is in contrast to arr_a + arr_b which is creating a new output array so is free to allocate it as it wishes.

If you wish to do an in-place add of a masked array, you must cast your target (arr_a) to be a masked array as well.

>>> arr_a = ma.asarray(arr_a)
>>> arr_a += arr_b

answered Nov 4, 2015 at 5:23

donkopotamus

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1 Comment

donkopotamus Over a year ago

yes ... however if you are wanting to repeatedly do additions, bear in mind that in-place add's (+=) are more efficient as they do not require memory allocation.

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