strange behaviour of numpy masked array

Question

I have troubles understanding the behaviour of numpy masked array.

Here is the snippet that puzzles me for two reasons:

arr = numpy.ma.array([(1,2),(3,4)],dtype=[("toto","int"),("titi","int")])
arr[0][0] = numpy.ma.masked

when doing this nothing happens, no mask is applied on the element [0][0]
changing the data to [[1,2],[3,4]] (instead of [(1,2),(3,4)]), I get the following error: TypeError: expected a readable buffer object

It seems that I misunderstood completely how to setup (and use) masked array.

Could you tell me what is wrong with this code ?

thanks

EDIT: without specifying the dtypes, it works like expected

Saullo G. P. Castro · Accepted Answer · 2013-10-30 18:29:42Z

1

The purpose of a masked array is to tell for any operation that some elements of the array are invalid to be used, i.e. masked.

For example, you have an array:

a = np.array([[2, 1000], [3, 1000]])

And you want to ignore any operations with the elements >100. You create a masked array like:

b = np.ma.array(a, mask=(a>100))

You can perform some operations in both arrays to see the differences:

a.sum()
# 2005
b.sum()
# 5

a.prod()
# 6000000
b.prod()
# 6

As you see, the masked items are ignored...

answered Oct 30, 2013 at 18:29

Saullo G. P. Castro

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Saullo G. P. Castro Over a year ago

@PellegriniEric I've seen you haven't accepted any answer. Just to let you know, you can do it by clicking on the arrow at the left-hand side of the answer...

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