Substituting values in a numpy masked array

Question

I'm trying to substitute some values in a numpy masked array, but my mask is being dropped:

import numpy as np
a = np.ma.array([1, 2, 3, -1, 5], mask=[0, 0, 0, 1, 0])
a[a < 2] = 999

The result is:

masked_array(data = [999 2 3 999 5],
mask = [False False False False False],
fill_value = 999999)

But what I want is:

masked_array(data = [999 2 3 -- 5],
mask = [False False False  True False],
fill_value = 999999)

What am I doing wrong? I'm using Python 2.7 and numpy 1.7.1 on Ubuntu 13.10

This is a long-standing gotcha/design-bug/feature with masked arrays. Basically, beware of assigning using boolean arrays when using masked arrays. A completely different (much cleaner) missing value system was added to numpy a few years back, but has been pulled back out until numpy 2.0 for various reasons. — Joe Kington
– Joe Kington, Commented Nov 13, 2013 at 15:13

jabaldonedo · Accepted Answer · 2013-11-13 15:15:52Z

4

I think you are not doing the substitution correctly, try this:

>>> import numpy as np
>>> a = np.ma.array([1, 2, 3, -1, 5], mask=[0, 0, 0, 1, 0])
>>> a.data[a < 2] = 999
>>> a
 masked_array(data = [999 2 3 -- 5],
         mask = [False False False  True False],
   fill_value = 999999)

answered Nov 13, 2013 at 15:15

jabaldonedo

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1 Comment

jabaldonedo Over a year ago

I have tested it on numpy 1.7.1

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