[Numpy-discussion] Strange behavior in setting masked array values in Numpy 1.1.0
Tony Yu
tsyu80@gmail....
Sat May 31 16:56:20 CDT 2008
Great job getting numpy 1.1.0 out and thanks for including the old API
of masked arrays.
I've been playing around with some software using numpy 1.0.4 and took
a crack at upgrading it to numpy 1.1.0, but I ran into some strange
behavior when assigning to slices of a masked array.
I made the simplest example I could think of to show this weird
behavior. Basically, reordering the masked array and assigning back to
itself *on the same line* seems to work for part of the array, but
other parts are left unchanged. In the example below, half of the
array is assigned "properly" and the other half isn't. This problem is
eliminated if the assignment is done with a copy of the array.
Alternatively, this problem is eliminated if I using
numpy.oldnumeric.ma.masked_array instead of the new masked array
implementation.
Is this just a problem on my setup?
Thanks in advance for your help.
-Tony Yu
Example:
========
In [1]: import numpy
In [2]: masked = numpy.ma.masked_array([[1, 2, 3, 4, 5]], mask=False)
In [3]: masked[:] = numpy.fliplr(masked.copy())
In [4]: print masked
[[5 4 3 2 1]]
In [5]: masked[:] = numpy.fliplr(masked)
In [6]: print masked
[[1 2 3 2 1]]
Specs:
======
Numpy 1.1.0
Python 2.5.1
OS X Leopard 10.5.3
More information about the Numpy-discussion
mailing list