On May 31, 2008, at 6:04 PM, Matthieu Brucher wrote:
Hi,
This is to be expected. You are trying to modify and read the same
array at the same time, which should never be done.
Thanks, I'll have to keep this in mind next time.
So, what's the best way to rearrange a subarray of an array. Copying
seems inefficient.
-Tony
Matthieu
2008/5/31 Tony Yu <[EMAIL PROTECTED]>:
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
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French PhD student
Website : http://matthieu-brucher.developpez.com/
Blogs : http://matt.eifelle.com and http://blog.developpez.com/?
blog=92
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