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.
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 > > _______________________________________________ > Numpy-discussion mailing list > [email protected] > http://projects.scipy.org/mailman/listinfo/numpy-discussion > -- French PhD student Website : http://matthieu-brucher.developpez.com/ Blogs : http://matt.eifelle.com and http://blog.developpez.com/?blog=92 LinkedIn : http://www.linkedin.com/in/matthieubrucher
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