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 Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion