Hi, On Sat, Jun 25, 2011 at 12:22 AM, Wes McKinney <[email protected]> wrote: ... > Perhaps we should make a wiki page someplace summarizing pros and cons > of the various implementation approaches?
But - we should do this if it really is an open question which one we go for. If not then, we're just slowing Mark down in getting to the implementation. Assuming the question is still open, here's a starter for the pros and cons: array.mask 1) It's easier / neater to implement 2) It can generalize across dtypes 3) You can still get the masked data underneath the mask (allowing you to unmask etc) nafloat64: 1) No memory overhead 2) Battle-tested implementation already done in R I guess we'd have to test directly whether the non-continuous memory of the mask and data would cause enough cache-miss problems to outweigh the potential cycle-savings from single byte comparisons in array.mask. I guess that one and only one of these will get written. I guess that one of these choices may be a lot more satisfying to the current and future masked array itch than the other. I'm personally worried that the memory overhead of array.masks will make many of us tend to avoid them. I work with images that can easily get large enough that I would not want an array-items size byte array added to my storage. The reason I'm asking for more details about the implementation is because that is most of the argument for array.mask at the moment (1 and 2 above). See you, Matthew _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
