On May 2, 2012, at 10:03 PM, Stéfan van der Walt wrote: > On Wed, May 2, 2012 at 6:25 PM, Travis Oliphant <[email protected]> wrote: >> The only new principle (which is not strictly new --- but new to NumPy's >> world-view) is using one (or more) fields of a structured array as >> "synthetic dimensions" which replace 1 or more of the raw table dimensions. > > Ah, thanks--that's the detail I was missing. I wonder if the > contiguity requirement will hamper us here, though. E.g., I could > imagine that some tree structure might be more suitable to storing and > organizing indices, and for large arrays we wouldn't like to make a > copy for each operation. I guess we can't wait for discontiguous > arrays to come along, though :)
Actually, it's better to keep the actual data together as much as possible, I think, and simulate a tree structure with a layer on top --- i.e. an index. Different algorithms will prefer different orderings of the underlying data just as today different algorithms prefer different striding patterns on the standard, strided view of a dense array. -Travis > >> More to come.... If you are interested in this sort of thing please let me >> know.... > > Definitely--if we can optimize this machinery it will be beneficial to > scipy.sparse as well. > > Stéfan > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
