2009/12/23 David Warde-Farley <d...@cs.toronto.edu>: > On 23-Dec-09, at 10:34 AM, Anne Archibald wrote: > >> The key idea would be that the "linear >> algebra dimensions" would always be the last one(s); this is fairly >> easy to arrange with rollaxis when it isn't already true, would tend >> to reduce copying on input to LAPACK, and is what the gufunc API >> wants. > > Would it actually reduce copying if you were using default C-ordered > arrays? Maybe I'm mistaken but I thought one almost always had to copy > in order to translate C to Fortran order except for a few functions > that can take row-ordered stuff.
That's a good point. But even if you need to do a transpose, it'll be faster to transpose data in a contiguous block than data scattered all over memory. Maybe more to the point, broadcasting adds axes to the beginning, so that (say) two-dimensional arrays can act as "matrix scalars". Anne _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
