On Wed, May 2, 2012 at 3:20 PM, Francesc Alted <franc...@continuum.io> wrote: > On 5/2/12 4:07 PM, Stéfan van der Walt wrote: > Well, as the OP said, coo_matrix does not support dimensions larger than > 2, right?
That's just an implementation detail, I would imagine--I'm trying to figure out if there is a new principle behind "synthetic dimensions"? By the way, David Cournapeau mentioned using b-trees for sparse ops a while ago; did you ever talk to him about those ideas? BTW, this coo-type storage is used in Stanford's probabilistic graphical models course, but for dense data (like we have in the course) it's a pain. Writing code in both Octave and Python, I again came to realize what a very elegant N-dimensional structure the numpy array exposes! Stéfan _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
