Fernando Perez wrote: > > On Sat, Jun 6, 2009 at 11:03 AM, Charles R > Harris<charlesr.har...@gmail.com> wrote: > >> I don't think we can change the current matrix class, to do so would >> break >> too much code. It would be nice to extend it with an explicit inner >> product, >> but I can't think of any simple notation for it that python would parse. > > Maybe it's time to make another push on python-dev for the pep-225 > stuff for other operators? > > https://cirl.berkeley.edu/fperez/static/numpy-pep225/ > > Last year I got pretty much zero interest from python-dev on this, but > they were very very busy with 3.0 on the horizon. Perhaps once they > put 3.1 out would be a good time to champion this again. > > It's slightly independent of the matrix class debate, but perhaps > having special operators for real matrix multiplication could ease > some of the bottlenecks of this discussion. > > It would be great if someone could champion that discussion on > python-dev though, I don't see myself finding the time for it another > time around... >
How about pep 211? http://www.python.org/dev/peps/pep-0211/ PEP 211 proposes a single new operator (@) that could be used for matrix multiplication. MATLAB has elementwise versions of multiply, exponentiation, and left and right division using a preceding "." for the usual matrix versions (* ^ \ /). PEP 225 proposes "tilde" versions of + - * / % **. While PEP 225 would allow a matrix exponentiation and right divide, I think these things are much less common than matrix multiply. Plus, I think following through with the PEP 225 implementation would create a frankenstein of a language that would be hard to read. So, I would argue for pushing for a single new operator that can then be used to implement "dot" with a binary infix operator. We can resurrect PEP 211 or start a new PEP or whatever, the main thing is to have a proposal that makes sense. Actually, what do you all think of this: @ --> matrix multiply @@ --> matrix exponentiation and we leave it at that - let's not get too greedy and try for matrix inverse via @/ or something. For the nd array operator, I would propose taking the last dimension of the left array and "collapsing" it with the first dimension of the right array, so shape (a0, ..., aL-1,k) @ (k, b0, ..., bM-1) --> (a0, ..., aL-1, b0, ..., bM-1) Does that make sense? With this proposal, matrices go away and all our lives are sane again. :-) Long live the numpy ndarray! Thanks to the creators for all your hard work BTW - I love this stuff! - Tom K. -- View this message in context: http://www.nabble.com/matrix-default-to-column-vector--tp23652920p23907204.html Sent from the Numpy-discussion mailing list archive at Nabble.com. _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
