On 6/5/2009 3:49 PM Stéfan van der Walt apparently wrote: > If the Matrix class is to remain, we need to take the steps > necessary to integrate it into NumPy properly.
I think this requires a list of current problems. Many of the problems for NumPy have been addressed over time. I believe the remaining problems center more on SciPy rather than NumPy. This requires that users report difficulties. For example, Jason Rennie says he ran into problems with scipy.optimize.fmin_cg, although I do not recall him reporting these (I do recall an optimization problem he reported using ndarrays). Has he filed a bug report detailing his problem? > To get going we'll need a list of changes required (i.e. "in an ideal > world, how would matrices work?"). The key anomaly concerning matrices comes with indexing. See the introduction here: http://www.scipy.org/MatrixIndexing However changing this for the current matrix object was rejected in the last (exhausting) go round. > There should be a set protocol for > all numpy functions that guarantees compatibility with ndarrays, > matrices and other derived classes. My impression was that this was resolved as follows: handle all ndarray based objects as arrays (using asarray) in any NumPy function, but return the subclass when possible. (E.g., using asmatrix, return a matrix output for a matrix input.) This seems fine to me. > Being one of the most vocal proponents of the Matrix class, would you > be prepared to develop your Matrix Proposal at > http://scipy.org/NewMatrixSpec further? I consider my proposal to have the following status: rejected. I consider the core reason to be: creates a backwards incompatibility. That was a very long and exhausting discussion that was productive in laying out the issues, but I do not think we can progress in that direction. The existing matrix object is very usable. It's primary problem is some indexing anomalies, http://www.scipy.org/MatrixIndexing and not everyone saw those as problems. In terms of NumPy functions, I think the asarray/asmatrix protocol fits the bill. (Altho perhaps I am overlooking something as a user that is obvious to a developer.) Cheers, Alan _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
