On 16/04/2008, Anne Archibald <[EMAIL PROTECTED]> wrote: > I don't think of arrays as containers of anything but scalars, so I > find this whole argument from intuition extremely strange.
I see now for the first time that Matrices can't have dims > 2. Grim. I do think that ColumnVector and RowVector could be useful in general; some statements read more clearly, e.g. (for x an (N,)-array) ColumnVector(x) instead of np.c_[x] # turn x into a column vector And, while np.dot(x,x) is valid, RowVector(x) * ColumnVector(x) is clearer than x = np.dot(np.r_[x], np.c_[x]) (which is a pattern I'd expect to find amongst linear algebra users) The last expression also yields array([14]) instead of 14! > My (draconian) suggestion would be to simply raise an exception when a > matrix is indexed with a scalar. They're inherently two-dimensional; > if you want a submatrix you should provide both indices (possibly > including a ":"). If you actually want a subarray, as with an array, > use ".A". Your idea isn't that far out -- but I think we can provide the expected (ndarray-like) behaviour in this case. > That said, I don't actually use matrices, so I don't get a vote. Apparently, neither do I :) But I do get to modify http://www.scipy.org/MatrixIndexing I also changed ProposedEnhancements into a Category page, that automatically accumulates all WikiPages tagged with ProposedEnhancements. Regards Stéfan _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
