On Sat, Apr 26, 2008 at 02:01:45PM -0400, Alan G Isaac wrote: > >>> A > matrix([[1, 2], > [ 3, 4]]) > >>> A = np.mat(x) > >>> for row in A: > ... for col in row: > ... print col > ... > [[1 2]] > [[3 4]]
> So are you saying that one should not be able to iterate > through to the elements of a matrix? I kinda expect this was the real issue. I think the only way to get consistent behavior for such code is either * to use a syntax similar to dictionnaries: for row in A.rows(): for col in row.cols() I actually think this is much better than the code you currently use, * or implement row and column objects. The problem in your code is that you do not distinguish iterating over rows and columns, and in linear algebra these are different objects. The two solutions I propose do this distinction. My favorite one is the first one (the rows and cols methods). Cheers, Gaƫl _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion