On 3/26/07, Alan G Isaac <[EMAIL PROTECTED]> wrote: > > Alan G Isaac schrieb: > >> What feels wrong: iterating over a container does not give > >> access to the contained objects. This is not Pythonic. > > On Mon, 26 Mar 2007, Sven Schreiber apparently wrote: > > If you iterate over the rows of the matrix, it feels > > natural to me to get the row vectors > > Natural in what way? > Again, I am raising the question of what > would be expected from someone familiar with Python. > Abstractly, what do you expect to get when you iterate > over a container? Seriously. > > > > But I admit I'm a 2d fan so much so that I didn't even > > know that using a single index is possible with a matrix. > > Exactly. When you want submatrices, you expect to index for > them. EXACTLY!! > If may chime in... I think Sven's argument in on the side saying, A "matrix" is an object that you expect a certain (mathematical !) behavior from. If some object behaves intuitively right -- that's ultimately pythonic ! The clash is, NOT to see a matrix "just as another container". Instead a matrix is a mathematical object , that has rows and columns. It is used in a field (lin-alg) where every vector is either a row or a column vector -- apparently that's big thing ;-) The whole reason to add a special matrix class to numpy in the first place, is to provide a better degree of convenience to lin-alg related applications. I would argue that it was just not consistently considered, that this should also come with "a column of a matrix is something else than a row -- (1,n) vs. (n,1) and not (n,)
more notes/points: a) I have never heard about the m.A1 - what is it ? b) I don't think that if m[1] would return a (rank 2) matrix, that m[1].A could return a (rank 1) array ... c) I'm curious if there is a unique way to extend the matrix class into 3D or ND. -Sebastian _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion