On Tue, Dec 15, 2009 at 11:01, Matthew Brett <[email protected]> wrote: > Hi, > > Following on from the occasional discussion on the list, can I propose > a small matrix_rank function for inclusion in numpy/linalg? > > I suggest it because it seems rather a basic need for linear algebra, > and it's very small and simple... > > I've appended an implementation with some doctests in the hope that it > will be acceptable,
I think you need a real example of a nontrivial numerically rank-deficient matrix. Note that c_[eye(4), eye(4)] is actually a full-rank matrix. A matrix is full rank if its numerical rank is equal to min(rows, cols) not max(rows, cols). Taking I=eye(4); I[-1,-1] = 0.0 should be a sufficient example. > Robert - I hope you don't mind me quoting you in the notes. I certainly. However, you do not need to cite me; I'm in the authors list already. On the other hand, you probably shouldn't copy-and-paste anything I write on the mailing list to use in a docstring. On the mailing list, I am answering a particular question and use a different voice than is appropriate for a docstring. Also, a full citation of Golub and Van Loan would be appropriate: .. [1] G. H. Golub and C. F. Van Loan, _Matrix Computations_. Baltimore: Johns Hopkins University Press, 1996. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
