Mercurial > hg > octave-lyh
view scripts/linear-algebra/rank.m @ 13097:52e4aa30d5b2
logm.m: Return real matrix when all eigenvalues are real (Bug #32121).
* logm.m: Remove complex numbers of order eps() which may have entered
return value through numeric roundoff.
author | Rik <octave@nomad.inbox5.com> |
---|---|
date | Sun, 04 Sep 2011 16:46:16 -0700 |
parents | 8c4605b4d0c8 |
children | e81ddf9cacd5 |
line wrap: on
line source
## Copyright (C) 1993-2011 John W. Eaton ## ## This file is part of Octave. ## ## Octave is free software; you can redistribute it and/or modify it ## under the terms of the GNU General Public License as published by ## the Free Software Foundation; either version 3 of the License, or (at ## your option) any later version. ## ## Octave is distributed in the hope that it will be useful, but ## WITHOUT ANY WARRANTY; without even the implied warranty of ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU ## General Public License for more details. ## ## You should have received a copy of the GNU General Public License ## along with Octave; see the file COPYING. If not, see ## <http://www.gnu.org/licenses/>. ## -*- texinfo -*- ## @deftypefn {Function File} {} rank (@var{A}) ## @deftypefnx {Function File} {} rank (@var{A}, @var{tol}) ## Compute the rank of @var{A}, using the singular value decomposition. ## The rank is taken to be the number of singular values of @var{A} that ## are greater than the specified tolerance @var{tol}. If the second ## argument is omitted, it is taken to be ## ## @example ## tol = max (size (@var{A})) * sigma(1) * eps; ## @end example ## ## @noindent ## where @code{eps} is machine precision and @code{sigma(1)} is the largest ## singular value of @var{A}. ## @end deftypefn ## Author: jwe function retval = rank (A, tol) if (nargin == 1) sigma = svd (A); if (isempty (sigma)) tolerance = 0; else if (isa (A, "single")) tolerance = max (size (A)) * sigma (1) * eps ("single"); else tolerance = max (size (A)) * sigma (1) * eps; endif endif elseif (nargin == 2) sigma = svd (A); tolerance = tol; else print_usage (); endif retval = sum (sigma > tolerance); endfunction %!test %! A = [1 2 3 4 5 6 7; %! 4 5 6 7 8 9 12; %! 1 2 3.1 4 5 6 7; %! 2 3 4 5 6 7 8; %! 3 4 5 6 7 8 9; %! 4 5 6 7 8 9 10; %! 5 6 7 8 9 10 11]; %! assert(rank(A),4); %!test %! A = [1 2 3 4 5 6 7; %! 4 5 6 7 8 9 12; %! 1 2 3.0000001 4 5 6 7; %! 4 5 6 7 8 9 12.00001; %! 3 4 5 6 7 8 9; %! 4 5 6 7 8 9 10; %! 5 6 7 8 9 10 11]; %! assert(rank(A),4); %!test %! A = [1 2 3 4 5 6 7; %! 4 5 6 7 8 9 12; %! 1 2 3 4 5 6 7; %! 4 5 6 7 8 9 12.00001; %! 3 4 5 6 7 8 9; %! 4 5 6 7 8 9 10; %! 5 6 7 8 9 10 11]; %! assert(rank(A),3); %!test %! A = [1 2 3 4 5 6 7; %! 4 5 6 7 8 9 12; %! 1 2 3 4 5 6 7; %! 4 5 6 7 8 9 12; %! 3 4 5 6 7 8 9; %! 4 5 6 7 8 9 10; %! 5 6 7 8 9 10 11]; %! assert(rank(A),3); %!test %! A = eye(100); %! assert(rank(A),100); %!test %! A = [1, 2, 3; 1, 2.001, 3; 1, 2, 3.0000001]; %! assert(rank(A),3) %! assert(rank(A,0.0009),1) %! assert(rank(A,0.0006),2) %! assert(rank(A,0.00000002),3)