Mercurial > hg > octave-nkf
view scripts/linear-algebra/normest.m @ 11542:695141f1c05c ss-3-3-55
snapshot 3.3.55
author | John W. Eaton <jwe@octave.org> |
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date | Sat, 15 Jan 2011 04:53:04 -0500 |
parents | fd0a3ac60b0e |
children | c792872f8942 |
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## Copyright (C) 2006-2011 David Bateman and Marco Caliari ## Copyright (C) 2009 VZLU Prague ## ## 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} {@var{n} =} normest (@var{A}) ## @deftypefnx {Function File} {@var{n} =} normest (@var{A}, @var{tol}) ## @deftypefnx {Function File} {[@var{n}, @var{c}] =} normest (@dots{}) ## Estimate the 2-norm of the matrix @var{A} using a power series ## analysis. This is typically used for large matrices, where the cost ## of calculating @code{norm (@var{A})} is prohibitive and an approximation ## to the 2-norm is acceptable. ## ## @var{tol} is the tolerance to which the 2-norm is calculated. By default ## @var{tol} is 1e-6. @var{c} returns the number of iterations needed for ## @code{normest} to converge. ## @end deftypefn function [n, c] = normest (A, tol = 1e-6) if (nargin != 1 && nargin != 2) print_usage (); endif if (! (isnumeric (A) && ndims (A) == 2)) error ("normest: A must be a numeric 2-D matrix"); endif if (! (isscalar (tol) && isreal (tol))) error ("normest: TOL must be a real scalar"); endif if (! isfloat (A)) A = double (A); endif tol = max (tol, eps (class (A))); ## Set random number generator to depend on target matrix v = rand ("state"); rand ("state", trace (A)); ncols = columns (A); ## Randomize y to avoid bad guesses for important matrices. y = rand (ncols, 1); c = 0; n = 0; do n0 = n; x = A * y; normx = norm (x); if (normx == 0) x = rand (ncols, 1); else x = x / normx; endif y = A' * x; n = norm (y); c += 1; until (abs (n - n0) <= tol * n) rand ("state", v); # restore state of random number generator endfunction %!test %! A = toeplitz ([-2,1,0,0]); %! assert (normest(A), norm(A), 1e-6); %!test %! A = rand (10); %! assert (normest(A), norm(A), 1e-6); %% Test input validation %!error normest () %!error normest (1, 2, 3) %!error normest ([true true]) %!error normest (ones (3,3,3)) %!error normest (1, [1, 2]) %!error normest (1, 1+1i)