Mercurial > hg > octave-lyh
view scripts/linear-algebra/cond.m @ 17435:15d592c82abc
test: Add test for bug #40036 to axis.m
* scripts/plot/axis.m: Add test for bug #40036 to axis.
author | Rik <rik@octave.org> |
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date | Mon, 16 Sep 2013 09:38:06 -0700 |
parents | c3bd7314643c |
children |
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## Copyright (C) 1993-2012 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} {} cond (@var{A}) ## @deftypefnx {Function File} {} cond (@var{A}, @var{p}) ## Compute the @var{p}-norm condition number of a matrix. ## ## @code{cond (@var{A})} is defined as ## @tex ## $ {\parallel A \parallel_p * \parallel A^{-1} \parallel_p .} $ ## @end tex ## @ifnottex ## @code{norm (@var{A}, @var{p}) * norm (inv (@var{A}), @var{p})}. ## @end ifnottex ## ## By default, @code{@var{p} = 2} is used which implies a (relatively slow) ## singular value decomposition. Other possible selections are ## @code{@var{p} = 1, Inf, "fro"} which are generally faster. See ## @code{norm} for a full discussion of possible @var{p} values. ## ## The condition number of a matrix quantifies the sensitivity of the matrix ## inversion operation when small changes are made to matrix elements. Ideally ## the condition number will be close to 1. When the number is large this ## indicates small changes (such as underflow or round-off error) will produce ## large changes in the resulting output. In such cases the solution results ## from numerical computing are not likely to be accurate. ## @seealso{condest, rcond, norm, svd} ## @end deftypefn ## Author: jwe function retval = cond (A, p = 2) if (nargin < 1 || nargin > 2) print_usage (); endif if (ndims (A) > 2) error ("cond: A must be a 2-D matrix"); endif if (p == 2) if (isempty (A)) retval = 0.0; elseif (any (! isfinite (A(:)))) error ("cond: A must not contain Inf or NaN values"); else sigma = svd (A); sigma_1 = sigma(1); sigma_n = sigma(end); if (sigma_1 == 0 || sigma_n == 0) retval = Inf; else retval = sigma_1 / sigma_n; endif endif else retval = norm (A, p) * norm (inv (A), p); endif endfunction %!test %! y = [7, 2, 3; 1, 3, 4; 6, 4, 5]; %! tol = 1e-6; %! type = {1, 2, "fro", "inf", inf}; %! for n = 1:numel (type) %! rcondition(n) = 1 / cond (y, type{n}); %! endfor %! assert (rcondition, [0.017460, 0.019597, 0.018714, 0.012022, 0.012022], tol); %!assert (cond ([1, 2; 2, 1]), 3, sqrt (eps)) %!assert (cond ([1, 2, 3; 4, 5, 6; 7, 8, 9]) > 1.0e+16) %!error cond () %!error cond (1, 2, 3) %!error <A must be a 2-D matrix> cond (ones (1,3,3)) %!error <A must not contain Inf or NaN value> cond ([1, 2;Inf 4]) %!error <A must not contain Inf or NaN value> cond ([1, 2;NaN 4])