Mercurial > octave
view scripts/linear-algebra/condeig.m @ 30564:796f54d4ddbf stable
update Octave Project Developers copyright for the new year
In files that have the "Octave Project Developers" copyright notice,
update for 2021.
In all .txi and .texi files except gpl.txi and gpl.texi in the
doc/liboctave and doc/interpreter directories, change the copyright
to "Octave Project Developers", the same as used for other source
files. Update copyright notices for 2022 (not done since 2019). For
gpl.txi and gpl.texi, change the copyright notice to be "Free Software
Foundation, Inc." and leave the date at 2007 only because this file
only contains the text of the GPL, not anything created by the Octave
Project Developers.
Add Paul Thomas to contributors.in.
author | John W. Eaton <jwe@octave.org> |
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date | Tue, 28 Dec 2021 18:22:40 -0500 |
parents | 7854d5752dd2 |
children | 597f3ee61a48 |
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######################################################################## ## ## Copyright (C) 2006-2022 The Octave Project Developers ## ## See the file COPYRIGHT.md in the top-level directory of this ## distribution or <https://octave.org/copyright/>. ## ## 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 ## <https://www.gnu.org/licenses/>. ## ######################################################################## ## -*- texinfo -*- ## @deftypefn {} {@var{c} =} condeig (@var{a}) ## @deftypefnx {} {[@var{v}, @var{lambda}, @var{c}] =} condeig (@var{a}) ## Compute condition numbers of a matrix with respect to eigenvalues. ## ## The condition numbers are the reciprocals of the cosines of the angles ## between the left and right eigenvectors; Large values indicate that the ## matrix has multiple distinct eigenvalues. ## ## The input @var{a} must be a square numeric matrix. ## ## The outputs are: ## ## @itemize @bullet ## @item ## @var{c} is a vector of condition numbers for the eigenvalues of ## @var{a}. ## ## @item ## @var{v} is the matrix of right eigenvectors of @var{a}. The result is ## equivalent to calling @code{[@var{v}, @var{lambda}] = eig (@var{a})}. ## ## @item ## @var{lambda} is the diagonal matrix of eigenvalues of @var{a}. The ## result is equivalent to calling ## @code{[@var{v}, @var{lambda}] = eig (@var{a})}. ## @end itemize ## ## Example ## ## @example ## @group ## a = [1, 2; 3, 4]; ## c = condeig (a) ## @result{} c = ## 1.0150 ## 1.0150 ## @end group ## @end example ## @seealso{eig, cond, balance} ## @end deftypefn function [v, lambda, c] = condeig (a) if (nargin < 1) print_usage (); endif if (! (isnumeric (a) && issquare (a))) error ("condeig: A must be a square numeric matrix"); endif if (issparse (a) && nargout <= 1) ## Try to use svds to calculate the condition number as it will typically ## be much faster than calling eig as only the smallest and largest ## eigenvalue are calculated. ## FIXME: This calculates one condition number for the entire matrix. ## In the full case, separate condition numbers are calculated for every ## eigenvalue. try s0 = svds (a, 1, 0); # min eigenvalue v = svds (a, 1) / s0; # max eigenvalue catch ## Caught an error as there is a singular value exactly at zero!! v = Inf; end_try_catch return; endif ## Right eigenvectors [v, lambda] = eig (a); if (isempty (a)) c = []; else ## Corresponding left eigenvectors ## Use 2-argument form to suppress possible singular matrix warning. [vl, ~] = inv (v); vl = vl'; ## Normalize vectors vl ./= repmat (sqrt (sum (abs (vl .^ 2))), rows (vl), 1); ## Condition numbers ## Definition: cos (angle) = (norm (v1) * norm (v2)) / dot (v1, v2) ## Eigenvectors have been normalized so 'norm (v1) * norm (v2)' = 1 c = abs (1 ./ dot (vl, v)'); endif if (nargout <= 1) v = c; endif endfunction %!test %! a = [1, 2; 3, 4]; %! c = condeig (a); %! expected_c = [1.0150; 1.0150]; %! assert (c, expected_c, 0.001); %!test %! a = [1, 3; 5, 8]; %! [v, lambda, c] = condeig (a); %! [expected_v, expected_lambda] = eig (a); %! expected_c = [1.0182; 1.0182]; %! assert (v, expected_v, 0.001); %! assert (lambda, expected_lambda, 0.001); %! assert (c, expected_c, 0.001); ## Test empty input %!assert (condeig ([]), []) ## Test input validation %!error <Invalid call> condeig () %!error <A must be a square numeric matrix> condeig ({1}) %!error <A must be a square numeric matrix> condeig (ones (3,2)) %!error <A must be a square numeric matrix> condeig (ones (2,2,2))