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comparison scripts/optimization/lsqnonneg.m @ 14787:acb09716fc94

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lsqnonneg have tolerance option for convergence (bug #33347)
author Axel Mathéi <axel.mathei@gmail.com>
date Thu, 21 Jun 2012 12:15:38 +0200
parents b76f0740940e
children 5d3a684236b0
comparison
equal deleted inserted replaced
14786:e70a0c9cada6 14787:acb09716fc94
19 ## <http://www.gnu.org/licenses/>. 19 ## <http://www.gnu.org/licenses/>.
20 20
21 ## -*- texinfo -*- 21 ## -*- texinfo -*-
22 ## @deftypefn {Function File} {@var{x} =} lsqnonneg (@var{c}, @var{d}) 22 ## @deftypefn {Function File} {@var{x} =} lsqnonneg (@var{c}, @var{d})
23 ## @deftypefnx {Function File} {@var{x} =} lsqnonneg (@var{c}, @var{d}, @var{x0}) 23 ## @deftypefnx {Function File} {@var{x} =} lsqnonneg (@var{c}, @var{d}, @var{x0})
24 ## @deftypefnx {Function File} {@var{x} =} lsqnonneg (@var{c}, @var{d}, @var{x0}, @var{options})
24 ## @deftypefnx {Function File} {[@var{x}, @var{resnorm}] =} lsqnonneg (@dots{}) 25 ## @deftypefnx {Function File} {[@var{x}, @var{resnorm}] =} lsqnonneg (@dots{})
25 ## @deftypefnx {Function File} {[@var{x}, @var{resnorm}, @var{residual}] =} lsqnonneg (@dots{}) 26 ## @deftypefnx {Function File} {[@var{x}, @var{resnorm}, @var{residual}] =} lsqnonneg (@dots{})
26 ## @deftypefnx {Function File} {[@var{x}, @var{resnorm}, @var{residual}, @var{exitflag}] =} lsqnonneg (@dots{}) 27 ## @deftypefnx {Function File} {[@var{x}, @var{resnorm}, @var{residual}, @var{exitflag}] =} lsqnonneg (@dots{})
27 ## @deftypefnx {Function File} {[@var{x}, @var{resnorm}, @var{residual}, @var{exitflag}, @var{output}] =} lsqnonneg (@dots{}) 28 ## @deftypefnx {Function File} {[@var{x}, @var{resnorm}, @var{residual}, @var{exitflag}, @var{output}] =} lsqnonneg (@dots{})
28 ## @deftypefnx {Function File} {[@var{x}, @var{resnorm}, @var{residual}, @var{exitflag}, @var{output}, @var{lambda}] =} lsqnonneg (@dots{}) 29 ## @deftypefnx {Function File} {[@var{x}, @var{resnorm}, @var{residual}, @var{exitflag}, @var{output}, @var{lambda}] =} lsqnonneg (@dots{})
29 ## Minimize @code{norm (@var{c}*@var{x} - d)} subject to 30 ## Minimize @code{norm (@var{c}*@var{x} - d)} subject to
30 ## @code{@var{x} >= 0}. @var{c} and @var{d} must be real. @var{x0} is an 31 ## @code{@var{x} >= 0}. @var{c} and @var{d} must be real. @var{x0} is an
31 ## optional initial guess for @var{x}. 32 ## optional initial guess for @var{x}.
33 ## Currently, @code{lsqnonneg}
34 ## recognizes these options: @code{"MaxIter"}, @code{"TolX"}.
35 ## For a description of these options, see @ref{doc-optimset,,optimset}.
32 ## 36 ##
33 ## Outputs: 37 ## Outputs:
34 ## 38 ##
35 ## @itemize @bullet 39 ## @itemize @bullet
36 ## @item resnorm 40 ## @item resnorm
145 endwhile 149 endwhile
146 150
147 ## compute the gradient. 151 ## compute the gradient.
148 w = c'*(d - c*x); 152 w = c'*(d - c*x);
149 w(p) = []; 153 w(p) = [];
150 if (! any (w > 0)) 154 tolx = optimget (options, "TolX", 10*eps*norm (c, 1)*length (c));
155 if (! any (w > tolx))
151 if (useqr) 156 if (useqr)
152 ## verify the solution achieved using qr updating. 157 ## verify the solution achieved using qr updating.
153 ## in the best case, this should only take a single step. 158 ## in the best case, this should only take a single step.
154 useqr = false; 159 useqr = false;
155 continue; 160 continue;