--- /dev/null
+## Copyright (C) 2011 Nir Krakauer <nkrakauer@ccny.cuny.edu>
+##
+## This program 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.
+##
+## This program 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
+## this program; if not, see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} [@var{p}, @var{obj_value}, @var{convergence}, @var{iters}, @var{nevs}] = powell (@var{f}, @var{p0}, @var{control})
+## Multidimensional minimization (direction-set method). Implements a direction-set (Powell's) method for multidimensional minimization of a function without calculation of the gradient [1, 2]
+##
+## @subheading Arguments
+##
+## @itemize @bullet
+## @item
+## @var{f}: name of function to minimize (string or handle), which should accept one input variable (see example for how to pass on additional input arguments)
+##
+## @item
+## @var{p0}: An initial value of the function argument to minimize
+##
+## @item
+## @var{options}: an optional structure, which can be generated by optimset, with some or all of the following fields:
+## @itemize @minus
+## @item
+## MaxIter: maximum iterations (positive integer, or -1 or Inf for unlimited (default))
+## @item
+## TolFun: minimum amount by which function value must decrease in each iteration to continue (default is 1E-8)
+## @item
+## MaxFunEvals: maximum function evaluations (positive integer, or -1 or Inf for unlimited (default))
+## @item
+## SearchDirections: an n*n matrix whose columns contain the initial set of (presumably orthogonal) directions to minimize along, where n is the number of elements in the argument to be minimized for; or an n*1 vector of magnitudes for the initial directions (defaults to the set of unit direction vectors)
+## @end itemize
+## @end itemize
+##
+## @subheading Examples
+##
+## @example
+## @group
+## y = @@(x, s) x(1) ^ 2 + x(2) ^ 2 + s;
+## o = optimset('MaxIter', 100, 'TolFun', 1E-10);
+## s = 1;
+## [x_optim, y_min, conv, iters, nevs] = powell(@@(x) y(x, s), [1 0.5], o); %pass y wrapped in an anonymous function so that all other arguments to y, which are held constant, are set
+## %should return something like x_optim = [4E-14 3E-14], y_min = 1, conv = 1, iters = 2, nevs = 24
+## @end group
+##
+## @end example
+##
+## @subheading Returns:
+##
+## @itemize @bullet
+## @item
+## @var{p}: the minimizing value of the function argument
+## @item
+## @var{obj_value}: the value of @var{f}() at @var{p}
+## @item
+## @var{convergence}: 1 if normal convergence, 0 if not
+## @item
+## @var{iters}: number of iterations performed
+## @item
+## @var{nevs}: number of function evaluations
+## @end itemize
+##
+## @subheading References
+##
+## @enumerate
+## @item
+## Powell MJD (1964), An efficient method for finding the minimum of a function of several variables without calculating derivatives, @cite{Computer Journal}, 7 :155-162
+##
+## @item
+## Press, WH; Teukolsky, SA; Vetterling, WT; Flannery, BP (1992). @cite{Numerical Recipes in Fortran: The Art of Scientific Computing} (2nd Ed.). New York: Cambridge University Press (Section 10.5)
+## @end enumerate
+## @end deftypefn
+
+## PKG_ADD: __all_opts__ ("powell");
+
+function [p, obj_value, convergence, iters, nevs] = powell (f, p0, options);
+
+ if (nargin == 1 && ischar (f) && strcmp (f, "defaults"))
+ p = optimset ("MaxIter", Inf, \
+ "TolFun", 1e-8, \
+ "MaxFunEvals", Inf, \
+ "SearchDirections", []);
+ return;
+ endif
+
+ ## check number of arguments
+ if ((nargin < 2) || (nargin > 3))
+ usage('powell: you must supply 2 or 3 arguments');
+ endif
+
+
+ ## default or input values
+
+ if (nargin < 3)
+ options = struct ();
+ endif
+
+ xi_set = 0;
+ xi = optimget (options, 'SearchDirections');
+ if (! isempty (xi))
+ if (isvector (xi)) # assume that xi is is n*1 or 1*n
+ xi = diag (x);
+ endif
+ xi_set = 1;
+ endif
+
+
+ MaxIter = optimget (options, 'MaxIter', Inf);
+ if (MaxIter < 0) MaxIter = Inf; endif
+ MaxFunEvals = optimget (options, 'MaxFunEvals', Inf);
+ TolFun = optimget (options, 'TolFun', 1E-8);
+
+ nevs = 0;
+ iters = 0;
+ convergence = 0;
+
+ p = p0; # initial value of the argument being minimized
+
+ try
+ obj_value = f(p);
+ catch
+ error ("function does not exist or cannot be evaluated");
+ end_try_catch
+
+ nevs++;
+
+ n = numel (p); # number of dimensions to minimize over
+
+ xit = zeros (n, 1);
+ if (! xi_set)
+ xi = eye(n);
+ endif
+
+
+
+ ## do an iteration
+ while (iters <= MaxIter && nevs <= MaxFunEvals && ! convergence)
+ iters++;
+ pt = p; # best point as iteration begins
+ fp = obj_value; # value of the objective function as iteration begins
+ ibig = 0; # will hold direction along which the objective function decreased the most in this iteration
+ dlt = 0; # will hold decrease in objective function value in this iteration
+ for i = 1:n
+ xit = reshape (xi(:, i), size(p));
+ fptt = obj_value;
+ [a, obj_value, nev] = line_min (f, xit, {p});
+ nevs = nevs + nev;
+ p = p + a*xit;
+ change = fptt - obj_value;
+ if (change > dlt)
+ dlt = change;
+ ibig = i;
+ endif
+ endfor
+
+ if ( 2*abs(fp-obj_value) <= TolFun*(abs(fp) + abs(obj_value)) )
+ convergence = 1;
+ return
+ endif
+
+ if (iters == MaxIter)
+ disp ("iteration maximum exceeded");
+ return
+ endif
+
+ ## attempt parabolic extrapolation
+ ptt = 2*p - pt;
+ xit = p - pt;
+ fptt = f(ptt);
+ nevs++;
+ if (fptt < fp) # check whether the extrapolation actually makes the objective function smaller
+ t = 2 * (fp - 2*obj_value + fptt) * (fp-obj_value-dlt)^2 - dlt * (fp-fptt)^2;
+ if (t < 0)
+ p = ptt;
+ [a, obj_value, nev] = line_min (f, xit, {p});
+ nevs = nevs + nev;
+ p = p + a*xit;
+
+ ## add the net direction from this iteration to the direction set
+ xi(:, ibig) = xi(:, n);
+ xi(:, n) = xit(:);
+ endif
+ endif
+ endwhile
+