# Copyright (C) 2004   Michael Creel   <michael.creel@uab.es>
# 
# 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 2 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/>. 
# (c) Michael Creel <michael.creel@uab.es>

# battery.m: repeatedly call bfgs using a battery of 
# start values, to attempt to find global min
# of a nonconvex function

# INPUTS:
# func: function to mimimize
# args: args of function
# minarg: argument to minimize w.r.t. (usually = 1)
# startvals: kxp matrix of values to try for sure (don't include all zeros, that's automatic)
# max iters per start value
# number of additional random start values to try

# OUTPUT: theta - the best value found - NOT iterated to convergence
		 
function theta = battery(func, args, minarg, startvals, maxiters)

# setup
[k,trials] = size(startvals);
bestobj = inf;
besttheta = zeros(k,1);
bfgscontrol = {maxiters,0,0,1};
# now try the supplied start values, and optionally the random start values
for i = 1:trials
	args{minarg} = startvals(:,i);
	[theta, obj_value, convergence] = bfgsmin (func, args, bfgscontrol);
	
	if obj_value < bestobj
		besttheta = theta;
		bestobj = obj_value;
	endif
endfor
	
theta = besttheta;
endfunction