// Copyright (C) 2004 Michael Creel // // 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, write to the Free Software // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA // bisection step, for use by minimization algorithms // // returns optimal stepsize using bisection - first until an improvement // is found, then until there is no further improvement // // since this is not for use by end-users, its documentation // is a bit short. See bfgsmin for an example of use // args are // f: string: function name // f_args: cell array: arguments of function // dx: vector: the direction of search // minarg: integer: (optional) the arg we are minimizing w.r.t. #include #include #include #include #include static bool any_bad_argument(const octave_value_list& args) { if (!args(0).is_string()) { error("bisectionstep: first argument must be string holding objective function name"); return true; } if (!args(1).is_cell()) { error("bisectionstep: second argument must cell array of function arguments"); return true; } if (!(args(2).is_real_matrix() || args(2).is_real_scalar())) { error("bisectionstep: third argument must be column vector of directions"); return true; } if ((args(2).is_real_matrix()) && (args(2).columns() != 1)) { error("bisectionstep: third argument must be column vector of directions"); return true; } if (args.length() == 4) { int tmp = args(3).int_value(); if (error_state) { error("bisectionstep: 4th argument, if supplied, must be an integer scalar"); return true; } if ((tmp > args(1).length()|| tmp < 1)) { error("bisectionstep: 4th argument must be a positive integer that indicates \n\ which of the elements of the second argument is the one minimization is over"); return true; } } return false; } DEFUN_DLD(bisectionstep, args, , "bisectionstep.cc - for internal use by bfgsmin and related functions") { int nargin = args.length (); if ((nargin < 3) || (nargin > 4)) { error("bisectionstep: you must supply 3 or 4 arguments"); return octave_value_list(); } // check the arguments if (any_bad_argument(args)) return octave_value_list(); std::string f (args(0).string_value()); Cell f_args (args(1).cell_value()); ColumnVector dx (args(2).column_vector_value()); double obj_0, obj, a; octave_value_list f_return; octave_value_list c_args(2,1); // for cellevall {f, f_args} octave_value_list stepobj(2,1); int minarg, found_improvement; // Default values for controls minarg = 1; // by default, first arg is one over which we minimize // possibly minimization not over 1st arg if (args.length() == 4) minarg = args(3).int_value(); ColumnVector x (f_args(minarg - 1).column_vector_value()); ColumnVector x_in = x; // possibly function returns a cell array // obj. value will be in first position c_args(0) = f; c_args(1) = f_args; f_return = feval("celleval", c_args); obj_0 = f_return(0).double_value(); a = 1.0; found_improvement = 0; // this first loop goes until an improvement is found while (a > 2*DBL_EPSILON) // limit iterations { f_args(minarg - 1) = x + a*dx; c_args(1) = f_args; f_return = feval("celleval", c_args); obj = f_return(0).double_value(); // reduce stepsize if worse, or if function can't be evaluated if ((obj >= obj_0) || lo_ieee_isnan(obj)) a = 0.5 * a; else { obj_0 = obj; found_improvement = 1; break; } } // If unable to find any improvement break out with stepsize zero if (!found_improvement) { stepobj(0) = 0.0; stepobj(1) = obj_0; return octave_value_list(stepobj); } // now keep going until we no longer improve, or reach max trials while (a > 2*DBL_EPSILON) { a = 0.5*a; f_args(minarg - 1) = x + a*dx; c_args(1) = f_args; f_return = feval("celleval", c_args); obj = f_return(0).double_value(); // if improved, record new best and try another step if ((obj < obj_0) & !lo_ieee_isnan(obj)) obj_0 = obj; else { a = a / 0.5; // put it back to best found break; } } stepobj(0) = a; stepobj(1) = obj_0; return octave_value_list(stepobj); }