annotate scripts/optimization/fminunc.m @ 26376:00f796120a6d stable

maint: Update copyright dates in all source files.
author John W. Eaton <jwe@octave.org>
date Wed, 02 Jan 2019 16:32:43 -0500
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1 ## Copyright (C) 2008-2019 VZLU Prague, a.s.
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2 ##
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3 ## This file is part of Octave.
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4 ##
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5 ## Octave is free software: you can redistribute it and/or modify it
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6 ## under the terms of the GNU General Public License as published by
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7 ## the Free Software Foundation, either version 3 of the License, or
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8 ## (at your option) any later version.
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9 ##
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10 ## Octave is distributed in the hope that it will be useful, but
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11 ## WITHOUT ANY WARRANTY; without even the implied warranty of
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12 ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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13 ## GNU General Public License for more details.
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14 ##
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15 ## You should have received a copy of the GNU General Public License
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16 ## along with Octave; see the file COPYING. If not, see
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17 ## <https://www.gnu.org/licenses/>.
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18 ##
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19 ## Author: Jaroslav Hajek <highegg@gmail.com>
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20
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21 ## -*- texinfo -*-
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22 ## @deftypefn {} {} fminunc (@var{fcn}, @var{x0})
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23 ## @deftypefnx {} {} fminunc (@var{fcn}, @var{x0}, @var{options})
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24 ## @deftypefnx {} {[@var{x}, @var{fval}, @var{info}, @var{output}, @var{grad}, @var{hess}] =} fminunc (@var{fcn}, @dots{})
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25 ## Solve an unconstrained optimization problem defined by the function
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26 ## @var{fcn}.
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27 ##
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28 ## @var{fcn} should accept a vector (array) defining the unknown variables, and
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29 ## return the objective function value, optionally with gradient.
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30 ## @code{fminunc} attempts to determine a vector @var{x} such that
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31 ## @code{@var{fcn} (@var{x})} is a local minimum.
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32 ##
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33 ## @var{x0} determines a starting guess. The shape of @var{x0} is preserved in
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34 ## all calls to @var{fcn}, but otherwise is treated as a column vector.
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35 ##
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36 ## @var{options} is a structure specifying additional parameters which
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37 ## control the algorithm. Currently, @code{fminunc} recognizes these options:
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38 ## @qcode{"AutoScaling"}, @qcode{"FinDiffType"}, @qcode{"FunValCheck"},
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39 ## @qcode{"GradObj"}, @qcode{"MaxFunEvals"}, @qcode{"MaxIter"},
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40 ## @qcode{"OutputFcn"}, @qcode{"TolFun"}, @qcode{"TolX"}, @qcode{"TypicalX"}.
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41 ##
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42 ## If @qcode{"AutoScaling"} is @qcode{"on"}, the variables will be
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43 ## automatically scaled according to the column norms of the (estimated)
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44 ## Jacobian. As a result, @qcode{"TolFun"} becomes scaling-independent. By
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45 ## default, this option is @qcode{"off"} because it may sometimes deliver
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46 ## unexpected (though mathematically correct) results.
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47 ##
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48 ## If @qcode{"GradObj"} is @qcode{"on"}, it specifies that @var{fcn}--when
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49 ## called with two output arguments---also returns the Jacobian matrix of
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50 ## partial first derivatives at the requested point.
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51 ##
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52 ## @qcode{"MaxFunEvals"} proscribes the maximum number of function evaluations
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53 ## before optimization is halted. The default value is
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54 ## @code{100 * number_of_variables}, i.e., @code{100 * length (@var{x0})}.
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55 ## The value must be a positive integer.
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56 ##
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57 ## @qcode{"MaxIter"} proscribes the maximum number of algorithm iterations
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58 ## before optimization is halted. The default value is 400.
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59 ## The value must be a positive integer.
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60 ##
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61 ## @qcode{"TolX"} specifies the termination tolerance for the unknown variables
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62 ## @var{x}, while @qcode{"TolFun"} is a tolerance for the objective function
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63 ## value @var{fval}. The default is @code{1e-6} for both options.
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64 ##
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65 ## For a description of the other options, see @code{optimset}.
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66 ##
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67 ## On return, @var{x} is the location of the minimum and @var{fval} contains
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68 ## the value of the objective function at @var{x}.
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69 ##
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70 ## @var{info} may be one of the following values:
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71 ##
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72 ## @table @asis
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73 ## @item 1
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74 ## Converged to a solution point. Relative gradient error is less than
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75 ## specified by @code{TolFun}.
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76 ##
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77 ## @item 2
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78 ## Last relative step size was less than @code{TolX}.
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79 ##
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80 ## @item 3
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81 ## Last relative change in function value was less than @code{TolFun}.
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82 ##
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83 ## @item 0
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84 ## Iteration limit exceeded---either maximum number of algorithm iterations
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85 ## @code{MaxIter} or maximum number of function evaluations @code{MaxFunEvals}.
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86 ##
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87 ## @item -1
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88 ## Algorithm terminated by @code{OutputFcn}.
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89 ##
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90 ## @item -3
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91 ## The trust region radius became excessively small.
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92 ## @end table
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93 ##
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94 ## Optionally, @code{fminunc} can return a structure with convergence
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95 ## statistics (@var{output}), the output gradient (@var{grad}) at the
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96 ## solution @var{x}, and approximate Hessian (@var{hess}) at the solution
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97 ## @var{x}.
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98 ##
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99 ## Application Notes: If the objective function is a single nonlinear equation
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100 ## of one variable then using @code{fminbnd} is usually a better choice.
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101 ##
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102 ## The algorithm used by @code{fminunc} is a gradient search which depends
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103 ## on the objective function being differentiable. If the function has
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104 ## discontinuities it may be better to use a derivative-free algorithm such as
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105 ## @code{fminsearch}.
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106 ## @seealso{fminbnd, fminsearch, optimset}
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107 ## @end deftypefn
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108
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109 ## PKG_ADD: ## Discard result to avoid polluting workspace with ans at startup.
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110 ## PKG_ADD: [~] = __all_opts__ ("fminunc");
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111
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112 function [x, fval, info, output, grad, hess] = fminunc (fcn, x0, options = struct ())
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113
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114 ## Get default options if requested.
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115 if (nargin == 1 && strcmp (fcn, "defaults"))
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116 x = struct ("AutoScaling", "off", "FunValCheck", "off",
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117 "FinDiffType", "forward", "GradObj", "off",
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118 "MaxFunEvals", [], "MaxIter", 400, "OutputFcn", [],
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119 "TolFun", 1e-6, "TolX", 1e-6, "TypicalX", []);
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120 return;
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121 endif
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122
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123 if (nargin < 2 || nargin > 3 || ! isnumeric (x0))
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124 print_usage ();
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125 endif
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126
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127 if (ischar (fcn))
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128 fcn = str2func (fcn);
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129 endif
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130
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131 xsz = size (x0);
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132 n = numel (x0);
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133
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134 has_grad = strcmpi (optimget (options, "GradObj", "off"), "on");
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135 cdif = strcmpi (optimget (options, "FinDiffType", "forward"), "central");
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136 maxiter = optimget (options, "MaxIter", 400);
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137 maxfev = optimget (options, "MaxFunEvals", 100*n);
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138 outfcn = optimget (options, "OutputFcn");
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139
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140 ## Get scaling matrix using the TypicalX option. If set to "auto", the
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141 ## scaling matrix is estimated using the Jacobian.
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142 typicalx = optimget (options, "TypicalX");
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143 if (isempty (typicalx))
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144 typicalx = ones (n, 1);
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145 endif
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146 autoscale = strcmpi (optimget (options, "AutoScaling", "off"), "on");
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147 if (! autoscale)
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148 dg = 1 ./ typicalx;
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149 endif
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150
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151 funvalchk = strcmpi (optimget (options, "FunValCheck", "off"), "on");
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152
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153 if (funvalchk)
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154 ## Replace fcn with a guarded version.
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155 fcn = @(x) guarded_eval (fcn, x);
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156 endif
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157
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158 ## These defaults are rather stringent. I think that normally, user
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159 ## prefers accuracy to performance.
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160
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161 tolx = optimget (options, "TolX", 1e-7);
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162 tolf = optimget (options, "TolFun", 1e-7);
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163
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164 factor = 0.1;
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165 ## FIXME: TypicalX corresponds to user scaling (???)
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166 autodg = true;
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167
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168 niter = 1;
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169 nfev = 0;
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170
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171 x = x0(:);
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172 info = 0;
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173
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174 ## Initial evaluation.
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175 fval = fcn (reshape (x, xsz));
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176 n = length (x);
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177
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178 if (! isempty (outfcn))
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179 optimvalues.iter = niter;
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180 optimvalues.funccount = nfev;
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181 optimvalues.fval = fval;
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182 optimvalues.searchdirection = zeros (n, 1);
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183 state = "init";
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184 stop = outfcn (x, optimvalues, state);
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185 if (stop)
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186 info = -1;
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187 return;
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188 endif
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189 endif
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190
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191 if (isa (x0, "single") || isa (fval, "single"))
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192 macheps = eps ("single");
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193 else
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194 macheps = eps ("double");
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195 endif
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196
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197 nsuciter = 0;
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198 lastratio = 0;
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199
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200 grad = [];
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201
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202 ## Outer loop.
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203 while (niter < maxiter && nfev < maxfev && ! info)
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204
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205 grad0 = grad;
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206
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207 ## Calculate function value and gradient (possibly via FD).
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208 if (has_grad)
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209 [fval, grad] = fcn (reshape (x, xsz));
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210 grad = grad(:);
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211 nfev += 1;
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212 else
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213 grad = __fdjac__ (fcn, reshape (x, xsz), fval, typicalx, cdif)(:);
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214 nfev += (1 + cdif) * length (x);
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215 endif
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216
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217 if (niter == 1)
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218 ## Initialize by identity matrix.
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219 hesr = eye (n);
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220 else
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221 ## Use the damped BFGS formula.
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222 y = grad - grad0;
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223 sBs = sumsq (w);
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224 Bs = hesr' * w;
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225 sy = y' * s;
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226 theta = 0.8 / max (1 - sy / sBs, 0.8);
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227 r = theta * y + (1-theta) * Bs;
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228 hesr = cholupdate (hesr, r / sqrt (s' * r), "+");
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229 [hesr, info] = cholupdate (hesr, Bs / sqrt (sBs), "-");
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230 if (info)
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231 hesr = eye (n);
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232 endif
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233 endif
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234
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235 if (autoscale)
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236 ## Second derivatives approximate the Hessian.
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237 d2f = norm (hesr, "columns").';
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238 if (niter == 1)
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239 dg = d2f;
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240 else
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241 ## FIXME: maybe fixed lower and upper bounds?
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242 dg = max (0.1*dg, d2f);
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243 endif
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244 endif
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245
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246 if (niter == 1)
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247 xn = norm (dg .* x);
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248 ## FIXME: something better?
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249 delta = factor * max (xn, 1);
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250 endif
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251
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252 ## FIXME: why tolf*n*xn? If abs (e) ~ abs(x) * eps is a vector
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253 ## of perturbations of x, then norm (hesr*e) <= eps*xn, i.e., by
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254 ## tolf ~ eps we demand as much accuracy as we can expect.
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255 if (norm (grad) <= tolf*n*xn)
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256 info = 1;
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257 break;
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258 endif
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259
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260 suc = false;
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261 decfac = 0.5;
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262
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263 ## Inner loop.
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264 while (! suc && niter <= maxiter && nfev < maxfev && ! info)
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265
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266 s = - __doglegm__ (hesr, grad, dg, delta);
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267
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268 sn = norm (dg .* s);
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269 if (niter == 1)
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270 delta = min (delta, sn);
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271 endif
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272
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273 fval1 = fcn (reshape (x + s, xsz))(:);
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274 nfev += 1;
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275
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276 if (fval1 < fval)
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277 ## Scaled actual reduction.
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278 actred = (fval - fval1) / (abs (fval1) + abs (fval));
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279 else
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280 actred = -1;
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281 endif
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282
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283 w = hesr * s;
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284 ## Scaled predicted reduction, and ratio.
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285 t = 1/2 * sumsq (w) + grad'*s;
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286 if (t < 0)
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287 prered = -t/(abs (fval) + abs (fval + t));
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288 ratio = actred / prered;
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289 else
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290 prered = 0;
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291 ratio = 0;
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292 endif
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293
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294 ## Update delta.
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295 if (ratio < min (max (0.1, 0.8*lastratio), 0.9))
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296 delta *= decfac;
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297 decfac ^= 1.4142;
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298 if (delta <= 10*macheps*xn)
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299 ## Trust region became uselessly small.
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300 info = -3;
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301 break;
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302 endif
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303 else
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304 lastratio = ratio;
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305 decfac = 0.5;
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306 if (abs (1-ratio) <= 0.1)
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307 delta = 1.4142*sn;
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308 elseif (ratio >= 0.5)
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309 delta = max (delta, 1.4142*sn);
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310 endif
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311 endif
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312
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313 if (ratio >= 1e-4)
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314 ## Successful iteration.
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315 x += s;
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316 xn = norm (dg .* x);
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317 fval = fval1;
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318 nsuciter += 1;
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319 suc = true;
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320 endif
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321
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322 niter += 1;
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323
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324 ## FIXME: should outputfcn be called only after a successful iteration?
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325 if (! isempty (outfcn))
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326 optimvalues.iter = niter;
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327 optimvalues.funccount = nfev;
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328 optimvalues.fval = fval;
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329 optimvalues.searchdirection = s;
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330 state = "iter";
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331 stop = outfcn (x, optimvalues, state);
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332 if (stop)
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333 info = -1;
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334 break;
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335 endif
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336 endif
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337
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338 ## Tests for termination conditions. A mysterious place, anything
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339 ## can happen if you change something here...
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340
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341 ## The rule of thumb (which I'm not sure M*b is quite following)
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342 ## is that for a tolerance that depends on scaling, only 0 makes
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343 ## sense as a default value. But 0 usually means uselessly long
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344 ## iterations, so we need scaling-independent tolerances wherever
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345 ## possible.
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346
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347 ## The following tests done only after successful step.
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348 if (ratio >= 1e-4)
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349 ## This one is classic. Note that we use scaled variables again,
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350 ## but compare to scaled step, so nothing bad.
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351 if (sn <= tolx*xn)
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352 info = 2;
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353 ## Again a classic one.
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354 elseif (actred < tolf)
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355 info = 3;
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356 endif
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357 endif
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358
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359 endwhile
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360 endwhile
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361
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362 ## When info != 1, recalculate the gradient and Hessian using the final x.
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363 if (nargout > 4 && (info == -1 || info == 2 || info == 3))
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364 grad0 = grad;
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365 if (has_grad)
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366 [fval, grad] = fcn (reshape (x, xsz));
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367 grad = grad(:);
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368 else
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369 grad = __fdjac__ (fcn, reshape (x, xsz), fval, typicalx, cdif)(:);
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370 endif
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371
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372 if (nargout > 5)
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373 ## Use the damped BFGS formula.
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374 y = grad - grad0;
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375 sBs = sumsq (w);
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376 Bs = hesr' * w;
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377 sy = y' * s;
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378 theta = 0.8 / max (1 - sy / sBs, 0.8);
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379 r = theta * y + (1-theta) * Bs;
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380 hesr = cholupdate (hesr, r / sqrt (s' * r), "+");
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381 hesr = cholupdate (hesr, Bs / sqrt (sBs), "-");
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382 endif
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383 ## Return the gradient in the same shape as x
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384 grad = reshape (grad, xsz);
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385 endif
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386
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387 ## Restore original shapes.
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388 x = reshape (x, xsz);
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389
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390 if (nargout > 3)
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Rik <rik@octave.org>
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diff changeset
391 output.iterations = niter;
6faaab833605 fminunc.m: Clean up function to meet Octave coding standards.
Rik <rik@octave.org>
parents: 20694
diff changeset
392 output.successful = nsuciter;
6faaab833605 fminunc.m: Clean up function to meet Octave coding standards.
Rik <rik@octave.org>
parents: 20694
diff changeset
393 output.funcCount = nfev;
6faaab833605 fminunc.m: Clean up function to meet Octave coding standards.
Rik <rik@octave.org>
parents: 20694
diff changeset
394 endif
9084
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Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
395
9627
5bcfa0b346e8 fix extra outputs in fminunc
Jaroslav Hajek <highegg@gmail.com>
parents: 9623
diff changeset
396 if (nargout > 5)
5bcfa0b346e8 fix extra outputs in fminunc
Jaroslav Hajek <highegg@gmail.com>
parents: 9623
diff changeset
397 hess = hesr'*hesr;
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parents: 9623
diff changeset
398 endif
5bcfa0b346e8 fix extra outputs in fminunc
Jaroslav Hajek <highegg@gmail.com>
parents: 9623
diff changeset
399
9084
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parents:
diff changeset
400 endfunction
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
401
18609
923614060f1d fminunc.m: Improve documentation.
Rik <rik@octave.org>
parents: 18608
diff changeset
402 ## A helper function that evaluates a function and checks for bad results.
9084
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
403 function [fx, gx] = guarded_eval (fun, x)
21758
ffad2baa90f7 maint: Use newlines to make code more readable.
Rik <rik@octave.org>
parents: 21751
diff changeset
404
9084
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Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
405 if (nargout > 1)
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Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
406 [fx, gx] = fun (x);
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
407 else
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
408 fx = fun (x);
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
409 gx = [];
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
410 endif
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
411
14383
07c55bceca23 Fix guarded_eval() subfunction in fminunc (bug #35534).
Olaf Till <olaf.till@uni-jena.de>
parents: 14138
diff changeset
412 if (! (isreal (fx) && isreal (gx)))
11587
c792872f8942 all script files: untabify and strip trailing whitespace
John W. Eaton <jwe@octave.org>
parents: 11523
diff changeset
413 error ("fminunc:notreal", "fminunc: non-real value encountered");
9084
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
414 elseif (any (isnan (fx(:))))
11587
c792872f8942 all script files: untabify and strip trailing whitespace
John W. Eaton <jwe@octave.org>
parents: 11523
diff changeset
415 error ("fminunc:isnan", "fminunc: NaN value encountered");
14386
59aab666f2bf Extend "FunValCheck" option to optimization routines to detect Inf values.
Rik <octave@nomad.inbox5.com>
parents: 14383
diff changeset
416 elseif (any (isinf (fx(:))))
59aab666f2bf Extend "FunValCheck" option to optimization routines to detect Inf values.
Rik <octave@nomad.inbox5.com>
parents: 14383
diff changeset
417 error ("fminunc:isinf", "fminunc: Inf value encountered");
9084
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Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
418 endif
21758
ffad2baa90f7 maint: Use newlines to make code more readable.
Rik <rik@octave.org>
parents: 21751
diff changeset
419
9084
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Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
420 endfunction
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
421
14386
59aab666f2bf Extend "FunValCheck" option to optimization routines to detect Inf values.
Rik <octave@nomad.inbox5.com>
parents: 14383
diff changeset
422
20695
6faaab833605 fminunc.m: Clean up function to meet Octave coding standards.
Rik <rik@octave.org>
parents: 20694
diff changeset
423 %!function f = __rosenb__ (x)
9084
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Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
424 %! n = length (x);
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
425 %! f = sumsq (1 - x(1:n-1)) + 100 * sumsq (x(2:n) - x(1:n-1).^2);
13305
63463570d9fe Add %!endfunction block keyword to test.m
Rik <octave@nomad.inbox5.com>
parents: 13027
diff changeset
426 %!endfunction
19833
9fc020886ae9 maint: Clean up m-files to follow Octave coding conventions.
Rik <rik@octave.org>
parents: 19697
diff changeset
427 %!
9084
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Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
428 %!test
20695
6faaab833605 fminunc.m: Clean up function to meet Octave coding standards.
Rik <rik@octave.org>
parents: 20694
diff changeset
429 %! [x, fval, info, out] = fminunc (@__rosenb__, [5, -5]);
9084
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parents:
diff changeset
430 %! tol = 2e-5;
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
431 %! assert (info > 0);
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
432 %! assert (x, ones (1, 2), tol);
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
433 %! assert (fval, 0, tol);
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
434 %!test
20695
6faaab833605 fminunc.m: Clean up function to meet Octave coding standards.
Rik <rik@octave.org>
parents: 20694
diff changeset
435 %! [x, fval, info, out] = fminunc (@__rosenb__, zeros (1, 4));
9084
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parents:
diff changeset
436 %! tol = 2e-5;
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
437 %! assert (info > 0);
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
438 %! assert (x, ones (1, 4), tol);
b7210faa3ed0 implement fminunc using factored trust-region BFGS
Jaroslav Hajek <highegg@gmail.com>
parents:
diff changeset
439 %! assert (fval, 0, tol);
19833
9fc020886ae9 maint: Clean up m-files to follow Octave coding conventions.
Rik <rik@octave.org>
parents: 19697
diff changeset
440
9fc020886ae9 maint: Clean up m-files to follow Octave coding conventions.
Rik <rik@octave.org>
parents: 19697
diff changeset
441 ## Test FunValCheck works correctly
26137
1ae11ca7dceb fminunc.m: Change algorithm defaults to match Matlab.
Rik <rik@octave.org>
parents: 26118
diff changeset
442 %!assert (fminunc (@(x) x^2, 1, optimset ("FunValCheck", "on")), 0, 1e-6)
14386
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Rik <octave@nomad.inbox5.com>
parents: 14383
diff changeset
443 %!error <non-real value> fminunc (@(x) x + i, 1, optimset ("FunValCheck", "on"))
59aab666f2bf Extend "FunValCheck" option to optimization routines to detect Inf values.
Rik <octave@nomad.inbox5.com>
parents: 14383
diff changeset
444 %!error <NaN value> fminunc (@(x) x + NaN, 1, optimset ("FunValCheck", "on"))
59aab666f2bf Extend "FunValCheck" option to optimization routines to detect Inf values.
Rik <octave@nomad.inbox5.com>
parents: 14383
diff changeset
445 %!error <Inf value> fminunc (@(x) x + Inf, 1, optimset ("FunValCheck", "on"))
59aab666f2bf Extend "FunValCheck" option to optimization routines to detect Inf values.
Rik <octave@nomad.inbox5.com>
parents: 14383
diff changeset
446
9084
b7210faa3ed0 implement fminunc using factored trust-region BFGS
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parents:
diff changeset
447
9899
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John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
448 ## Solve the double dogleg trust-region minimization problem:
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
449 ## Minimize 1/2*norm(r*x)^2 subject to the constraint norm(d.*x) <= delta,
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
450 ## x being a convex combination of the gauss-newton and scaled gradient.
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
451
21578
683a1beee538 maint: Use "FIXME:" for all code blocks needing further attention.
Rik <rik@octave.org>
parents: 21546
diff changeset
452 ## FIXME: error checks
683a1beee538 maint: Use "FIXME:" for all code blocks needing further attention.
Rik <rik@octave.org>
parents: 21546
diff changeset
453 ## FIXME: handle singularity, or leave it up to mldivide?
9899
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
454
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
455 function x = __doglegm__ (r, g, d, delta)
21758
ffad2baa90f7 maint: Use newlines to make code more readable.
Rik <rik@octave.org>
parents: 21751
diff changeset
456
9899
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
457 ## Get Gauss-Newton direction.
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
458 b = r' \ g;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
459 x = r \ b;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
460 xn = norm (d .* x);
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
461 if (xn > delta)
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
462 ## GN is too big, get scaled gradient.
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
463 s = g ./ d;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
464 sn = norm (s);
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
465 if (sn > 0)
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
466 ## Normalize and rescale.
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
467 s = (s / sn) ./ d;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
468 ## Get the line minimizer in s direction.
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
469 tn = norm (r*s);
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
470 snm = (sn / tn) / tn;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
471 if (snm < delta)
10549
95c3e38098bf Untabify .m scripts
Rik <code@nomad.inbox5.com>
parents: 10201
diff changeset
472 ## Get the dogleg path minimizer.
9899
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
473 bn = norm (b);
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
474 dxn = delta/xn; snmd = snm/delta;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
475 t = (bn/sn) * (bn/xn) * snmd;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
476 t -= dxn * snmd^2 - sqrt ((t-dxn)^2 + (1-dxn^2)*(1-snmd^2));
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
477 alpha = dxn*(1-snmd^2) / t;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
478 else
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
479 alpha = 0;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
480 endif
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
481 else
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
482 alpha = delta / xn;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
483 snm = 0;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
484 endif
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
485 ## Form the appropriate convex combination.
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
486 x = alpha * x + ((1-alpha) * min (snm, delta)) * s;
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
487 endif
21758
ffad2baa90f7 maint: Use newlines to make code more readable.
Rik <rik@octave.org>
parents: 21751
diff changeset
488
9899
9f25290a35e8 more private function and subfunction changes
John W. Eaton <jwe@octave.org>
parents: 9758
diff changeset
489 endfunction