first commit with current lessons
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252
10-12/GRS.m
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252
10-12/GRS.m
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function [ x , status ] = GRS( f , varargin )
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%function [ x , status ] = GRS( f , range , delta , MaxFeval )
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%
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% Apply the classical Golden Ratio Search for the minimization of the
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% provided one-dimensional function f, which must have the following
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% interface:
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%
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% [ v , varargout ] = f( x )
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%
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% Input:
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%
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% - x is either a scalar real denoting the input of f(), or [] (empty).
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%
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% Output:
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%
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% - v (real, scalar): if x == [] this is the best known lower bound on
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% the global optimum of f() on the standard interval in which f() is
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% supposed to be minimised (see next). If x ~= [] then v = f(x).
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%
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% - g (real, either scalar or a [ 2 x 1 ] matrix denoting an interval) is
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% the first optional argument. This also depends on x. if x == [] then
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% g is a [ 2 x 1 ] matrix denoting the standard interval in which f()
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% is supposed to be minimised (into which v is the minimum). f() is
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% never called with x ~= [].
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%
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% The other [optional] input parameters are:
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%
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% - range: (either [ 2 x 1 ] real vector or [], default []): the range
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% in which the local minimum has to be seached; if range == [], the
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% default range point provided by f() is used.
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%
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% - delta (real scalar, default value 1e-6): the accuracy in the stopping
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% criterion: the algorithm is stopped when the diameter of the
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% restricted range is less than or equal to delta.
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%
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% - MaxFeval (integer scalar, default value 100): the maximum number of
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% function evaluations (hence, iterations will be not more than
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% MaxFeval - 2 because at each iteration one function evaluation is
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% performed, except in the first one when two are).
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%
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% Output:
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%
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% - x (real scalar): the best solution found so far.
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%
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% - status (string): a string describing the status of the algorithm at
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% termination
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%
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% = 'optimal': the algorithm terminated having proven that x is a(n
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% approximately) optimal solution, i.e., the diameter of the
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% restricted range is less than or equal to delta.
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%
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% = 'empty': the provided range is empty (x_- > x_+) and therefore
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% such is the optimization problem
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%
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% = 'stopped': the algorithm terminated having exhausted the maximum
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% number of iterations: x is the best solution found so far, but not
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% necessarily the optimal one
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%
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% = 'error': the algorithm found a numerical error that prevents it from
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% continuing optimization
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%
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%{
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=======================================
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Author: Antonio Frangioni
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Date: 09-08-21
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Version 0.10
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Copyright Antonio Frangioni
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=======================================
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%}
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Plotg = 1;
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% 0 = nothing is plotted
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% 1 = the function value / gap are plotted
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% 2 = the function and the test points used are plotted
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Interactive = true; % if we pause at every iteration
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% reading and checking input- - - - - - - - - - - - - - - - - - - - - - - -
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% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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if ~ isa( f , 'function_handle' )
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error( 'f not a function' );
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end
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if isempty( varargin ) || isempty( varargin{ 1 } )
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[ fStar , range ] = f( [] );
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else
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fStar = - Inf; % if the range is not the standard one, we can't trust
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% the standard global minima
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range = varargin{ 1 };
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end
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if ~ isreal( range )
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error( 'range not a real vector' );
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end
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if ( size( range , 1 ) ~= 1 ) || ( size( range , 2 ) ~= 2 )
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error( 'range is not a [ 1 x 2 ] vector' );
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end
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xm = range( 1 ); % x_-
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xp = range( 2 ); % x_+
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if xm > xp
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fprintf( 'range is empty\n' );
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x = NaN;
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status = 'empty';
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return;
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end
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if length( varargin ) > 1
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delta = varargin{ 2 };
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if ~ isreal( delta ) || ~ isscalar( delta )
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error( 'delta is not a real scalar' );
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end
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else
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delta = 1e-6;
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end
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if length( varargin ) > 2
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MaxFeval = round( varargin{ 3 } );
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if ~ isscalar( MaxFeval )
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error( 'MaxFeval is not an integer scalar' );
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end
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if MaxFeval < 2
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error( 'at least two function computations are required' );
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end
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else
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MaxFeval = 100;
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end
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% initializations - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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r = ( sqrt( 5 ) - 1 ) / 2;
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xmp = xm + ( 1 - r ) * ( xp - xm ); % x'_-
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xpp = xm + r * ( xp - xm ); % x'_+
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fxmp = f( xmp ); % f( x'_- )
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fxpp = f( xpp ); % f( x'_+ )
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feval = 2;
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if fxmp <= fxpp
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fx = fxmp;
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else
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fx = fxpp;
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end
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status = 'optimal';
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if Plotg
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gap = [];
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end
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fprintf( 'Golden ratio search\n');
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if fStar > - Inf
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fprintf( 'feval\trel gap\t\tx_-\t\tx_+\n');
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else
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fprintf( 'feval\tfbest\t\tx_-\t\tx_+\n');
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end
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% main loop - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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while xp - xm > delta
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% output statistics - - - - - - - - - - - - - - - - - - - - - - - - - -
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if fStar > - Inf
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gapk = ( fx - fStar ) / max( [ abs( fStar ) 1 ] );
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if Plotg == 1
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gap( end + 1 ) = gapk;
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semilogy( gap , 'Color' , 'k' , 'LineWidth' , 2 );
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xlim( [ 0 35 ] );
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ylim( [ 1e-15 inf ] );
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ax = gca;
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ax.FontSize = 16;
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ax.Position = [ 0.03 0.07 0.95 0.92 ];
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ax.Toolbar.Visible = 'off';
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end
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else
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gapk = fx;
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end
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fprintf( '%4d\t%1.4e\t%1.8e\t%1.8e\n' , feval , gapk , xm , xp );
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if Plotg == 2
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xbot = xm - ( xp - xm ) / 20;
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xtop = xp + ( xp - xm ) / 20;
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warning( 'off' , 'all' );
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fplot( @(x) f( x ) , [ xbot xtop ] , 'Color' , 'k' , ...
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'LineWidth' , 1 );
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xlim( [ xbot xtop ] );
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yticks( [] );
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ax = gca;
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ax.FontSize = 16;
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ax.Position = [ 0.025 0.05 0.95 0.95 ];
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ax.Toolbar.Visible = 'off';
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xticks( [ xbot xm xmp xpp xp xtop ] );
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xticklabels( { num2str( xbot , '%1.1g' ) , 'x-' , 'x''-' , ...
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'x''+' , 'x+' , num2str( xtop , '%1.1g' ) } );
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warning( 'on' , 'all' );
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end
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% stopping criteria - - - - - - - - - - - - - - - - - - - - - - - - - -
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if feval > MaxFeval
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status = 'stopped';
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break;
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end
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% main logic- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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if fxmp <= fxpp
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xp = xpp; xpp = xmp; xmp = xm + ( 1 - r ) * ( xp - xm );
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fxpp = fxmp; fx = fxmp; fxmp = f( xmp );
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else
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xm = xmp; xmp = xpp; xpp = xm + r * ( xp - xm );
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fxmp = fxpp; fx = fxpp; fxpp = f( xpp );
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end
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feval = feval + 1;
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if Interactive
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pause;
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end
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% iterate - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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end
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% end of main loop- - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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% select final answer
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if fxmp <= fxpp
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x = xmp;
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else
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x = xpp;
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end
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% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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end % the end- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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