psoptimset.m

遗传算法工具包

function options = psoptimset(varargin)
%PSOPTIMSET Create/alter pattern search OPTIONS structure.
%   OPTIONS = PSOPTIMSET('PARAM1',VALUE1,'PARAM2',VALUE2, ...) creates an
%   optimization options structure OPTIONS in which the named parameters
%   have the specified values. Any unspecified parameters are set to []
%   (parameters with value [] indicate to use the default value for that
%   parameter when  OPTIONS is passed to the optimization function). It is
%   sufficient to type  only the leading characters that uniquely identify
%   the parameter. Case is  ignored for parameter names. NOTE: For
%   values that are strings, correct case and the complete string are
%   required.
%   
%   OPTIONS = PSOPTIMSET(OLDOPTS,'PARAM1',VALUE1, ...) creates a copy of
%   OLDOPTS with the named parameters altered with the specified values.
%   
%   OPTIONS = PSOPTIMSET(OLDOPTS,NEWOPTS) combines an existing options
%   structure OLDOPTS with a new options structure NEWOPTS. Any parameters
%   in NEWOPTS with non-empty values overwrite the corresponding old
%   parameters in OLDOPTS. 
%   
%   PSOPTIMSET with no input arguments and no output arguments displays all
%   parameter names and their possible values, with defaults shown in {}.
%
%   OPTIONS = PSOPTIMSET (with no input arguments) creates an options
%   structure OPTIONS where all the fields are set to defaults for
%   PATTERNSEARCH.
%
%PSOPTIMSET PARAMETERS
%   TolMesh              - Tolerance on mesh size used to terminate the
% 	                        iteration 
%                          [ positive scalar | {1e-6} ]
%   TolFun               - Tolerance on function used to terminate the
% 	                        iteration
%                          [ positive scalar | {1e-6} ] 
%   TolX                 - Tolerance on X used to terminate the iteration
%                          [ positive scalar | {1e-6} ] 
%   TolBind              - Binding Tolerance
%                          [ positive scalar | {1e-3} ]
%   MaxIteration         - Maximum number of iterations allowed 
%                          [ positive scalar | {100*numberOfVariables} ]
%   MaxFunEvals          - Maximum number of function (objective)
% 	                        evaluations allowed 
%                          [ positive scalar | {2000*numberOfVariables} ]
% 	
%   MeshContraction      - Mesh refining factor used when an iteration is not
%                          successful 
%                          [ positive scalar | {0.5} ]
%   MeshExpansion        - Mesh coarsening factor used when an iteration is
%                          successful 
%                          [ positive scalar | {2.0} ] 
%   MeshAccelerator      - Accelerate convergence when near a minima (may
%                          lose some accuracy)
%                          [ 'on',{'off'} ]
%   MeshRotate           - Rotate the pattern before declaring a point to
%                          be optimum
%                          [ 'off',{'on'} ]
%   InitialMeshSize      - Initial mesh size at start
%                          [ positive scalar | {1.0} ]
%   ScaleMesh            - Mesh is scaled if 'on'
%                          [ 'off', {'on'} ]
%   MaxMeshSize          - Maximum mesh size used in a POLL/SEARCH step
%                          [ positive scalar | {Inf} ]
% 	
%   PollMethod           - Polling method
%                          [ 'PositiveBasisNp1' | {'PositiveBasis2N'} ]
%   CompletePoll         - Complete polling around the current iterate
%                          [ 'on',{'off'} ]
%   PollingOrder         - Ordering of the POLL directions
%                          [ 'Random' |'Success'| {'Consecutive'} ]
% 	
%   SearchMethod         - Search method
%                          [ @PositiveBasisNp1 | @PositiveBasis2N  |
%                            @searchlhs        | @searchneldermead | 
%                            @searchga         | {[]} ]
%   CompleteSearch       - Complete search around the current iterate
%                          [ 'on',{'off'} ]
%
%   Display              - Level of display 
%                          [ 'off' | 'iter' | 'diagnose' | {'final'} ]
%   OutputFcns           - A set of functions called in every iteration 
%                          [ @psoutputhistory| {[]} ]
%   PlotFcns             - A set of specialized plot functions called in
%                          every iteration 
%                          [ @psplotbestf    |  @psplotmeshsize | 
%                            @psplotfuncount |  @psplotbestx    | {[]} ]
%   PlotInterval         - Plot functions will be called every interval
%                          [ {1} ]
%   Cache                - Use a CACHE of the points evaluated. This
% 	                        options could be expensive in terms of memory 
%                          and speed . If the objective function is
%                          stochastic, it is advised not to use this option.
%                          [ 'on', {'off'} ]
%   CacheSize            - Limit the CACHE size. A typical choice of 1e4 is
%                          suggested but it depends on computer speed and 
%                          memory. Used if 'Cache' option is 'on'.
%                          [ positive scalar | {1e4} ]
%   CacheTol             - Tolerance used to determine if two points are
%                          close enough to be declared same. 
%                          Used if 'Cache' option is 'on'. 
%                          [ positive scalar | {eps} ]
% 	
%   Vectorized           - Objective function is vectorized and it can
%                          evaluate more than one point in one call 
%                          [ 'on' | {'off'} ]
% 	 	
% 	 See also PSOPTIMGET.

%   Copyright 2004 The MathWorks, Inc.
%   $Revision: 1.19.4.1 $  $Date: 2004/03/18 17:59:38 $


% Print out possible values of properties, when called with no input/output arguments
if (nargin == 0) && (nargout == 0)
    fprintf('                 TolMesh: [ positive scalar | {1e-6} ]\n');
    fprintf('                    TolX: [ positive scalar | {1e-6} ]\n');
    fprintf('                  TolFun: [ positive scalar | {1e-6} ]\n');
    fprintf('                 TolBind: [ positive scalar | {1e-3} ]\n');
    fprintf('            MaxIteration: [ positive scalar | {100*numberOfVariables} ]\n');
    fprintf('             MaxFunEvals: [ positive scalar | {2000*numberOfVariables} ]\n\n');
    
    fprintf('         MeshContraction: [ positive scalar | {0.5} ]\n');
    fprintf('           MeshExpansion: [ positive scalar | {2.0} ]\n');
    fprintf('         MeshAccelerator: [ on  | {off} ]\n');
    fprintf('              MeshRotate: [ off | {on} ]\n');
    fprintf('         InitialMeshSize: [ positive scalar | {1.0} ]\n');
    fprintf('               ScaleMesh: [ off | {on} ]\n');
    fprintf('             MaxMeshSize: [ positive scalar | {Inf} ]\n\n');
    
    fprintf('              PollMethod: [ PositiveBasisNp1 | {PositiveBasis2N} ]\n');
    fprintf('            CompletePoll: [ on  | {off} ]\n');
    fprintf('            PollingOrder: [ Random | Success | {Consecutive} ]\n\n');
    
    fprintf('            SearchMethod: [ function_handle  | @PositiveBasisNp1 |\n');
    fprintf('                            @PositiveBasis2N | @searchga |\n'); 
    fprintf('                            @searchlhs       | @searchneldermead | {[]} ]\n');
    fprintf('          CompleteSearch: [ on  | {off} ]\n\n');
    
    fprintf('                 Display: [ off | iter | diagnose | {final} ]\n');
    fprintf('              OutputFcns: [ function_handle | @psoutputhistory {[]} ]\n\n');
    fprintf('                PlotFcns: [ function_handle | @psplotbestf |\n');
    fprintf('                            @psplotmeshsize | @psplotfuncount |\n');
    fprintf('                            @psplotbestx    | {[]} ]\n');
    fprintf('            PlotInterval: [ positive scalar | {1} ]\n\n');
    
    fprintf('                   Cache: [ on  | {off} ]\n');
    fprintf('               CacheSize: [ positive scalar | {1e4} ]\n');
    fprintf('                CacheTol: [ positive scalar | {eps} ]\n\n');
    
    fprintf('              Vectorized: [ on | {off} ]\n');
    return; 
end     

numberargs = nargin; 

%Return options with default values and return it when called with one
%output argument
options= struct('TolMesh', 1e-6, ...
                'TolX', 1e-6 , ...
                'TolFun',1e-6 , ...
                'TolBind',1e-3, ...
                'MaxIteration', '100*numberofvariables', ...
                'MaxFunEvals', '2000*numberofvariables', ...
                'MeshContraction', 0.5, ... 
                'MeshExpansion', 2.0, ...
                'MeshAccelerator','off', ... 
                'MeshRotate','on', ...
                'InitialMeshSize', 1.0, ...
                'ScaleMesh', 'on', ...
                'MaxMeshSize', inf, ...
                'PollMethod', 'positivebasis2n', ...
                'CompletePoll','off', ...
                'PollingOrder', 'consecutive', ...
                'SearchMethod', [], ...
                'CompleteSearch','off', ...
                'Display', 'final', ...
                'OutputFcns', [], ... 
                'PlotFcns',[]', ...
                'PlotInterval', 1, ...
                'Cache', 'off', ...
                'CacheSize',1e4, ... 
                'CacheTol',eps, ...
                'Vectorized','off' ...
               ); 

% If we pass in a function name then return the defaults.
if (numberargs==1) && (ischar(varargin{1}) || isa(varargin{1},'function_handle') )
    if ischar(varargin{1})
        funcname = lower(varargin{1});
        if ~exist(funcname)
            msg = sprintf( ...
                'No default options available: the function ''%s'' does not exist on the path.',funcname);
            error('gads:PSOPTIMSET:functionNotFound',msg)
        end
    elseif isa(varargin{1},'function_handle')
        funcname = func2str(varargin{1});
    end
    try 
        optionsfcn = feval(varargin{1},'defaults');
    catch
        msg = sprintf( ...
            'No default options available for the function ''%s''.',funcname);
        error('gads:PSOPTIMSET:noDefaultOptions',msg)
    end
    % To get output, run the rest of psoptimset as if called with psoptimset(options, optionsfcn)