unsudemo.m

四种SVM工具箱的分类与回归算法别人的

function []=unsudemo(action,hfigure,varargin)
% UNSUDEMO demo on unsupervised (EM) learning algorithm.
%
% UNSUDEMO demonstrates the unsupervised (Expectation-Maximization) 
%   learning algorithm on simple examples in 2D space.
%
%   The aim is to estimate a statistical model described as the
%   weighted mixture of Gaussians from unlabeled data 
%   (point set/patterns). The input data is supposed to be
%   identicaly and independently seleted.
%
%   The found model is described by ellipsoids (shape of 
%   covariances) and a croses (mean value vectors). The value
%   of the optimized log-likelihood function for given model 
%   is displayed as well.
%
% Control:
%  Features     - select the model with Independent (diagonal covariance 
%                 matrix) or Dependent (full cov. matrix) features.
%  % of classes - prescribe the number of classes (components of the 
%                 mixture of Gaussians).
%               
%  Iterations   - number of iterations in one step.
%  Random init  - the initial model is randomly generated and/or it is 
%                 determined by the first n-patterns (mean values)
%                 and sample covarinace matrix (covarinaces matrices).
%
%  FIG2EPS     - export screen to the PostScript file.
%  Save model  - save current model to file.
%  Load data   - load input point sets from file.
%  Create data - invoke program for creating point sets.
%  Reset       - set the tested algorithm to the initial state.
%  Play        - run the tested algorithm.
%  Stop        - stop the running algorithm.
%  Step        - perform only one step.
%  Info        - invoke the info box.
%  Close       - close the program.
%
% See also UNSUNI, UNSUND.
%

% Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac
% (c) Czech Technical University Prague, http://cmp.felk.cvut.cz
% Written Vojtech Franc (diploma thesis) 10.11.1999
% Modifications
% 11-june-2001, V.Franc, comments added.
% 27.02.00 V. Franc
%  5. 4.00 V. Franc
% 23.06.00 V. Hlavac Comments polished. Message when no data loaded.
%                    Export of the solution to global variables.
% 27-mar-2001, V.Franc, Graph og log-likelihood function added


% Used functions: PPOINTS, PNMIX

% == Global variables, used to export results from UNSUDEMO ========

global UNSU_MI       % K vectors with mean values
global UNSU_SIGMA    % K covariance matrices
global UNSU_PK       % K apriori probabilities for each distributions.
%global UNSU_eI      % Used only by the next iteration, not globalised
global UNSU_solution % 1 if alg. finished in stationary point, 0 otherwise
global UNSU_t        % Number of iterations the algorithm performed

% == Constants =====================================================

AXIST_ADD=10;
AXISY_ADD=5;

BORDER=0.25;           % space betwean window outer and the points
CENTERSIZE=10;         % size of center point
LINE_WIDTH=1;
AXIST_ADD=10;
DATA_IDENT='Finite sets, enumeration';   % file identifier
randinit=1;

if nargin < 1,
   action = 'initialize';
end

% What action is required ?
switch lower(action)

case 'initialize'
   % == Initialize user interface control and figure window ================

   % == Figure
   % =============================================================
   left=0.2;
   width=0.6;
   bottom=0.1;
   height=0.8;
   hfigure=figure('Name','Unsupervised learning', ...
      'Visible','off',...
      'NumberTitle','off', ...
      'Units','normalized', ...
      'Position',[left bottom width height],...
      'tag','Unsudemo',...
      'doublebuffer','on',...
      'backingstore','off');

   
   % == Axes ===============================================================
   left=0.1;
   width=0.65;
   bottom=0.45;
   height=0.5;
   haxes1=axes(...
      'Units','normalized', ...
      'NextPlot','add',...
      'UserData',[],...
      'Position',[left bottom width height]);
   xlabel('feature x');
   ylabel('feature y');

   htitle1=title('No data loaded',...
      'VerticalAlignment','bottom',...
      'Parent',haxes1,...
      'HorizontalAlignment','left',...
      'Units','normalized',...
      'Position',[0 1 0]);

   % axes log-Likelihood graph
   left=0.1;
   width=0.65;
   bottom=0.1;
   height=0.25;
   haxes2=axes(...
      'Units','normalized', ...
      'NextPlot','add',...
      'Position',[left bottom width height]);
   ylabel('logL(t)');
   
   htitle2=title('Log-likelihood function',...
       'Parent',haxes2,...
       'VerticalAlignment','bottom',...
       'Units','normalized',...
       'HorizontalAlignment','left',...
       'Position',[0 1 0]);
    htxsteps=xlabel('step number t=0');
   
   
   
   % == Comment Window frame ==============================================
%%   bottom=0.05;
%%   height=0.16;
%%   uicontrol( ...
%%        'Style','frame', ...
%%        'Units','normalized', ...
%%        'Position',[left bottom width height], ...
%%        'BackgroundColor',[0.5 0.5 0.5]);

   % Text label
%   uicontrol( ...
%        'Style','text', ...
%        'Units','normalized', ...
%        'Position',[left height-0.01 width 0.05], ...
%        'BackgroundColor',[0.5 0.5 0.5], ...
%        'ForegroundColor',[1 1 1], ...
%        'String','Comment Window');

   % Edit window
%%   border=0.01;
%%   hconsole=uicontrol( ...
%%        'Style','edit', ...
%%        'HorizontalAlignment','left', ...
%%        'Units','normalized', ...
%%        'Max',10, ...
%%        'BackgroundColor',[1 1 1], ...
%%        'Position',[left+border bottom width-2*border height-0.05], ...
%%      'Enable','inactive',...
%%        'String','');


   % == Buttons ===========================================================

   % -- Export to EPS ---------
   width=0.1;
   left=0.75-width;
   bottom=0.95;
   height=0.04;
   hbtclose = uicontrol(...
    'Units','Normalized', ...
      'Callback','fig2eps(gcf)',...
        'ListboxTop',0, ...
        'Position',[left bottom width height], ...
      'String','FIG2EPS');
   %----------------------------------

   % Close button
   left=0.8;
   bottom=0.05;
   height=0.044;
   width=0.15;
   hbtclose = uicontrol(...
    'Units','Normalized', ...
      'Callback','close(gcf)',...
        'ListboxTop',0, ...
        'Position',[left bottom width height], ...
        'String','Close');

   % Info button: call stanard info box
   bottom=bottom+1.5*height;
   hbtinfo = uicontrol(...
    'Units','Normalized', ...
      'Callback','unsudemo(''info'',gcf)',...
        'ListboxTop',0, ...
        'Position',[left bottom width height], ...
        'String','Info');

   % Step button: perform one adaptation step
   bottom=bottom+1.5*height;
    hbtstep = uicontrol(...
      'Units','Normalized', ...
      'ListboxTop',0, ...
        'Position',[left bottom width height], ...
      'String','Step', ...
      'Interruptible','off',...
      'Callback','unsudemo(''step'',gcf)');

   % Stop button: stop process of adaptation
   bottom=bottom+height;
   hbtstop = uicontrol(...
    'Units','Normalized', ...
        'ListboxTop',0, ...
        'Position',[left bottom width height], ...
      'String','Stop', ...
      'Callback','set(gcbo,''UserData'',1)',...
      'Enable','off');

   % Play button: begin adaptation
   bottom=bottom+height;
   hbtplay = uicontrol(...
    'Units','Normalized', ...
      'ListboxTop',0, ...
        'Position',[left bottom width height], ...
      'String','Play', ...
      'Callback','unsudemo(''play'',gcf)');

   % Reset button: set up t = 0
   bottom=bottom+height;
    hbtreset = uicontrol(...
      'Units','Normalized', ...
      'ListboxTop',0, ...
        'Position',[left bottom width height], ...
      'String','Reset', ...
      'Callback','unsudemo(''reset'',gcf)');

   % Create data
   bottom=bottom+1.5*height;
    hbtcreat = uicontrol(...
      'Units','Normalized', ...
      'ListboxTop',0, ...
        'Position',[left bottom width height], ...
      'String','Create data', ...
      'Callback','unsudemo(''creatdata'',gcf)');

   % Load data
   bottom=bottom+1*height;
    hbtload = uicontrol(...
      'Units','Normalized', ...
      'ListboxTop',0, ...
        'Position',[left bottom width height], ...
      'String','Load data', ...
      'Callback','unsudemo(''getfile'',gcf)');

   % Save model
   bottom=bottom+1.5*height;
    hbtSaveModel = uicontrol(...
      'Units','Normalized', ...
      'ListboxTop',0, ...
        'Position',[left bottom width height], ...
      'String','Save model', ...
      'Callback','unsudemo(''savemodel'',gcf)');

   % Load model
%   bottom=bottom+1*height;
%    hbtLoadModel = uicontrol(...
%      'Units','Normalized', ...
%      'ListboxTop',0, ...
%        'Position',[left bottom width height], ...
%      'String','Load model', ...
%      'Callback','unsudemo(''loadmodel'',gcf)');

   % == PopUp Menu =====================================================
   bottom=0.95-height;
   htxfeatures=uicontrol( ...
      'Style','text', ...
      'Units','normalized', ...
      'Position',[left bottom width height], ...
      'String','Features');
   % popup menu
   bottom=bottom-height;
   hpufeatures=uicontrol( ...
      'Style','popup', ...
      'Units','normalized', ...
      'Position',[left bottom width height], ...
      'String',['Independent ';'Dependent   ']);

   % == Edit line ==========================================================
   % prior info about number of the classes
   bottom=bottom-1.3*height;
   htxclasses=uicontrol( ...
      'Style','text', ...
      'Units','normalized', ...
      'Position',[left bottom width 0.9*height], ...
      'String','# of classes');
   bottom=bottom-height;
   hedclasses = uicontrol(...
    'Units','normalized', ...
      'ListboxTop',0, ...
        'Position',[left bottom width height], ...
      'Style','edit',...
      'String','2');

   % Iterations
   bottom=bottom-1.3*height;
   htxiter=uicontrol( ...
      'Style','text', ...
      'Units','normalized', ...
      'Position',[left bottom width 0.9*height], ...
      'String','Iterations');
   bottom=bottom-height;
   hediter = uicontrol(...
    'Units','normalized', ...
      'ListboxTop',0, ...
        'Position',[left bottom width height], ...
      'Style','edit',...
      'String','1');

   % == CheckBox =========================================================

   % Should the first algorithm step be random or not ?
   bottom=bottom-height*1.3;
    hxbrandom = uicontrol(...
    'Style','checkbox', ...
       'Units','normalized', ...
    'ListboxTop',0, ...
       'Position',[left bottom width height], ...
    'String','Random init');

   %=====================================================================
   % Store handlers
   handlers=struct(...
      'ellipse',struct('handler',-1,'mi',[],'sigma',[],'t',0,'Pk',[],...
        'solution',0),...
      'center',[],...
      'graph1',struct('handler',-1,'loglik',[],'axist',0,'time',[]),...
      'title1',htitle1,...
      'title2',htitle2,...
      'btSaveModel',hbtSaveModel,...%      'btLoadModel',hbtLoadModel,...
      'btstep',hbtstep,...
      'btstop',hbtstop,... 
      'btclose',hbtclose,...
      'btplay',hbtplay,...
      'btreset',hbtreset,...
      'btinfo',hbtinfo,...
      'btload',hbtload,...
      'btcreat',hbtcreat,... %%%      'console',hconsole,...
      'txsteps',htxsteps,...
      'txclasses',htxclasses,...
      'txiter',htxiter,...
      'txfeatures',htxfeatures,...
      'pufeatures',hpufeatures,...
      'editer',hediter,...
      'xbrandom',hxbrandom,...
      'axes1',haxes1,...
      'axes2',haxes2,...
      'edclasses',hedclasses);
   set(hfigure,'UserData',handlers)

   % Reset
   unsudemo('reset',hfigure);

   % Put figure on desktop
   set(hfigure,'Visible','on');
   drawnow;

 case 'savemodel'
   % == Save model ============================================

   h=get(hfigure,'UserData');
   
   if h.ellipse.t == 0,
     errordlg('No model has found yet.','No model to save','modal');
     return;
   end
   
   [name,path]=uiputfile('*.mat','Save model');
   if name ~= 0,
     
     MI=h.ellipse.mi;        % mean values
     SIGMA=h.ellipse.sigma;  % covariance matrices
     Pk=h.ellipse.Pk;        % a-priory probabilities

     solution=h.ellipse.solution;
     steps=h.ellipse.t;      % number of performed steps
     
     I=[1:size(MI,2)];
     N=size(MI,1);
     id=dataid(2);
     K=ones(1,size(MI,2));
     
     save(strcat(path,name),'id','K','N','I',...
         'steps','solution','Pk','SIGMA','MI');
     
   end   
   
 case 'loadmodel'
   % == Load model ============================================

   h=get(hfigure,'UserData');