gusucode.com > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM源码程序 > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM\stprtool\learning\unsuper\unsudemo.m
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');
sets=get(h.axes1,'UserData');
% Are data sets loaded ?
if isempty(sets)==1,
% no warning is needy because of the huge topic on the screen:))).
return;
end
[name,path]=uigetfile('*.mat','Load model');
if name ~= 0,
fname=strcat(path,name);
% if checkdat(fname,DATA_IDENT,2,0)==1,
unsudemo('reset',hfigure);
model=load(fname);
if exist('model.Pk')==0,
% suppose uniformly distributed Pk
model.Pk=ones(1,sum(model.K))/sum(model.K);
end
h.ellipse.mi = model.MI;
h.ellipse.sigma=model.SIGMA;
h.ellipse.Pk = model.Pk;
h.ellipse.solution=0;
h.ellipse.t=0;
set(h.edclasses,'String',num2str(sum(model.K)));
h.ellipse.classes=sum(model.K);
h.ellipse.features=get(h.pufeatures,'Value');
set(hfigure,'UserData',h);
unsudemo('step',hfigure);
% else
% errordlg('This file does not contain required data.','Bad file','modal');
% end
end
case 'play'
% == Play ============================================
h=get(hfigure,'UserData');
% get data set
sets=get(h.axes1,'UserData');
% Are data sets loaded ?
if isempty(sets)==1 | h.ellipse.solution==1,
%% text=sprintf(...
%% 'No action performed. No data to work on. Load or create it!');
%% set(h.console,'String',text);
return;
end
% disable button
set([h.editer,h.btstep,h.btclose,h.btplay,...
h.btreset,h.btinfo,h.btload,h.btcreat,h.txiter],...
'Enable','off');
% enable stop button
set(h.btstop,'Enable','on');
% get # of iterations
iter=str2num(get(h.editer,'String'));
% # of classes
if h.ellipse.t==0,
h.ellipse.classes=str2num(get(h.edclasses,'String'));
h.ellipse.features=get(h.pufeatures,'Value');
set([h.xbrandom,h.edclasses,h.txclasses,h.pufeatures,h.txfeatures],...
'Enable','off');
end
% Shall the init be random, yes or no ?
randinit=get(h.xbrandom,'Value');
% set stop button
set(h.btstop,'UserData',0);
% Play - adaptation process
play=1; % flag 1 - not finished, 1 - finished;
while play==1 & get(h.btstop,'UserData')==0,
% perform one learning step
if h.ellipse.features==2, % correlated features
[h.ellipse.mi,h.ellipse.sigma,h.ellipse.Pk,eI,h.ellipse.solution,...
h.ellipse.t]=unsund(sets.X,h.ellipse.classes,iter,randinit,...
h.ellipse.t,h.ellipse.mi, h.ellipse.sigma,h.ellipse.Pk);
else % independent
[h.ellipse.mi,h.ellipse.sigma,h.ellipse.Pk,eI,h.ellipse.solution,...
h.ellipse.t]=unsuni(sets.X,h.ellipse.classes,iter,randinit,...
h.ellipse.t,h.ellipse.mi,h.ellipse.sigma,h.ellipse.Pk);
end
text=sprintf('step number t=%d ',h.ellipse.t);
if h.ellipse.solution==1,
%% text=strvcat(text,'Solution was found.');
text=[text ',solution was found'];
play=0;
set(h.txsteps,'String',text);
else
set(h.txsteps,'String',text);
val= mln(sets.X,h.ellipse.mi,h.ellipse.sigma,h.ellipse.Pk);
text=sprintf('Log-likelihood, logL(t) = %f',val);
set(h.title2,'String',text);
h.graph1.time=[h.graph1.time,h.ellipse.t];
h.graph1.loglik=[h.graph1.loglik,val];
ylimit=get(h.axes2,'YLim');
if ylimit(2) < val,
set(h.axes2,'YLim',[ylimit(1) val+AXISY_ADD]);
end
% is axis to be changed ?
if h.ellipse.t > h.graph1.axist,
h.graph1.axist=h.ellipse.t+iter*AXIST_ADD;
set(h.axes2,'XLim',[1 h.graph1.axist]);
end
set(h.graph1.handler,'XData',h.graph1.time,'YData',h.graph1.loglik,...
'Visible','on');
if h.ellipse.handler==-1,
axes(h.axes1);
end
[h.ellipse.handler,h.center]=...
pnmix(sets.X,h.ellipse.mi,h.ellipse.sigma,eI,h.ellipse.handler,h.center);
end
% comment
%% set(h.console,'String',text);
% store data
set(hfigure,'UserData',h);
% flush it on desktop
drawnow;
end % of while
% dissable button
set([h.editer,h.btstep,h.btclose,h.btplay,...
h.btreset,h.btinfo,h.btload,h.btcreat,h.txiter],...
'Enable','on');
% enable stop button
set(h.btstop,'Enable','off');
% copy the solution to global variables to be visible outside unsudemo
UNSU_MI = h.ellipse.mi;
UNSU_SIGMA = h.ellipse.sigma;
UNSU_PK = h.ellipse.Pk;
UNSU_solution = h.ellipse.solution;
UNSU_t = h.ellipse.t;
case 'step'
% == One step of learning ===========================================
h=get(hfigure,'UserData');
% get data set
sets=get(h.axes1,'UserData');
% are data sets loaded ?
if isempty(sets)==1 | h.ellipse.solution==1,
%%text=sprintf('No action performed. No data to work on. Load or create it!');
%% set(h.console,'String',text);
%% set(h.txsteps,'String',text);
return;
end
% get # of iter
iter=str2num(get(h.editer,'String'));
% # of classes
if h.ellipse.t==0,
h.ellipse.classes=str2num(get(h.edclasses,'String'));
h.ellipse.features=get(h.pufeatures,'Value');
set([h.xbrandom,h.edclasses,h.txclasses,h.pufeatures,h.txfeatures],'Enable','off');
end
% random init yes or no
randinit=get(h.xbrandom,'Value');
% perform one learning step
if h.ellipse.features==2, % correlated
[h.ellipse.mi,h.ellipse.sigma,h.ellipse.Pk,eI,h.ellipse.solution,...
h.ellipse.t]=unsund(sets.X,h.ellipse.classes,iter,randinit,...
h.ellipse.t,h.ellipse.mi,h.ellipse.sigma,h.ellipse.Pk);
else % independent
[h.ellipse.mi,h.ellipse.sigma,h.ellipse.Pk,eI,h.ellipse.solution,...
h.ellipse.t]=unsuni(sets.X,h.ellipse.classes,iter,randinit,...
h.ellipse.t,h.ellipse.mi,h.ellipse.sigma,h.ellipse.Pk);
end
text=sprintf('step number t=%d ',h.ellipse.t);
if h.ellipse.solution==1,
%% text=strvcat(text,'Solution is found.');
text=[text ',solution was found'];
set(h.txsteps,'String',text);
else
set(h.txsteps,'String',text);
val= mln(sets.X,h.ellipse.mi,h.ellipse.sigma,h.ellipse.Pk);
text=sprintf('Log-likelihood, logL(t) = %f',val);
set(h.title2,'String',text);
h.graph1.time=[h.graph1.time,h.ellipse.t];
h.graph1.loglik=[h.graph1.loglik,val];
ylimit=get(h.axes2,'YLim');
if ylimit(2) < val,
set(h.axes2,'YLim',[ylimit(1) val+AXISY_ADD]);
end
% is axis to be changed ?
if h.ellipse.t > h.graph1.axist,
h.graph1.axist=h.ellipse.t+iter*AXIST_ADD;
set(h.axes2,'XLim',[1 h.graph1.axist]);
end
set(h.graph1.handler,'XData',h.graph1.time,'YData',h.graph1.loglik,...
'Visible','on');
if h.ellipse.handler==-1,
axes(h.axes1);
end
[h.ellipse.handler,h.center]=...
pnmix(sets.X,h.ellipse.mi,h.ellipse.sigma,eI,h.ellipse.handler,h.center);
end
% comment
%% set(h.console,'String',text);
% flush it on desktop
drawnow;
set(hfigure,'UserData',h);
% copy the solution to global variables to be visible outside unsudemo
UNSU_MI = h.ellipse.mi;
UNSU_SIGMA = h.ellipse.sigma;
UNSU_PK = h.ellipse.Pk;
UNSU_solution = h.ellipse.solution;
UNSU_t = h.ellipse.t;
case 'getfile'
% == Invoke standard open file dialog ====================================
% Opens file and checks if contains apropriate data, if yes than loads data.
h=get(hfigure,'UserData');
% change path to directory
%% wres=what('unsuper');
%% cd(wres.path);
[name,path]=uigetfile('*.mat','Open file');
if name~=0,
file.pathname=strcat(path,name);
file.path=path;
file.name=name;
if checkdat(file.pathname,DATA_IDENT,2,0)==1,
set(h.btload,'UserData',file);
unsudemo('loadsets',hfigure);
else
errordlg('This file does not contain required data.','Bad file','modal');
end
end
case 'loadsets'
% == Load sets ==================================================================
% Get file name from the pop up menu according to menu pointer.
h=get(hfigure,'UserData');
% Get file name with sets
file=get(h.btload,'UserData');
% Load sets
sets=load(file.pathname);
% store loaded sets
set(h.axes1,'UserData',sets);
% call reset
unsudemo('reset',hfigure);
drawnow;
case 'reset'
% == Reset adaptation process, set up t=0 ================
h=get(hfigure,'UserData'); % get handlers
% get file
file=get(h.btload,'UserData');
% get data set
sets=get(h.axes1,'UserData');
% zeroes parameters of the separation line
h.ellipse.mi=[];
h.ellipse.sigma=[];
h.ellipse.t=0;
h.ellipse.Pk=[];
h.center=-1;
h.ellipse.handler=-1;
h.ellipse.solution=0;
h.graph1.time=[];
h.graph1.axist=0;
h.graph1.loglik=[];
% clear axes prob.
clrchild(h.axes2);
axes(h.axes2);
%% setaxis(h.axes2,[0 1 0 1]);
axis auto;
h.graph1.handler=plot([0],[0],'b','Parent',h.axes2,...
'EraseMode','background','Visible','off');
% store h
set(hfigure,'UserData',h);
% enable Edit Line 'classes'
set([h.xbrandom,h.edclasses,h.txclasses,h.pufeatures,h.txfeatures],'Enable','on');
% comment
text=sprintf('Log-likelihood, logL(t)');
set(h.title2,'String',text);
text=sprintf('step number t=0. ');
set(h.txsteps,'String',text);
% clears axes
set(get(h.axes1,'Children'),'EraseMode','normal');
%%% cla;
clrchild(h.axes1);
drawnow;
% set axes and plot mixture
axes(h.axes1);
if isempty(sets)==0,
win=cmpwin(min(sets.X'),max(sets.X'),BORDER,BORDER);
%%% axis(win);
setaxis(h.axes1,win);
%% axes(h.axes1);
ppoints(sets.X,sets.I);
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% create comment
if isempty(sets)==0,
set(h.title1,'String',sprintf('File: %s, # of points K = %d',file.name,sum(sets.K)));
else
set(h.title1,'String','No data loaded');
pos=get(h.axes1,'Position');
fsize=min(pos(3),pos(4))/7;
setaxis(h.axes1,[-1 1 -1 1]);
builtin('text',0,0,'Press ''Load data'' button.',...
'Parent',h.axes1,...
'HorizontalAlignment','center',...
'FontUnits','normalized',...
'Clipping','on',...
'FontSize',fsize);
end
drawnow;
case 'creatdata'
% == Invoke data set creator ============================================
creatset('finite',10,'unsudemo','created',hfigure);
case 'created'
% == Load new created data set ===========================================
% get handler and make this figure active
figure(hfigure);
h=get(hfigure,'UserData');
% get file name
path=varargin{1};
name=varargin{2};
pathname=strcat(path,name);
if checkdat(pathname,DATA_IDENT,2,0)==1,
file.pathname=pathname;
file.path=path;
file.name=name;
set(h.btload,'UserData',file);
unsudemo('loadsets',hfigure);
else
errordlg('This file does not contain required data.','Bad file','modal');
end
case 'info'
% == Call standard Matlab`s info box =========================================
helpwin(mfilename);
end % of switch