da_pcavr.m

王小平《遗传算法——理论、应用与软件实现》随书光盘

%
% da_pcavr
%
% Plots the variance of the individual prinipal
% components
%

w1=gcf;
da_front;
da_pcapb;
set(w1,'NumberTitle','off','Name','Principal Component Analysis');
drawnow;

figure(w1);
ax1=axes(...
	'Units','pixels',...
	'Position',[80 120 500 270],...
	'Box','on',...
	'Color',[0 0 0],...
	'Visible','on');

%
% Print a title
%
text1=da_text(w1,200,410,250,15,'Plot of principal component variances',[1 1 1],[1 0 0]);
%
% Plot the contribution to a model plot
%
%bar(ssq(:,4));
%
% Own PCA routine
%
bar(ssq);

[D L]=size(ssq);
set(ax1,'Xlim',[0 D],'Ylim',[0 100]);
Xlabel('Principal component number');
Ylabel('Percentage variation in original data explained');


%
% Save coefficients button
%
but10=uicontrol(w1,...
	'style','push',...
	'position',[20 40 175 20],...
	'string','Save loadings',...
	'callback',[
		'dummy=pcincl(data,include_var,output_var);',...
		'[dummy m s]=mcen(dummy);',...
		'clear dummy;',...
		'svpca('''',include_var,m,s,c);']);