www.pudn.com > osu_svm3.00.zip > SVMPlot.m

function SVMPlot(AlphaY, SVs, Bias, Parameters,Samples, Labels, nSV, nLabel, aspect,mag,xaxis,yaxis,input) 
% USAGE: 
%   SVMPlot(AlphaY, SVs, Bias, Parameters,Samples, Labels, nSV, nLabel 
%   SVMPlot(AlphaY, SVs, Bias, Parameters,Samples, Labels, nSV, nLabel, aspect,mag,xaxis,yaxis,input) 
% 
% DESCRIPTION: 
%  Plot a 2-class Support Vector classifier with some labelled samples. 
% 
% INPUTS: 
%  AlphaY: Alpha * Y, where Alpha is the non-zero Lagrange Coefficients 
%                    Y is the corresponding labels. 
%  SVs: support vectors. That is, the patterns corresponding the non-zero 
%       Alphas. 
%  Bias: the bias in the decision function, which is AlphaY*Kernel(SVs',x)-Bias. 
%  Parameters:the paramters required by the training algorithm.  
%  Samples: all the training patterns. (a row of column vectors) 
%  Labels:  the corresponding class labels for the training patterns in Samples. 
%         where Labels(i) in {1, -1}. (a row vector) 
%  nSV       -  numbers of SVs in each class, 1xL; 
%  nLabel    -  Labels of each class, 1xL. 
%  aspect: Aspect Ratio (default: 0 (fixed), 1 (variable)) 
%  mag: display magnification  (default: 0.1) (kind of side margin) 
%  xaxis: xaxis input (default: 1) 
%  yaxis: yaxis input (default: 2) 
%  input: vector of input values (default: zeros(no_of_inputs)) 
% 
%  By Junshui Ma 
 
if (nargin < 8 | nargin > 13) % check correct number of arguments 
   help SVMPlot; 
   return; 
else 
   if (nLabel > 12)  
       disp(['This function can only maximally display a 12-class problem']); 
       return; 
   end 
   Symbol = {'bd','r<', 'b*', 'rx', 'bs', 'rv', 'b^', 'r+', 'b>', 'rp', 'bh', 'gx'}; 
    
 
   epsilon = 1e-5;   
   if (nargin < 13) input = zeros(size(Samples,1),1);, end 
   %if (nargin < 13) input = mean(Samples,2);, end 
   if (nargin < 12) yaxis = 2;, end 
   if (nargin < 11) xaxis = 1;, end 
   if (nargin < 10) mag = 0.1;, end 
   if (nargin < 9) aspect = 0;, end 
     
   % Scale the axes 
   xmin = min(Samples(xaxis,:)); 
   xmax = max(Samples(xaxis,:));  
    
   ymin = min(Samples(yaxis,:)); 
   ymax = max(Samples(yaxis,:)); 
    
   xa = (xmax - xmin); 
   ya = (ymax - ymin); 
   if (~aspect) 
       if (0.75*abs(xa) < abs(ya))  
          offadd = 0.5*(ya*4/3 - xa);,  
          xmin = xmin - offadd - mag*0.5*ya; 
          xmax = xmax + offadd + mag*0.5*ya; 
          ymin = ymin - mag*0.5*ya; 
          ymax = ymax + mag*0.5*ya; 
       else 
          offadd = 0.5*(xa*3/4 - ya);,  
          xmin = xmin - mag*0.5*xa; 
          xmax = xmax + mag*0.5*xa; 
          ymin = ymin - offadd - mag*0.5*xa; 
          ymax = ymax + offadd + mag*0.5*xa; 
       end 
    else 
       xmin = xmin - mag*0.5*xa; 
       xmax = xmax + mag*0.5*xa; 
       ymin = ymin - mag*0.5*ya; 
       ymax = ymax + mag*0.5*ya; 
    end 
     
    set(gca,'XLim',[xmin xmax],'YLim',[ymin ymax]);   
 
    % Plot function value 
 
    [x,y] = meshgrid(xmin:(xmax-xmin)/50:xmax,ymin:(ymax-ymin)/50:ymax);  
 
	z = ones(size(x)); 
    OutLabels = ones(size(x)); 
    Inputs = input*ones(1,size(x,2)); 
 
    wh = waitbar(0,'Plotting...'); 
    for x1 = 1 : size(x,1) 
       Inputs(xaxis,:) = x(x1,:); 
       Inputs(yaxis,:) = y(x1,:); 
       [OutLabels(x1,:), z(x1,:)]= SVMClass(Inputs,AlphaY, SVs, Bias,Parameters, nSV, nLabel); 
       waitbar((x1)/size(x,1)); 
    end 
    close(wh); 
     
    sp = pcolor(x,y,OutLabels); 
    shading interp;   
    set(sp,'LineStyle','none'); 
    %set(gca,'Clim',[-l  l],'Position',[0 0 1 1]); 
    set(gca,'Clim',[min(min(OutLabels))  max(max(OutLabels))],'Position',[0 0 1 1]); 
    axis off; 
    load cmap; 
    colormap(colmap); 
 
    % Plot Training points 
 
   hold on 
   for i = 1:length(Labels) 
       for j=1:length(nLabel) 
           if Labels(i) == nLabel(j) 
               plot(Samples(xaxis,i),Samples(yaxis,i), Symbol{j}); 
               break; 
           end 
       end 
   end 
    
   for i = 1:length(AlphaY)  
      plot(SVs(xaxis,i),SVs(yaxis,i),'wo');    % Support Vector 
   end 
    
   hold off 
end