pdiscrim.m~

该工具箱是用于统计模式识别的

function pdiscrim( D, X, Y, background, linestyle )
% PDISCRIM plot discriminat functions regions in 2D.
% pdiscrim( D, X, Y )
%
% Input:
%  D [m x n] value of discriminat function in the binary case or
%   D [c x (m*n)] values of discriminant functions for all the 
%    classes in the multi-class case.
%  X [1 x m] values of x-axis.
%  Y [1 x n] values of y-axis, e.g. X=[1:10], Y=[1:10] (mash 10x10).
% 

% Modifications:
% 23-sep-2002, VF
% 21-may-2001, V.Franc, created

if nargin < 4, 
  background = 1;
end

if nargin < 5,
  linestyle = 'k';
end


dx=X(2)-X(1);
dy=Y(2)-Y(1);

m = size( X, 2 );
n = size( Y, 2 );

Z = -inf*ones( m+2, n+2 );

nclass = size(D,1);

if lenght( size( D )) == 2,
  
   A=D;
   l=(-min(A)+max(A))/2;

   A = reshape( A', m, n );   
  
   if background,
     phandle = pcolor(X,Y,A');
     shading interp;
   end
  
   contour(X,Y,A',[0 0],linestyle);  

   if background,
     set(phandle, 'LineStyle','none' );
     set(gca,'Clim',[-l l]);
     load cmp1;
     colormap( cmp );
   end
  
elseif nclass == 2,

   A=D(1,:) - D(2,:);
   l=(-min(A)+max(A))/2;

   A = reshape( A', m, n );   
  
   if background,
     phandle = pcolor(X,Y,A');
     shading interp;
   end
  
   contour(X,Y,A',[0 0],linestyle);  

   if background,
     set(phandle, 'LineStyle','none' );
     set(gca,'Clim',[-l l]);
     load cmp1;
     colormap( cmp );
   end
  
else

  for i = 1: nclass,
  
    A = D(i,:) - max(D(find([1:nclass] ~= i),:));
    A = reshape( A', m, n );
  
    Z(2:end-1,2:end-1) = A;  
  
    [cc,h] = contour([X(1)-dx,X,X(end)+dx],[Y(1)-dy,Y,Y(end)+dy],Z',[0 0],...
     linestyle);  

    if background,
     while ~isempty(cc)
       len = cc(2,1);
       fill(cc(1,2:len+1),cc(2,2:len+1),color(i));
 	  cc(:,1:len+1) = [];
     end  
    end
  
  end
end

return;