% learncl.m: competitive learning example with clustering
% copyright (c) 1996 by Yu Hen Hu
% created: 9/3/96
%
% mfiles needed:  datagen1.m
%
clear all, clf
echo on
N=input('# of samples in each cluster = ');
N2=N+N; B1=ceil(N/2); B2=N+B1;
eta=0.2;
means=[.7  -.8
       .7  -.8];
var= [0.2  0.2];
x=datagen1([N N],[means;var]); % x is 2N by 2
x=randomize(x);  % randomize the ordering of clusters
w=rand(2,2)-0.5*ones(2,2);  % both neuron initially at random place
figure(1),subplot(221),plot(x(:,1),x(:,2),'g.',w(:,1),w(:,2),'r*')
title('Initial position')
title('initial')
for i=1:N2,
   if norm(x(i,:)-w(1,:)) < norm(x(i,:)-w(2,:)),
      w(1,:)=w(1,:)+eta*(x(i,:)-w(1,:));
   elseif norm(x(i,:)-w(1,:)) > norm(x(i,:)-w(2,:))
      w(2,:)=w(2,:)+eta*(x(i,:)-w(2,:));
   end
   if i==B1,
      figure(1),subplot(222),plot(x(:,1),x(:,2),'g.',w(:,1),w(:,2),'r*')
      title(['after ' num2str(B1) ' iterations']);drawnow
   end
   if i==B2,
      figure(1),subplot(223),plot(x(:,1),x(:,2),'g.',w(:,1),w(:,2),'r*')
      title(['after ' num2str(B2) ' iterations']);drawnow
   end
end
figure(1),subplot(224),plot(x(:,1),x(:,2),'g.',w(:,1),w(:,2),'r*')
title(['at end of ' num2str(N2) ' iterations'])
echo off