load Data6;
X=XX{1};
[mm,nn]=size(X);
P=X';
clear XX group_num X;

net = newsom([0 1; 0 1],[5 6]);
plotsom(net.iw{1,1},net.layers{1}.distances)
pause

net.trainParam.epochs = 25;
net.trainParam.show=1;
net = train(net,P);
plotsom(net.iw{1,1},net.layers{1}.distances)
hold on
plot(P(1,:),P(2,:),'k.');
hold off

fprintf('Result of training\n\n');
pause

voronoi(net.IW{1,1}(:,1),net.IW{1,1}(:,2));
hold on
plot(P(1,:),P(2,:),'r.');
hold off

fprintf('To find which cluster data belongs to, use sim\n\n');
echo on
T=sim(net,P);
T(:,1)
T(:,2)
echo off

%How many data points are there per cluster?
Total=zeros(30,1);
for j=1:299
    idx=find(T(:,j)~=0);
    Total(idx)=Total(idx)+1;
end
fprintf('The mean number of data points per cluster: %f\n',mean(Total));
fprintf('The theoretical mean number of data points per cluster: 299/30\n\n');