%% Sample training script for using Matlab's built-in RBF functions

% Synthetic data:  Two dimensional sine wave.  First, we'll take a look at
% the data (no changes need to be made here)
[X,Y]=meshgrid(-1:0.1:8);
Z=sin(X/4).*sin(Y/2);
figure(1);
surf(X,Y,Z);
title('Original surface before noise');


%Training stuff here:

Patterns=9*rand(2,300)-1;  %Dimension x Number of Points for newrb
Targets=sin(Patterns(1,:)/4).*sin(Patterns(2,:)/2)+0.01*randn(size(Patterns(1,:)));
goal=0.1;
spread=1.0;
MaxCenters=200;
DisplayRate=10;  %Redo the graph every 10 iterations
net=newrb(Patterns,Targets,goal,spread,MaxCenters,DisplayRate);


% Plotting routines again:
[mm,nn]=size(X);
Xtest=[X(:)';Y(:)'];
Zout=sim(net,Xtest);
Zout=reshape(Zout,mm,nn);
figure(2)
surf(X,Y,Zout);
title('Modeled surface');

%
% Manually performing the simulation of the network:
%  This shows you what Matlab's "net" structure holds
%

Centers=net.IW{1,1};
Weights=net.LW{2,1};
spr=net.b{1}(1);
bias=net.b{2};
A=radbas(dist(Xtest',Centers').*spr);
Zout2=A*Weights'+bias;