Java Question

NerfNerder · 25-04-2009 9:29pm #1

I have a program that I was provided with, which is an example of a neural net. I just need to know what a section of code means. I have highlighted the code I need to understand in red. If anyone could help it would be appreciated. Many thanks.

import javax.swing.*;
import java.awt.*;
import java.awt.event.*;
import java.text.*;
/**
* XorExample
* Copyright 2005 by Jeff Heaton(jeff@jeffheaton.com)
*
* Example program from Chapter 3
* Programming Neural Networks in Java
* http://www.heatonresearch.com/articles/series/1/
*
* This software is copyrighted. You may use it in programs
* of your own, without restriction, but you may not
* publish the source code without the author's permission.
* For more information on distributing this code, please
* visit:
* http://www.heatonresearch.com/hr_legal.php
*
* @author Jeff Heaton
* @version 1.1
*/
public class XorExample extends JFrame implements
ActionListener,Runnable {
/**
* The train button.
*/
JButton btnTrain;
/**
* The run button.
*/
JButton btnRun;
/**
* The quit button.
*/
JButton btnQuit;
/**
* The status line.
*/
JLabel status;
/**
* The background worker thread.
*/
protected Thread worker = null;
/**
* The number of input neurons.
*/
protected final static int NUM_INPUT = 2;
/**
* The number of output neurons.
*/
protected final static int NUM_OUTPUT = 1;
/**
* The number of hidden neurons.
*/
protected final static int NUM_HIDDEN = 3;
/**
* The learning rate.
*/
protected final static double RATE = 0.5;
/**
* The learning momentum.
*/
protected final static double MOMENTUM = 0.7;

/**
* The training data that the user enters.
* This represents the inputs and expected
* outputs for the XOR problem.
*/
protected JTextField data[][] = new JTextField[4][4];
/**
* The neural network.
*/
protected Network network;

/**
* Constructor. Setup the components.
*/
public XorExample()
{
setTitle("XOR Solution");
network = new Network(
NUM_INPUT,
NUM_HIDDEN,
NUM_OUTPUT,
RATE,
MOMENTUM);
Container content = getContentPane();
GridBagLayout gridbag = new GridBagLayout();
GridBagConstraints c = new GridBagConstraints();
content.setLayout(gridbag);
c.fill = GridBagConstraints.NONE;
c.weightx = 1.0;
// Training input label
c.gridwidth = GridBagConstraints.REMAINDER; //end row
c.anchor = GridBagConstraints.NORTHWEST;
content.add(
new JLabel(
"Enter training data:"),c);
JPanel grid = new JPanel();
grid.setLayout(new GridLayout(5,4));
grid.add(new JLabel("IN1"));
grid.add(new JLabel("IN2"));
grid.add(new JLabel("Expected OUT "));
grid.add(new JLabel("Actual OUT"));
for ( int i=0;i<4;i++ ) {
int x = (i&1);
int y = (i&2)>>1;
grid.add(data[0] = new JTextField(""+y));
grid.add(data[1] = new JTextField(""+x));
grid.add(data[2] = new JTextField(""+(x^y)));
grid.add(data[3] = new JTextField("??"));
data[0].setEditable(false);
data[1].setEditable(false);
data[3].setEditable(false);
}
content.add(grid,c);
// the button panel
JPanel buttonPanel = new JPanel(new FlowLayout());
buttonPanel.add(btnTrain = new JButton("Train"));
buttonPanel.add(btnRun = new JButton("Run"));
buttonPanel.add(btnQuit = new JButton("Quit"));
btnTrain.addActionListener(this);
btnRun.addActionListener(this);
btnQuit.addActionListener(this);
// Add the button panel
c.gridwidth = GridBagConstraints.REMAINDER; //end row
c.anchor = GridBagConstraints.CENTER;
content.add(buttonPanel,c);
// Training input label
c.gridwidth = GridBagConstraints.REMAINDER; //end row
c.anchor = GridBagConstraints.NORTHWEST;
content.add(
status = new JLabel("Click train to begin training..."),c);
// adjust size and position
pack();
Toolkit toolkit = Toolkit.getDefaultToolkit();
Dimension d = toolkit.getScreenSize();
setLocation(
(int)(d.width-this.getSize().getWidth())/2,
(int)(d.height-this.getSize().getHeight())/2 );
setDefaultCloseOperation(WindowConstants.DISPOSE_ON_CLOSE);
setResizable(false);
btnRun.setEnabled(false);
}
/**
* The main function, just display the JFrame.
*
* @param args No arguments are used.
*/
public static void main(String args[])
{
(new XorExample()).show(true);
}
/**
* Called when the user clicks one of the three
* buttons.
*
* @param e The event.
*/
public void actionPerformed(ActionEvent e)
{
if ( e.getSource()==btnQuit )
System.exit(0);
else if ( e.getSource()==btnTrain )
train();
else if ( e.getSource()==btnRun )
evaluate();
}
/**
* Called when the user clicks the run button.
*/
protected void evaluate()
{
double xorData[][] = getGrid();
int update=0;
for (int i=0;i<4;i++) {
NumberFormat nf = NumberFormat.getInstance();
double d[] = network.computeOutputs(xorData);
data[3].setText(nf.format(d[0]));
}
}

/**
* Called when the user clicks the train button.
*/
protected void train()
{
if ( worker != null )
worker = null;
worker = new Thread(this);
worker.setPriority(Thread.MIN_PRIORITY);
worker.start();
}
/**
* The thread worker, used for training
*/
public void run()
{
double xorData[][] = getGrid();
double xorIdeal[][] = getIdeal();
int update=0;
int max = 10000;
for (int i=0;i<max;i++) {
for (int j=0;j<xorData.length;j++) {
network.computeOutputs(xorData[j]);
network.calcError(xorIdeal[j]);
network.learn();
}

update++;
if (update==100) {
status.setText( "Cycles Left:" + (max-i) + ",Error:" + network.getError(xorData.length) );
update=0;
}
}
btnRun.setEnabled(true);
}

/**
* Called to generate an array of doubles based on
* the training data that the user has entered.
*
* @return An array of doubles
*/
double [][]getGrid()
{
double array[][] = new double[4][2];
for ( int i=0;i<4;i++ ) {
array[0] =
Float.parseFloat(data[0].getText());
array[1] =
Float.parseFloat(data[1].getText());
}
return array;
}
/**
* Called to the the ideal values that that the neural network
* should return for each of the grid training values.
*
* @return The ideal results.
*/
double [][]getIdeal()
{
double array[][] = new double[4][1];
for ( int i=0;i<4;i++ ) {
array[0] =
Float.parseFloat(data[2].getText());
}
return array;
}

}