/*
* Encog(tm) Core v3.0 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2011 Heaton Research, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.platformspecific.j2se;
import java.awt.BorderLayout;
import java.awt.Container;
import java.awt.GridLayout;
import java.awt.event.ActionEvent;
import java.awt.event.ActionListener;
import javax.swing.JButton;
import javax.swing.JDialog;
import javax.swing.JLabel;
import javax.swing.JPanel;
import org.encog.ml.data.MLDataSet;
import org.encog.ml.train.MLTrain;
import org.encog.neural.networks.BasicNetwork;
import org.encog.neural.networks.training.propagation.Propagation;
import org.encog.neural.networks.training.propagation.resilient.ResilientPropagation;
import org.encog.util.Format;
import org.encog.util.simple.EncogUtility;
/**
* Display a training dialog.
*/
public class TrainingDialog extends JDialog implements ActionListener {
/**
* The serial id.
*/
private static final long serialVersionUID = -6847676575773420316L;
/**
* Holds the current error.
*/
private JLabel labelError;
/**
* Holds the iteration count.
*/
private JLabel labelIterations;
/**
* Holds the current total training time.
*/
private JLabel labelTime;
/**
* The stop button.
*/
private JButton buttonStop;
/**
* Set to true if the network should stop after the current iteration.
*/
private boolean shouldStop = false;
/**
* Construct the training dialog.
*/
public TrainingDialog() {
this.setSize(320, 100);
setTitle("Training");
final Container content = getContentPane();
content.setLayout(new BorderLayout());
final JPanel statsPanel = new JPanel();
statsPanel.setLayout(new GridLayout(3, 2));
statsPanel.add(new JLabel("Current Error:"));
statsPanel.add(this.labelError = new JLabel("Starting..."));
statsPanel.add(new JLabel("Iterations:"));
statsPanel.add(this.labelIterations = new JLabel(""));
statsPanel.add(new JLabel("Training Time:"));
statsPanel.add(this.labelTime = new JLabel(""));
content.add(this.buttonStop = new JButton("Stop"), BorderLayout.SOUTH);
content.add(statsPanel, BorderLayout.CENTER);
this.buttonStop.addActionListener(this);
}
/**
* Called when the user clicks the stop button.
* @param e The action event.
*/
public void actionPerformed(final ActionEvent e) {
if (e.getSource() == this.buttonStop) {
this.buttonStop.setEnabled(false);
this.buttonStop.setText("Stopping...");
this.shouldStop = true;
}
}
/**
* Set the current error.
* @param e The current error.
*/
public void setError(final double e) {
this.labelError.setText(Format.formatPercent(e));
}
/**
* Set the number of iterations.
* @param iteration The current iteration.
*/
public void setIterations(final int iteration) {
this.labelIterations.setText(Format.formatInteger(iteration));
}
/**
* Set the time.
* @param seconds The time in seconds.
*/
public void setTime(final int seconds) {
this.labelTime.setText(Format.formatTimeSpan(seconds));
}
/**
* @return True if training should stop after current iteration.
*/
public boolean shouldStop() {
return this.shouldStop;
}
/**
* Train, using the specified training method, display progress to a dialog
* box.
*
* @param train
* The training method to use.
* @param network
* The network to train.
* @param trainingSet
* The training set to use.
*/
public static void trainDialog(final MLTrain train,
final BasicNetwork network, final MLDataSet trainingSet) {
final TrainingDialog dialog = new TrainingDialog();
dialog.setVisible(true);
final long start = System.currentTimeMillis();
do {
train.iteration();
int iteration = train.getIteration();
final long current = System.currentTimeMillis();
final long elapsed = (current - start) / 1000;// seconds
dialog.setIterations(iteration);
dialog.setError(train.getError());
dialog.setTime((int) elapsed);
} while (!dialog.shouldStop());
train.finishTraining();
dialog.dispose();
}
/**
* Train using SCG and display progress to a dialog box.
*
* @param network
* The network to train.
* @param trainingSet
* The training set to use.
*/
public static void trainDialog(final BasicNetwork network,
final MLDataSet trainingSet) {
final Propagation train = new ResilientPropagation(network, trainingSet);
train.setNumThreads(0);
TrainingDialog.trainDialog(train, network, trainingSet);
}
}