functioncache.java

利用Java实现的神经网络工具箱

/*
 * FunctionCache.java	1.0 09 Jun 2004
 *
 * NeuralNetworkToolkit
 * Copyright (C) 2004 Universidade de Bras�lia
 *
 * This file is part of NeuralNetworkToolkit.
 *
 * NeuralNetworkToolkit is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2 of the License, or
 * (at your option) any later version.
 *
 * NeuralNetworkToolkit is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with NeuralNetworkToolkit; if not, write to the Free Software
 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA - 02111-1307 - USA.
 */

package neuralnetworktoolkit.activationfunctions;

import java.io.Serializable;
import java.util.Vector;

/**
 * Class that implements some technics for activation functions
 * instances management. The intention is that various activation
 * functions can be used in different points of the neural network,
 * without unnecessary instances.
 * 
 * @version 1.0 09 Jun 2004
 * 
 * @author <a href="mailto:[e-mail]">Hugo Iver V. Gon�alves</a>
 * @author <a href="mailto:[e-mail]">Rodrigo C. M. Coimbra</a>
 */
public class FunctionCache implements IFunctionCache, Serializable {

	/** Store the activation functions. */
	private Vector              activationFunctions;
	/** An activation function to be stored. */
	private IActivationFunction newFunction;

	/**
	 * Creates a new activation functions cache.
	 */
	public FunctionCache() {
		activationFunctions = new Vector();
		
	} //FunctionCache()

	/* (non-Javadoc)
	 * @see neuralnetworktoolkit.IFunctionCache#addActivationFunction(java.lang.String)
	 */
	public void addActivationFunction(String function) {
		// TODO Remake this implementation.
		if ((activationFunctions.size() > 0) && (isIn(function) == true)) {
			// TODO Throw a exception.
		} else {

			if (function.compareTo("Logistic") == 0) {
				newFunction = new Logistic();
			} else if (function.compareTo("Tanh") == 0) {
				newFunction = new Tanh();
			} else if (function.compareTo("Xcube") == 0) {
				newFunction = new Xcube();
			} else if (function.compareTo("Xsquare") == 0) {
				newFunction = new Xsquare();
			} else if (function.compareTo("X") == 0) {
				newFunction = new X();
			} else if (function.compareTo("Exp") == 0) {
				newFunction = new Exp();
			} else if (function.compareTo("Step") == 0) {
				newFunction = new Step();
			} else if (function.compareTo("Sin") == 0) {
				newFunction = new Sin();
			}
			activationFunctions.addElement(newFunction);

		}

	} //addActivationFunction()

	/* (non-Javadoc)
	 * @see neuralnetworktoolkit.IFunctionCache#removeActivationFunction(java.lang.String)
	 */
	public void removeActivationFunction(String function) {
		IActivationFunction in;

		for (int i = 0; i < activationFunctions.size(); i++) {
			in = (IActivationFunction) activationFunctions.elementAt(i);
			if (function.compareTo(in.getFunctionName()) == 0) {
				activationFunctions.remove(i);
			}
		}

	} //removeActivationFunction()

	/* (non-Javadoc)
	 * @see neuralnetworktoolkit.IFunctionCache#getActivationFunction(java.lang.String)
	 */
	public IActivationFunction getActivationFunction(String function) {
		// TODO Remake this implementation.
		int i = 0;
		IActivationFunction in = null;

		do {
			in = (IActivationFunction) activationFunctions.elementAt(i);
			i++;
		} while (function.compareTo(in.getFunctionName()) != 0);

		return in;
		
	} //getActivationFunction()

	private boolean isIn(String function) {
		boolean result = false;
		int i = 0;
		IActivationFunction in;

		while ((result == false)&&(i<activationFunctions.size())) {
			in = (IActivationFunction) activationFunctions.elementAt(i);
			if (function.compareTo(in.getFunctionName()) == 0) {
				result = true;
			}
			i++;

		}

		return result;
		
	} //isIn()

} //FunctionCache