Java tutorial
/*********************************************************************** This file is part of KEEL-software, the Data Mining tool for regression, classification, clustering, pattern mining and so on. Copyright (C) 2004-2010 F. Herrera (herrera@decsai.ugr.es) L. Snchez (luciano@uniovi.es) J. Alcal-Fdez (jalcala@decsai.ugr.es) S. Garca (sglopez@ujaen.es) A. Fernndez (alberto.fernandez@ujaen.es) J. Luengo (julianlm@decsai.ugr.es) This program 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 3 of the License, or (at your option) any later version. This program 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 this program. If not, see http://www.gnu.org/licenses/ **********************************************************************/ package keel.Algorithms.Neural_Networks.NNEP_Common.neuralnet; import java.util.ArrayList; import javolution.xml.XmlElement; import javolution.xml.XmlFormat; import org.apache.commons.lang.builder.HashCodeBuilder; /** * <p> * @author Written by Pedro Antonio Gutierrez Penya, Aaron Ruiz Mora (University of Cordoba) 17/07/2007 * @version 0.1 * @since JDK1.5 * </p> */ public class InputLayer implements ILayer<InputNeuron> { /** * <p> * Input layer of a neural net * </p> */ ///////////////////////////////////////////////////////////////// // ------------------------------------- Marshal/unmarshal format ///////////////////////////////////////////////////////////////// /** * <p> * Marshal/Unmarshal maximum number of neurons and each neuron * </p> */ protected static final javolution.xml.XmlFormat<InputLayer> XML = new XmlFormat<InputLayer>(InputLayer.class) { public void format(InputLayer source, XmlElement xml) { // Marshal maxnofneurons xml.setAttribute("max-n-of-neurons", source.maxnofneurons); // Marshal each neuron xml.add(source.neurons, "neurons"); } public InputLayer parse(XmlElement xml) { // Resulting object InputLayer result = (InputLayer) xml.object(); // Unmarshal maxnofneurons result.maxnofneurons = xml.getAttribute("max-n-of-neurons", 1); // Unmarshal each neuron result.neurons = xml.<ArrayList<InputNeuron>>get("neurons"); // Return result return result; } public String defaultName() { return "input-layer"; } }; ///////////////////////////////////////////////////////////////// // --------------------------------------- Serialization constant ///////////////////////////////////////////////////////////////// /** Generated by Eclipse */ private static final long serialVersionUID = -4960947669851010992L; ///////////////////////////////////////////////////////////////// // --------------------------------------------------- Attributes ///////////////////////////////////////////////////////////////// /** Maximum number of neurons */ protected int maxnofneurons; /** Array of neurons of the layer */ protected ArrayList<InputNeuron> neurons = new ArrayList<InputNeuron>(); ///////////////////////////////////////////////////////////////// // ------------------------------------------------- Constructors ///////////////////////////////////////////////////////////////// /** * Empty constructor */ public InputLayer() { super(); } ///////////////////////////////////////////////////////////////// // -------------------------------- Implementing ILayer interface ///////////////////////////////////////////////////////////////// /** * <p> * Returns the maximum number of neurons of this layer * </p> * @return int Maximum number of neurons */ public int getMaxnofneurons() { return maxnofneurons; } /** * <p> * Sets the maximum number of neurons of this layer * </p> * @param maxnofneurons Number of neurons */ public void setMaxnofneurons(int maxnofneurons) { this.maxnofneurons = maxnofneurons; //Remove the neurons if (neurons != null) neurons.clear(); //Generate the neurons for (int i = 0; i < maxnofneurons; i++) { InputNeuron iNeuron = new InputNeuron(); iNeuron.setIndex(i); addNeuron(iNeuron); } } /** * <p> * Add a neuron to the layer * </p> * @param neuron New neuron to add to the layer */ public void addNeuron(InputNeuron neuron) { neurons.add(neuron); } /** * <p> * Returns a neuron of the layer using its index * </p> * @param index Index of the neuron * @return InputNeuron Neuron of the layer */ public InputNeuron getNeuron(int index) { return neurons.get(index); } /** * <p> * Returns the number of neurons of this layer * </p> * @return int Number of neurons */ public int getNofneurons() { return neurons.size(); } /** * <p> * Returns the index of a neuron in the layer * </p> * @param neuron Neuron in the layer * @return int Index of the neuron */ public int indexOf(InputNeuron neuron) { return neurons.indexOf(neuron); } /** * <p> * Checks if this layer is equal to another * </p> * @param other Other layer to compare * @return true if both layers are equal */ public boolean equals(ILayer<InputNeuron> other) { if (this.hashCode() != other.hashCode()) return false; else return true; } /** * <p> * Returns an integer number that identifies the layer * </p> * @return int Hashcode */ public int hashCode() { HashCodeBuilder hcb = new HashCodeBuilder(41, 43); for (INeuron neuron : neurons) hcb.append(neuron); return hcb.toHashCode(); } ///////////////////////////////////////////////////////////////// // ----------------------------------------------- Public methods ///////////////////////////////////////////////////////////////// /** * <p> * Returns a copy of this input layer * </p> * @return InputLayer Copy of this input layer */ public InputLayer copy() { // Copy result InputLayer result = new InputLayer(); // Set max of neurons result.setMaxnofneurons(this.maxnofneurons); // Return result return result; } }