/***********************************************************************
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. S�nchez (luciano@uniovi.es)
J. Alcal�-Fdez (jalcala@decsai.ugr.es)
S. Garc�a (sglopez@ujaen.es)
A. Fern�ndez (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;
import net.sf.jclec.util.range.Interval;
/**
* <p>
* @author Written by Pedro Antonio Gutierrez Penia (University of Cordoba) 16/7/2007
* @param <I> Type of represented individuals
* @version 0.1
* @since JDK1.5
* </p>
*/
public abstract class AbstractNeuralNetSpecies<I extends NeuralNetIndividual> implements INeuralNetSpecies<I>
{
/**
* <p>
* Abstract implementation for INeuralNetSpecies.
* </p>
*/
/////////////////////////////////////////////////////////////////
// --------------------------------------------------- Properties
/////////////////////////////////////////////////////////////////
/** Type of neuralnets */
protected String neuralNetType;
/** Number of inputs of the neural nets */
protected int nOfInputs;
/** Number of hidden layers of the neural nets */
protected int nOfHiddenLayers;
/** Number of outputs */
protected int nOfOutputs;
/** Weight ranges of each LinkedLayer of the neural nets */
protected Interval[][] weightRanges;
/** Maximum number of neurons of each LinkedLayer of the neural nets */
protected int[] maxNofneurons;
/** Minimum number of neurons of each LinkedLayer of the neural nets */
protected int[] minNofneurons;
/** Initial number of neurons of each LinkedLayer of the neural nets */
protected int[] initialMaxNofneurons;
/** Type of each LinkedLayer of the neural nets */
protected String[] type;
/** Initiator of each LinkedLayer of the neural nets */
protected String[] initiator;
/** Boolean indicating if each linked layer of neural nets are biased */
protected boolean[] biased;
/** Types of each neuron for hibrid layers */
protected String[][] neuronTypes;
/** Percentages of each neuron type for hibrid layers */
protected double[][] percentages;
/** Initiator of neurons of each HibridLayer of the neural nets */
protected String[][] initiatorNeuronTypes;
/////////////////////////////////////////////////////////////////
// ------------------------------------------------- Constructors
/////////////////////////////////////////////////////////////////
/**
* <p>
* Empty constructor
* </p>
*/
public AbstractNeuralNetSpecies()
{
super();
}
/////////////////////////////////////////////////////////////////
// ------------ Implementing INeuralNetSpecies interface
/////////////////////////////////////////////////////////////////
/**
* <p>
* Returns a neural net type
*
* @return int Number of hidden layers
* </p>
*/
public String getNeuralNetType() {
return neuralNetType;
}
/**
* <p>
* Returns number of hidden layers of the neural nets
*
* @return int Number of hidden layers
* </p>
*/
public int getNOfHiddenLayers() {
return nOfHiddenLayers;
}
/**
* <p>
* Returns number of inputs of the neural nets
*
* @return int Number of inputs
* </p>
*/
public int getNOfInputs() {
return nOfInputs;
}
/**
* <p>
* Returns number of outputs of the neural nets
*
* @return int Number of outputs
* </p>
*/
public int getNOfOutputs() {
return nOfOutputs;
}
/**
* <p>
* Returns weight range of a hidden layer
*
* @param index Index of the desired hidden layer
* @param indexRange Index of the desired range into the layer (useful for hibrid layer)
*
* @return Interval Weight range
* </p>
*/
public Interval getHiddenLayerWeightRange(int index, int indexRange) {
return weightRanges[index][indexRange];
}
/**
* <p>
* Returns weight range of the output layer
*
* @param indexRange Index of the desired range into the layer (useful for hibrid layer)
*
* @return Interval Weight range
* </p>
*/
public Interval getOutputLayerWeightRange(int indexRange) {
return weightRanges[weightRanges.length-1][indexRange];
}
/**
* <p>
* Returns minimum number of neurons of a hidden layer
*
* @param index Index of the desired hidden layer
*
* @return int Minimum number of neurons
* </p>
*/
public int getHiddenLayerMinNofneurons(int index) {
return minNofneurons[index];
}
/**
* <p>
* Returns maximum number of neurons of a hidden layer
*
* @param index Index of the desired hidden layer
*
* @return int Maximum number of neurons
* </p>
*/
public int getHiddenLayerMaxNofneurons(int index) {
return maxNofneurons[index];
}
/**
* <p>
* Returns initial maximum number of neurons of a hidden layer
*
* @param index Index of the desired hidden layer
*
* @return int Initial maximum number of neurons
* </p>
*/
public int getHiddenLayerInitialMaxNofneurons(int index) {
return initialMaxNofneurons[index];
}
/**
* <p>
* Returns type of neurons of a hidden layer
*
* @param index Index of the desired hidden layer
*
* @return String Type of neurons
* </p>
*/
public String getHiddenLayerType(int index) {
return type[index];
}
/**
* <p>
* Returns type of neurons of the output layer
*
* @return String Type of neurons
* </p>
*/
public String getOutputLayerType() {
return type[type.length-1];
}
/**
* <p>
* Returns initiator of neurons of a hidden layer
*
* @param index Index of the desired hidden layer
*
* @return String Initiator of neurons
* </p>
*/
public String getHiddenLayerInitiator(int index) {
return initiator[index];
}
/**
* <p>
* Returns initiator of neurons of the output layer
*
* @return String Initiator of neurons
* </p>
*/
public String getOutputLayerInitiator() {
return initiator[initiator.length-1];
}
/**
* <p>
* Returns a boolean indicating if a hidden layer is biased
*
* @param index Index of the desired hidden layer
*
* @return boolean Is hidden layer biased?
* </p>
*/
public boolean isHiddenLayerBiased(int index){
return biased[index];
}
/**
* <p>
* Returns a boolean indicating if output layer is biased
*
* @return boolean Is output layer biased?
* </p>
*/
public boolean isOutputLayerBiased(){
return biased[biased.length-1];
}
/**
* <p>
* Returns an array of neuron types of a concrete layer
* (this is an hibrid layer)
*
* @param index Index of the desired hidden layer
*
* @return String[] Array of neurons types
* </p>
*/
public String[] getNeuronTypes(int index) {
return neuronTypes[index];
}
/**
* <p>
* Returns an array of percentages of a concrete layer
* (this is an hibrid layer)
*
* @param index Index of the desired hidden layer
*
* @return double[] Array of percentages
* </p>
*/
public double[] getPercentages(int index) {
return percentages[index];
}
/**
* <p>
* Returns an array of initiators of neurons of hibrid layers
*
* @param index Index of the desired hidden layer
*
* @return String[] Array of percentages
* </p>
*/
public String[] getInitiatorNeuronTypes(int index) {
return initiatorNeuronTypes[index];
}
}