inputlayer.java

JaNet: Java Neural Network Toolkit resume: A well documented toolkit for designing and training, a

////////////////////////////////////////////////////////////////////////////////////  
//  
//  Copyright (C) 1996 L.  Patocchi & W.Gander
//
//  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 2 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, write to the Free Software  Foundation, Inc., 675 Mass
//  Ave, Cambridge, MA 02139, USA.
//
//  Contacts:
//  
//    Project Supervisor
//      W.Hett       [e-mail]
//  
//    Authors
//      W.Gander     [e-mail]
//      L.Patocchi   [e-mail]
//
//  Documentation can be found at:
//
//      http://www.isbiel.ch/Projects/janet/index.html
//
////////////////////////////////////////////////////////////////////////////////////
//
// File : inputLayer.java
//
//////////////////////////////////////////////////////////////////
//
//						inputLayer extending class
//
//////////////////////////////////////////////////////////////////
//
//	Author:  Patocchi L.
//	Date:    02.09.1996
//	Project: jaNet
//
//	inputLayer is the extended BPNLayer class for a BackPropagation 
//	input layer.
//	
//////////////////////////////////////////////////////////////////
//
//	date		who					what
//  02.09.1996	Patocchi L.			creation

package jaNet.backprop;

import java.io.*;

public class inputLayer extends BPNLayer{

	protected 			BPNLayer 		lowerLayer;
	protected 			BPNWeightPack 	lowerWeights;

//////////////////////////////////////////////////////////////////
//
//	Constructors
//
//////////////////////////////////////////////////////////////////
	public inputLayer(){
		this(1);
	}
	public inputLayer(int n){
		setSize(n);
	}

//////////////////////////////////////////////////////////////////
//
//	I/O ports
//
//////////////////////////////////////////////////////////////////
	public void writeToFile(RandomAccessFile raf) throws BPNException{
		try{
			raf.writeUTF(getClass().getName()+version);
			int size = getSize();
			raf.writeInt(size);
		}catch(IOException ioe){
			throw new BPNException("outputLayer: Error in writeToFile,("+ioe+").");
		}
	}
	public static inputLayer readFromFile(RandomAccessFile raf) throws BPNException{
		int upper, lower;
		inputLayer temp = new inputLayer();
		
		try{
			if(raf.readUTF().compareTo(temp.getClass().getName()+version) != 0){
				throw new BPNException("inputLayer: Error in readFromFile, unknown version.");
			}
			// setup size of tables in temporary variables
			int size = raf.readInt();
			temp = new inputLayer(size);
		}catch(IOException ioe){
			throw new BPNException("outputLayer: Error in readFromFile,("+ioe+").");
		}
		
		return temp;
	}

//////////////////////////////////////////////////////////////////
//
//	Plug-in's (activating function, layers, weights pack)
//
//////////////////////////////////////////////////////////////////
	public void 			setLowerLayer(BPNLayer layer){
		lowerLayer = layer;
	}
	public BPNLayer 		getLowerLayer(){
		return lowerLayer;
	}
	public void 			setLowerWeightPack(BPNWeightPack uwp){
		lowerWeights = uwp;
	}
	public BPNWeightPack 	getLowerWeightPack(){
		return lowerWeights;
	}
//////////////////////////////////////////////////////////////////
//
//	neural network input layer functionalities
//
//////////////////////////////////////////////////////////////////
	public void propagate() throws BPNException{
		// propagate actual layer state;
		propagate(vector);
	}

	public void propagate(double newVector[]) throws BPNException{
		// set vector as actual input
		setVector(newVector);
		// stroke next layer for propagation
		lowerLayer.propagate();
	} 

}