/**
* Copyright (c) 2006, Seweryn Habdank-Wojewodzki
* Copyright (c) 2006, Janusz Rybarski
* Copyright (c) 2014, Sergei Chekanov 
*
* All rights reserved.
* 
* Redistribution and use in source and binary forms,
* with or without modification, are permitted provided
* that the following conditions are met:
*
* Redistributions of source code must retain the above
* copyright notice, this list of conditions and the
* following disclaimer.
*
* Redistributions in binary form must reproduce the
* above copyright notice, this list of conditions
* and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS
* AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
* A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL
* THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
* HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
* WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY
* WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
* OF THE POSSIBILITY OF SUCH DAMAGE.
*/

package jhpro.nnet.jknnl;

import java.io.FileWriter;
import java.io.PrintWriter;
import java.util.ArrayList;
import java.io.File;
import java.io.FileReader;
import java.io.BufferedReader;
import java.io.IOException;
import jhplot.PND;

/**
 * Default Network Model. 
 * We can create network with specified topology, inputs for each neuron and maximal value for neurons weights.  
 * @author Janusz Rybarski
 * @author Seweryn Habdank-Wojewodzki
 * @author Sergei Chekanov 
*/

public class DefaultNetwork implements NetworkModel{
    
    /**
     * Array of neurons
     */
    private NeuronModel[] neuronList;
    
    /**
     * Reference to topology
     */
    private TopologyModel topology;
    
    /**
     * Create network with specified topology, random weight from
     * defined interval and number of inputs
     * @param weightNumber number of weights (inputs)
     * @param maxWeight array with specified weight
     * @param topology Topology
     */
    public DefaultNetwork(int weightNumber, double[] maxWeight, TopologyModel topology) {
        this.topology = topology;
        int numberOfNeurons = topology.getNumbersOfNeurons();
        neuronList = new KohonenNeuron[numberOfNeurons];
        for (int i=0; i getWeightsAsArray(){
        ArrayList data= new ArrayList(); 
        for (int i=0; i< neuronList.length; i++ ){
            double[] weight = neuronList[i].getWeight();
            data.add(weight); 
        }
        return data;
      }

     /**
     * Returns data representation of the Coords object
     * @return Returns PND data representation of the Coords (weights) object
     */
    public PND getWeights(){
        PND data= new PND("weights");
        for (int i=0; i< neuronList.length; i++ ){
            double[] weight = neuronList[i].getWeight();
            data.add(weight);
        }
        return data;
      }


 
    /**
     * Save network into file
     * @param fileName File Name
     */
    public void networkToFile(String fileName){
        File outFile =  new File(fileName);
        String weightList;
        double[] weight;
        try{
        FileWriter fw = new FileWriter(outFile);
        PrintWriter pw = new PrintWriter(fw);
        int networkSize = neuronList.length;
        for (int i=0; i< networkSize; i++ ){
            weightList ="";
            weight = neuronList[i].getWeight();
            for (int j=0; j< weight.length; j++){
                weightList += weight[j];
                if (j < weight.length -1){
                    weightList += "\t";
                }
            }
            pw.println(weightList);
        }
        fw.close();
        }catch(IOException e){
            System.out.println("File can not be read!. Error: " + e);
        }
    }
}