package org.joone.samples.engine.validation;

import java.util.*;

import org.joone.engine.*;
import org.joone.inspection.implementations.*;
import org.joone.io.*;
import org.joone.net.*;

/*
 * 
Title: Effort Estimations Through Neural Networks - Joone Test
 * 
Description: Stage II - Joone Pilot
 * 
Copyright: Copyright (c) 2003
 * 
Company: Motorola
 * @author Sebastian Donatti - AGD013
 * @version 1.0.0
 */

public class NeuralNetTester implements Runnable,NeuralNetListener,NeuralValidationListener{
  // Joone Global Variables
  private Vector listeners;
  private NeuralNet oldNetwork;
  private NeuralNet newNetwork;
  private Thread myThread=null;
  private double lastRSME;
  private int minimaEpochs;
  // JoonePilot Global Variables;
  private int problem;
  private boolean relaunch;
  private static int relaunchNumber;
  private boolean learnCurve; // Added to avoid to print all the intermediate errors when in learning curve mode

  // Launches the train & validation of one neural network - Class Constructor
  public NeuralNetTester(NeuralNet _network,boolean lCurve,int _problem){
    problem=_problem;
    listeners=new Vector();
    oldNetwork=_network;
    newNetwork=cloneNet(_network);
    learnCurve=lCurve;
    lastRSME=0;
    minimaEpochs=0;
    relaunch=false;
  }

  public void addValidationListener(NeuralValidationListener newListener){
    if(!listeners.contains(newListener)){
      listeners.addElement(newListener);
    }
  }

  // Trains the neural network - Class Method
  protected void train(){
    newNetwork.getMonitor().addNeuralNetListener(this);
    newNetwork.getMonitor().setLearning(true);
    newNetwork.getMonitor().setValidation(false);
    newNetwork.start();
    newNetwork.getMonitor().Go();
  }

  // Validates the trained neural network - Class Method
  protected void validate(){
    if(!learnCurve){
      // Update Screen
      System.out.print("\nTraining Finished \n");
      System.out.print("\nValidation Started\n\n");
    }
    // Set all the parameters for the validation
    NeuralNetValidator nnv=new NeuralNetValidator(cloneNet(newNetwork));
    nnv.addValidationListener(this);
    // Validate the network
    nnv.start();
  }

  // Clones the neural network passed as parameter - Class Method
  private NeuralNet cloneNet(NeuralNet oldNet){
    // Create a copy of the neural network
    oldNet.getMonitor().setExporting(true);
    NeuralNet newNet=oldNet.cloneNet();
    oldNet.getMonitor().setExporting(false);
    // Clean the old listeners (This is a fundamental action to avoid that the validated net calls any method of previously registered listeners)
    newNet.removeAllListeners();
    return newNet;
  }

  // Notifies all the registered listeners - Class Method
  private void fireNetValidated(NeuralValidationEvent event){
    NeuralNet NN=(NeuralNet)event.getSource();
    for(int i=0;i