[Quantproject-developers] QuantProject/b1_ADT/Optimizing/Genetic GeneticOptimizer.cs,1.6,1.7

[Marco M. <mi...@us...>]

Update of /cvsroot/quantproject/QuantProject/b1_ADT/Optimizing/Genetic
In directory sc8-pr-cvs1.sourceforge.net:/tmp/cvs-serv20238/b1_ADT/Optimizing/Genetic

Modified Files:
	GeneticOptimizer.cs 
Log Message:
- Added if condition for calling NewGeneration event (just to avoid run time errors if no handler has been added to the event)
- added new constructor: now it is possible to set directly the randomGenerator 

Index: GeneticOptimizer.cs
===================================================================
RCS file: /cvsroot/quantproject/QuantProject/b1_ADT/Optimizing/Genetic/GeneticOptimizer.cs,v
retrieving revision 1.6
retrieving revision 1.7
diff -C2 -d -r1.6 -r1.7
*** GeneticOptimizer.cs	23 Jul 2005 18:02:23 -0000	1.6
--- GeneticOptimizer.cs	25 Jul 2005 22:27:49 -0000	1.7
***************
*** 41,45 ****
  	{
      #region fields  
!     private static Random random = new Random((int)DateTime.Now.Ticks);
      
      private double mutationRate;
--- 41,45 ----
  	{
      #region fields  
!     private Random random;
      
      private double mutationRate;
***************
*** 143,147 ****
        this.populationSize = populationSize;
        this.generationNumber = generationNumber;
!       
        this.commonInitialization();
      }
--- 143,147 ----
        this.populationSize = populationSize;
        this.generationNumber = generationNumber;
!       this.random = new Random((int)DateTime.Now.Ticks);
        this.commonInitialization();
      }
***************
*** 158,162 ****
        this.generationNumber = generationNumber;
        this.genomeManager = genomeManager;
!       
        this.commonInitialization();
      }
--- 158,176 ----
        this.generationNumber = generationNumber;
        this.genomeManager = genomeManager;
!       this.random = new Random((int)DateTime.Now.Ticks);
!       this.commonInitialization();
!     }
!     
!     public GeneticOptimizer(double crossoverRate, double mutationRate, double elitismRate, 
!                             int populationSize, int generationNumber,
!                             IGenomeManager genomeManager, int seedForRandomGenerator)
!     {
!       this.crossoverRate = crossoverRate;
!       this.mutationRate = mutationRate;
!       this.elitismRate = elitismRate;
!       this.populationSize = populationSize;
!       this.generationNumber = generationNumber;
!       this.genomeManager = genomeManager;
!       this.random = new Random(seedForRandomGenerator);
        this.commonInitialization();
      }
***************
*** 234,239 ****
        this.createGenomes();
        this.currentGeneration.Sort(this.genomeComparer);
! 			this.NewGeneration( this , new NewGenerationEventArgs(
! 				this.currentGeneration , this.generationCounter , this.generationNumber ) );
        this.calculateTotalFitness();
        this.updateCumulativeFitnessList();
--- 248,254 ----
        this.createGenomes();
        this.currentGeneration.Sort(this.genomeComparer);
!       if(this.NewGeneration != null)
! 			  this.NewGeneration( this , new NewGenerationEventArgs(
! 				  this.currentGeneration , this.generationCounter , this.generationNumber ) );
        this.calculateTotalFitness();
        this.updateCumulativeFitnessList();
***************
*** 263,267 ****
      private int rouletteSelection()
      {
!       double randomFitness = this.totalFitness *(double)GeneticOptimizer.random.Next(1,1001)/1000;
        int idx = -1;
        int first = 0;
--- 278,282 ----
      private int rouletteSelection()
      {
!       double randomFitness = this.totalFitness *(double)this.random.Next(1,1001)/1000;
        int idx = -1;
        int first = 0;
***************
*** 294,303 ****
      {
        this.totalFitness = 0.0;
-       for (int i = 0; i < this.populationSize; i++)
-       {
-         Genome g = ((Genome) this.currentGeneration[i]);
-         this.totalFitness += g.Fitness;
-       }
        
      }
      
--- 309,316 ----
      {
        this.totalFitness = 0.0;
        
+       foreach(Genome g in this.currentGeneration)
+         this.totalFitness += g.Fitness;
+             
      }
      
***************
*** 364,368 ****
          parent1 = ((Genome) this.currentGeneration[indexForParent1]);
          parent2 = ((Genome) this.currentGeneration[indexForParent2]);
!         if ((double)GeneticOptimizer.random.Next(1,1001)/1000 < this.crossoverRate)
          {
            childs = this.genomeManager.GetChilds(parent1, parent2);
--- 377,381 ----
          parent1 = ((Genome) this.currentGeneration[indexForParent1]);
          parent2 = ((Genome) this.currentGeneration[indexForParent2]);
!         if ((double)this.random.Next(1,1001)/1000 < this.crossoverRate)
          {
            childs = this.genomeManager.GetChilds(parent1, parent2);
***************
*** 387,392 ****
        this.updateCurrentGeneration();
        this.currentGeneration.Sort(this.genomeComparer);
! 			this.NewGeneration( this , new NewGenerationEventArgs(
! 				this.currentGeneration , this.generationCounter , this.generationNumber ) );
        this.calculateTotalFitness();
        this.updateCumulativeFitnessList();
--- 400,406 ----
        this.updateCurrentGeneration();
        this.currentGeneration.Sort(this.genomeComparer);
! 			if(this.NewGeneration != null)
! 			  this.NewGeneration( this , new NewGenerationEventArgs(
! 				  this.currentGeneration , this.generationCounter , this.generationNumber ) );
        this.calculateTotalFitness();
        this.updateCumulativeFitnessList();