[Quantproject-developers] QuantProject/b7_Scripts/EvaluatingOptimizationTechnique/EfficientPortfolio RunTestingOptimizationOpenToClose.cs,1.1,1.2

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

Update of /cvsroot/quantproject/QuantProject/b7_Scripts/EvaluatingOptimizationTechnique/EfficientPortfolio
In directory sc8-pr-cvs1.sourceforge.net:/tmp/cvs-serv16908/b7_Scripts/EvaluatingOptimizationTechnique/EfficientPortfolio

Modified Files:
	RunTestingOptimizationOpenToClose.cs 
Log Message:
RunTestingOptimizationOpenToClose now saves a log file to disk at the end of the test.

Index: RunTestingOptimizationOpenToClose.cs
===================================================================
RCS file: /cvsroot/quantproject/QuantProject/b7_Scripts/EvaluatingOptimizationTechnique/EfficientPortfolio/RunTestingOptimizationOpenToClose.cs,v
retrieving revision 1.1
retrieving revision 1.2
diff -C2 -d -r1.1 -r1.2
*** RunTestingOptimizationOpenToClose.cs	20 Aug 2005 16:08:48 -0000	1.1
--- RunTestingOptimizationOpenToClose.cs	28 Aug 2005 10:02:52 -0000	1.2
***************
*** 23,26 ****
--- 23,27 ----
  using System;
  using System.Data;
+ using System.IO;
  
  using QuantProject.ADT;
***************
*** 46,49 ****
--- 47,51 ----
      private int numDaysForLiquidity;
      private int populationSizeForGeneticOptimizer;
+     private int generationNumberForGeneticOptimizer;
    	private string benchmark;
    	private DateTime marketDate;
***************
*** 52,64 ****
    	private int numDaysAfterLastOptimizationDay;
    	private int numberOfSubsets;
    	
      public RunTestingOptimizationOpenToClose(string tickerGroupID, int numberOfEligibleTickers,
!       				int numberOfTickersToBeChosen, int numDaysForLiquidity, 
!       				int populationSizeForGeneticOptimizer, string benchmark,
        				DateTime marketDate, double targetReturn,
!       				PortfolioType portfolioType, int numDaysAfterLastOptimizationDay)
      {
!   		this.fitnessesInSample = new double[populationSizeForGeneticOptimizer];
!   		this.fitnessesOutOfSample = new double[populationSizeForGeneticOptimizer];
    		this.tickerGroupID = tickerGroupID;
    		this.numberOfEligibleTickers = numberOfEligibleTickers;
--- 54,72 ----
    	private int numDaysAfterLastOptimizationDay;
    	private int numberOfSubsets;
+   	private Genome[] genomesToTestOutOfSample;
+   	private int numberOfGenomesToTest;
    	
      public RunTestingOptimizationOpenToClose(string tickerGroupID, int numberOfEligibleTickers,
!       				int numberOfTickersToBeChosen, int numDaysForLiquidity,
!       				int generationNumberForGeneticOptimizer, int populationSizeForGeneticOptimizer, 
!       				string benchmark,
        				DateTime marketDate, double targetReturn,
!       				PortfolioType portfolioType, int numDaysAfterLastOptimizationDay,
!       				int numberOfSubsets, int numberOfGenomesToTest)
      {
!   		this.numberOfGenomesToTest = numberOfGenomesToTest;
!   		this.genomesToTestOutOfSample = new Genome[numberOfGenomesToTest];
!   		this.fitnessesInSample = new double[numberOfGenomesToTest];
!   		this.fitnessesOutOfSample = new double[numberOfGenomesToTest];
    		this.tickerGroupID = tickerGroupID;
    		this.numberOfEligibleTickers = numberOfEligibleTickers;
***************
*** 66,69 ****
--- 74,78 ----
    		this.numDaysForLiquidity = numDaysForLiquidity;
    		this.populationSizeForGeneticOptimizer = populationSizeForGeneticOptimizer;
+   		this.generationNumberForGeneticOptimizer = generationNumberForGeneticOptimizer;
    		this.benchmark = benchmark;
    		this.marketDate = marketDate;
***************
*** 71,76 ****
    		this.portfolioType = portfolioType;
    		this.numDaysAfterLastOptimizationDay = numDaysAfterLastOptimizationDay;
!   		this.numberOfSubsets = 5;
!     }
      
    	private DataTable getSetOfTickersToBeOptimized(DateTime date)
--- 80,86 ----
    		this.portfolioType = portfolioType;
    		this.numDaysAfterLastOptimizationDay = numDaysAfterLastOptimizationDay;
!   		this.numberOfSubsets = numberOfSubsets;
!   		
!   	}
      
    	private DataTable getSetOfTickersToBeOptimized(DateTime date)
***************
*** 138,150 ****
      }
    	
!   	private void setFitnesses_setFitnessesActually(GeneticOptimizer GO)
    		
      {
    		
!   		for(int i = 0; i<GO.CurrentGeneration.Count; i++)
    		{
!   			this.fitnessesInSample[i]=((Genome)GO.CurrentGeneration[i]).Fitness;
    			this.fitnessesOutOfSample[i]= 
!   				this.setFitnesses_setFitnessesActually_getFitnessOutOfSample((Genome)GO.CurrentGeneration[i]);
    		}
        
--- 148,171 ----
      }
    	
!   	private void setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample(GeneticOptimizer GO)
    		
      {
+   		Random random = new Random(10);
+   		for(int i = 0; i<this.numberOfGenomesToTest; i++)
+   		{
+   			this.genomesToTestOutOfSample[i]=
+   				(Genome)GO.CurrentGeneration[random.Next(this.populationSizeForGeneticOptimizer)];
+   		}
+   		Array.Sort(this.genomesToTestOutOfSample);
+     }
+   	private void setFitnesses_setFitnessesActually(GeneticOptimizer GO)
    		
!     {
!   		this.setFitnesses_setFitnessesActually_setGenomesToTestOutOfSample(GO);
!   		for(int i = 0; i<this.numberOfGenomesToTest; i++)
    		{
!   			this.fitnessesInSample[i]=(this.genomesToTestOutOfSample[i]).Fitness;
    			this.fitnessesOutOfSample[i]= 
!   				this.setFitnesses_setFitnessesActually_getFitnessOutOfSample(this.genomesToTestOutOfSample[i]);
    		}
        
***************
*** 167,171 ****
        GeneticOptimizer GO = new GeneticOptimizer(genManEfficientCTOPortfolio,
                                                    this.populationSizeForGeneticOptimizer,
!                                                   0,
                                                   ConstantsProvider.SeedForRandomGenerator);
            
--- 188,192 ----
        GeneticOptimizer GO = new GeneticOptimizer(genManEfficientCTOPortfolio,
                                                    this.populationSizeForGeneticOptimizer,
!                                                   this.generationNumberForGeneticOptimizer,
                                                   ConstantsProvider.SeedForRandomGenerator);
            
***************
*** 181,184 ****
--- 202,210 ----
      		new OptimizationTechniqueEvaluator(this.fitnessesInSample,
      		                                   this.fitnessesOutOfSample);
+     	this.run_writeToLogFile(evaluator);
+     }
+     
+     private void run_writeToLogFile(OptimizationTechniqueEvaluator evaluator)
+     {
      	double[] averagesInSample = 
      		evaluator.GetAveragesOfSubsetsInSample(this.numberOfSubsets);
***************
*** 186,190 ****
      		evaluator.GetAveragesOfSubsetsOutOfSample(this.numberOfSubsets);
      	double r = evaluator.GetCorrelationBetweenFitnesses();
!     }
  	}
  }
--- 212,245 ----
      		evaluator.GetAveragesOfSubsetsOutOfSample(this.numberOfSubsets);
      	double r = evaluator.GetCorrelationBetweenFitnesses();
!     	GenomeCounter genomeCounter = new GenomeCounter(this.genomesToTestOutOfSample);
!     	int differentEvaluatedGenomes = genomeCounter.TotalEvaluatedGenomes;
!      	string pathFile = System.Configuration.ConfigurationSettings.AppSettings["GenericArchive"] +
!                     "\\OpenToCloseOptimizationEvaluation.txt";
!   	  StreamWriter w = File.AppendText(pathFile);
!   	  w.WriteLine ("\n----------------------------------------------\r\n");
!   	  w.Write("\r\nNew Test for Evaluation of Open To Close Optimization {0}\r", DateTime.Now.Date.ToLongDateString());
!   	  w.WriteLine ("\n----------------------------------------------");
!   	  w.Write("\r\nFitnesses compared: {0}\r", this.fitnessesInSample.Length.ToString());
!   	  w.Write("\r\nDifferent evaluated genomes: {0}\r", differentEvaluatedGenomes.ToString());
!       w.Write("\r\nAverages of the {0} sub sets of fitnesses In Sample:\r",
!   	          this.numberOfSubsets);
!       //
!       for(int i = 0; i<averagesInSample.Length; i++)
!         	w.WriteLine("\n{0}-->{1}", i.ToString(), averagesInSample[i].ToString());
!       
!       w.WriteLine ("\n\n----------------------------------------------");
!       w.Write("\r\nAverages of the {0} sub sets of fitnesses Out of Sample:\r",
!   	          this.numberOfSubsets);
!       //
!       for(int i = 0; i<averagesOutOfSample.Length; i++)
!         	w.WriteLine("\n{0}-->{1}", i.ToString(), averagesOutOfSample[i].ToString());	
!       w.WriteLine ("\n\n----------------------------------------------");
!       //
!       w.Write("\r\nCorrelation coefficient between fitnesses: {0}\r", r.ToString());
!       w.WriteLine ("\n-----------------End of Test------------------\r\n");
!       // Update the underlying file.
!       w.Flush();
!       w.Close();
!     }	
  	}
  }