Examples of PortfolioProblemDescription

org.jamesii.asf.portfolios.plugintype.PortfolioProblemDescription
The Class PortfolioProblemDescription. @author Roland Ewald

Examples of org.jamesii.asf.portfolios.plugintype.PortfolioProblemDescription


  @Override
  public double[] portfolio(PortfolioProblemDescription problem) {


    Double[][] performances = problem.getPerformancesForMaximization(0);
    PortfolioProblemDescription problemGA =
        new PortfolioProblemDescription(new PortfolioPerformanceData(
            performances), problem.getAcceptableRisk(),
            problem.getMaximizationFlags()[0], problem.getMinSize(),
            problem.getMaxSize());


    currentPool =

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Examples of org.jamesii.asf.portfolios.plugintype.PortfolioProblemDescription

   */
  private Pair<double[], double[]> createPortfolios(
      PerformanceDataGenerator generator, GeneticAlgorithmPortfolioSelector gaps) {


    PortfolioPerformanceData perfData = generator.generateTestMatrix();
    PortfolioProblemDescription pdd =
        new PortfolioProblemDescription(perfData, acceptableRisk, false,
            MIN_SIZE, MAX_SIZE);
    gaps.setIndividualFactory(new ListIndividualFactory());
    double[] portfolio = gaps.portfolio(pdd);
    double[] stochasticPortfolio = null;

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Examples of org.jamesii.asf.portfolios.plugintype.PortfolioProblemDescription

   * Tests simple portfolio construction.
   */
  public void testSimplePortfolioConstruction() {


    List<Pair<Integer, Double>> portfolio =
        ps.constructPortfolio(new PortfolioProblemDescription(
            new PortfolioPerformanceData(PERF_DATA), 1, false, 1, 2));
    assertTrue(portfolio.size() == 1 || portfolio.size() == 2);


    double weightSum = 0;
    for (Pair<Integer, Double> pElem : portfolio) {
      assertTrue(pElem.getSecondValue() >= 0 && pElem.getSecondValue() <= 1.0);
      assertTrue(pElem.getFirstValue() >= 0
          && pElem.getFirstValue() < PERF_DATA[0].length);
      weightSum += pElem.getSecondValue();
    }


    assertTrue(Math.abs(1 - weightSum) <= AbstractPortfolioSelector.EPSILON);


    // This is a stochastic result (although *very* likely) - re-run if check
    // fails
    PERF_DATA[0] = new Double[] { .5, .5, .5, .5 };
    portfolio =
        ps.constructPortfolio(new PortfolioProblemDescription(
            new PortfolioPerformanceData(PERF_DATA), 1, true, 1, 2));
    assertEquals(1, portfolio.size());
    assertEquals(2, portfolio.get(0).getFirstValue().intValue());


    portfolio =
        ps.constructPortfolio(new PortfolioProblemDescription(
            new PortfolioPerformanceData(PERF_DATA), 1, false, 1, 2));
    assertEquals(1, portfolio.size());
    assertEquals(0, portfolio.get(0).getFirstValue().intValue());


  }

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Examples of org.jamesii.asf.portfolios.plugintype.PortfolioProblemDescription

  PortfolioProblemDescription ppd;


  @Override
  public void setUp() {
    ppd =
        new PortfolioProblemDescription(new PortfolioPerformanceData(
            PERF_MATRIX), 0, false, 1, 2);
  }

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Examples of org.jamesii.asf.portfolios.plugintype.PortfolioProblemDescription


    List<Double> execTimes = new ArrayList<>();


    for (int rep = 0; rep < PORT_GEN_REPS; rep++) {


      PortfolioProblemDescription pdd =
          new PortfolioProblemDescription(
              new PortfolioPerformanceData[] { portPerfData }, ACCEPTABLE_RISK,
              new boolean[] { false }, MIN_PORTFOLIO_SIZE, MAX_PORTFOLIO_SIZE);
      GeneticAlgorithmPortfolioSelector gaps =
          new GeneticAlgorithmPortfolioSelector();
      gaps.setAbortCriterion(new GenerationCountAbort(NUM_GENERATIONS));

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Examples of org.jamesii.asf.portfolios.plugintype.PortfolioProblemDescription

    gaps.setNumIndividuals(NUM_OF_IND);
    gaps.setMutationRate(MUTATION_RATE);
    gaps.setFactoryGenePool(FACTORY_GENE_POOL);
    gaps.setIndividualFactory(FACTORY_INDIVIDUAL);
    double[] vector =
        gaps.portfolio(new PortfolioProblemDescription(perfData, 0, MAXIMIZE,
            MIN_SIZE, MAX_SIZE));


    System.out.println("PerformanceTest finished.");
    System.out.println("Vector:");
    for (int i = 0; i < vector.length; i++) {

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Examples of org.jamesii.asf.portfolios.plugintype.PortfolioProblemDescription

  private GeneticAlgorithmPortfolioSelector gaps;


  @Override
  public void setUp() {
    problemDescription =
        new PortfolioProblemDescription(new PortfolioPerformanceData(
            problemMatrix), 0, true, MIN_SIZE, MAX_SIZE);
    gaps = new GeneticAlgorithmPortfolioSelector();
    gaps.setFactoryGenePool(FACTORY_GENE_POOL);
  }

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Examples of org.jamesii.asf.portfolios.plugintype.PortfolioProblemDescription

    }
    gaps.setAbortCriterion(new GenerationCountAbort(GEN_COUNT));
    gaps.setFitness(NULL_FITNESS);
    gaps.setNumIndividuals(NUM_OF_IND);


    gaps.portfolio(new PortfolioProblemDescription(
        new PortfolioPerformanceData(problemMatrixNull), 0, true, MIN_SIZE,
        MAX_SIZE));
    gaps.setIndividualFactory(FACTORY_INDIVIDUAL);


    SimSystem.report(Level.INFO,

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Examples of org.jamesii.asf.portfolios.plugintype.PortfolioProblemDescription

   */
  public void testFixFitnessMinimize() {
    gaps.setAbortCriterion(new MaxFitnessAbort(MINIMIZE_FITNESS));
    gaps.setFitness(TEST_FITNESS_MIN);
    gaps.setNumIndividuals(NUM_OF_IND);
    gaps.portfolio(new PortfolioProblemDescription(
        new PortfolioPerformanceData(problemMatrix), 0, false, MIN_SIZE,
        MAX_SIZE));
    gaps.setIndividualFactory(FACTORY_INDIVIDUAL);


    assertTrue("Best Fitness should be " + MINIMIZE_FITNESS + " but it is "

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