Package org.apache.commons.math.random

Examples of org.apache.commons.math.random.UncorrelatedRandomVectorGenerator

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        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(16069223052l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
            new MultiStartDifferentiableMultivariateVectorialOptimizer(underlyingOptimizer,
                                                                       10, generator);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6));
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        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(12373523445l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
            new MultiStartDifferentiableMultivariateVectorialOptimizer(underlyingOptimizer,
                                                                       10, generator);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6));
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        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(16069223052l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
            new MultiStartDifferentiableMultivariateVectorialOptimizer(underlyingOptimizer,
                                                                       10, generator);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6));
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        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(12373523445l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
            new MultiStartDifferentiableMultivariateVectorialOptimizer(underlyingOptimizer,
                                                                       10, generator);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6));
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                                         { -1.2,  1.0 }, { 0.9, 1.2 } , {  3.5, -2.3 }
                                     });
    JDKRandomGenerator g = new JDKRandomGenerator();
    g.setSeed(16069223052l);
    RandomVectorGenerator generator =
        new UncorrelatedRandomVectorGenerator(2, new GaussianRandomGenerator(g));
    MultiStartMultivariateRealOptimizer optimizer =
        new MultiStartMultivariateRealOptimizer(underlying, 10, generator);
    optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1, 1.0e-3));
    optimizer.setMaxIterations(100);
    RealPointValuePair optimum =
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        NonLinearConjugateGradientOptimizer underlying =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(753289573253l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(new double[] { 50.0, 50.0 }, new double[] { 10.0, 10.0 },
                                                  new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateRealOptimizer optimizer =
            new MultiStartDifferentiableMultivariateRealOptimizer(underlying, 10, generator);
        optimizer.setMaxIterations(100);
        assertEquals(100, optimizer.getMaxIterations());
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                                         { -1.2,  1.0 }, { 0.9, 1.2 } , {  3.5, -2.3 }
                                     });
    JDKRandomGenerator g = new JDKRandomGenerator();
    g.setSeed(16069223052l);
    RandomVectorGenerator generator =
        new UncorrelatedRandomVectorGenerator(2, new GaussianRandomGenerator(g));
    MultiStartMultivariateRealOptimizer optimizer =
        new MultiStartMultivariateRealOptimizer(underlying, 10, generator);
    optimizer.setConvergenceChecker(new SimpleScalarValueChecker(-1, 1.0e-3));
    optimizer.setMaxIterations(100);
    RealPointValuePair optimum =
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        NonLinearConjugateGradientOptimizer underlying =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(753289573253l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(new double[] { 50.0, 50.0 }, new double[] { 10.0, 10.0 },
                                                  new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateRealOptimizer optimizer =
            new MultiStartDifferentiableMultivariateRealOptimizer(underlying, 10, generator);
        optimizer.setMaxIterations(100);
        assertEquals(100, optimizer.getMaxIterations());
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        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(16069223052l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
            new MultiStartDifferentiableMultivariateVectorialOptimizer(underlyingOptimizer,
                                                                       10, generator);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6));
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        DifferentiableMultivariateVectorialOptimizer underlyingOptimizer =
            new GaussNewtonOptimizer(true);
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(12373523445l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        MultiStartDifferentiableMultivariateVectorialOptimizer optimizer =
            new MultiStartDifferentiableMultivariateVectorialOptimizer(underlyingOptimizer,
                                                                       10, generator);
        optimizer.setMaxIterations(100);
        optimizer.setConvergenceChecker(new SimpleVectorialValueChecker(1.0e-6, 1.0e-6));
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Related Classes of org.apache.commons.math.random.UncorrelatedRandomVectorGenerator

  • org.apache.commons.math.optimization.DirectSearchOptimizer
  • org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateRealOptimizerTest
  • org.apache.commons.math.optimization.MultiStartDifferentiableMultivariateVectorialOptimizerTest
  • org.apache.commons.math.optimization.MultiStartMultivariateRealOptimizerTest
  • org.apache.commons.math.optimization.NelderMeadTest
  • org.apache.commons.math.exception.DimensionMismatchException
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