Examples of NonLinearConjugateGradientOptimizer

Examples of org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer

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        circle.addPoint( 30.0,  68.0);
        circle.addPoint( 50.0,  -6.0);
        circle.addPoint(110.0, -20.0);
        circle.addPoint( 35.0,  15.0);
        circle.addPoint( 45.0,  97.0);
        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));
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Examples of org.apache.commons.math.optimization.general.NonLinearConjugateGradientOptimizer

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        circle.addPoint( 30.0,  68.0);
        circle.addPoint( 50.0,  -6.0);
        circle.addPoint(110.0, -20.0);
        circle.addPoint( 35.0,  15.0);
        circle.addPoint( 45.0,  97.0);
        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));
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Examples of org.apache.commons.math3.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer

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        circle.addPoint( 45.0,  97.0);
        // TODO: the wrapper around NonLinearConjugateGradientOptimizer is a temporary hack for
        // version 3.1 of the library. It should be removed when NonLinearConjugateGradientOptimizer
        // will officially be declared as implementing MultivariateDifferentiableOptimizer
        GradientMultivariateOptimizer underlying
            = new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
                                                      new SimpleValueChecker(1e-10, 1e-10));
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(753289573253l);
        RandomVectorGenerator generator
            = new UncorrelatedRandomVectorGenerator(new double[] { 50, 50 },
View Full Code Here

Examples of org.apache.commons.math3.optim.nonlinear.scalar.gradient.NonLinearConjugateGradientOptimizer

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        circle.addPoint( 45.0,  97.0);
        // TODO: the wrapper around NonLinearConjugateGradientOptimizer is a temporary hack for
        // version 3.1 of the library. It should be removed when NonLinearConjugateGradientOptimizer
        // will officially be declared as implementing MultivariateDifferentiableOptimizer
        GradientMultivariateOptimizer underlying
            = new NonLinearConjugateGradientOptimizer(NonLinearConjugateGradientOptimizer.Formula.POLAK_RIBIERE,
                                                      new SimpleValueChecker(1e-10, 1e-10));
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(753289573253l);
        RandomVectorGenerator generator
            = new UncorrelatedRandomVectorGenerator(new double[] { 50, 50 },
View Full Code Here

Examples of org.apache.commons.math3.optimization.general.NonLinearConjugateGradientOptimizer

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        // will officially be declared as implementing MultivariateDifferentiableOptimizer
        MultivariateDifferentiableOptimizer underlying =
                new MultivariateDifferentiableOptimizer() {

            private final NonLinearConjugateGradientOptimizer cg =
                    new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                            new SimpleValueChecker(1.0e-10, 1.0e-10));
            public PointValuePair optimize(int maxEval,
                                           MultivariateDifferentiableFunction f,
                                           GoalType goalType,
                                           double[] startPoint) {
                return cg.optimize(maxEval, f, goalType, startPoint);
            }

            public int getMaxEvaluations() {
                return cg.getMaxEvaluations();
            }

            public int getEvaluations() {
                return cg.getEvaluations();
            }

            public ConvergenceChecker<PointValuePair> getConvergenceChecker() {
                return cg.getConvergenceChecker();
            }
        };
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(753289573253l);
        RandomVectorGenerator generator =
View Full Code Here

Examples of org.apache.commons.math3.optimization.general.NonLinearConjugateGradientOptimizer

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        // will officially be declared as implementing MultivariateDifferentiableOptimizer
        MultivariateDifferentiableOptimizer underlying =
                new MultivariateDifferentiableOptimizer() {

            private final NonLinearConjugateGradientOptimizer cg =
                    new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                            new SimpleValueChecker(1.0e-10, 1.0e-10));
            public PointValuePair optimize(int maxEval,
                                           MultivariateDifferentiableFunction f,
                                           GoalType goalType,
                                           double[] startPoint) {
                return cg.optimize(maxEval, f, goalType, startPoint);
            }

            public int getMaxEvaluations() {
                return cg.getMaxEvaluations();
            }

            public int getEvaluations() {
                return cg.getEvaluations();
            }

            public ConvergenceChecker<PointValuePair> getConvergenceChecker() {
                return cg.getConvergenceChecker();
            }
        };
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(753289573253l);
        RandomVectorGenerator generator =
View Full Code Here

Examples of org.apache.commons.math3.optimization.general.NonLinearConjugateGradientOptimizer

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        circle.addPoint( 30.0,  68.0);
        circle.addPoint( 50.0,  -6.0);
        circle.addPoint(110.0, -20.0);
        circle.addPoint( 35.0,  15.0);
        circle.addPoint( 45.0,  97.0);
        NonLinearConjugateGradientOptimizer underlying =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1.0e-10, 1.0e-10));
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(753289573253l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(new double[] { 50.0, 50.0 }, new double[] { 10.0, 10.0 },
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