Examples of org.apache.commons.math3.optimization.SimpleValueChecker

Package org.apache.commons.math3.optimization

Examples of org.apache.commons.math3.optimization.SimpleValueChecker

org.apache.commons.math3.optimization.SimpleValueChecker
Simple implementation of the {@link ConvergenceChecker} interface usingonly objective function values. Convergence is considered to have been reached if either the relative difference between the objective function values is smaller than a threshold or if either the absolute difference between the objective function values is smaller than another threshold.
The {@link #converged(int,PointValuePair,PointValuePair) converged}method will also return {@code true} if the number of iterations has been set(see {@link #SimpleValueChecker(double,double,int) this constructor}). @deprecated As of 3.1 (to be removed in 4.0). @since 3.0

                 { 0.0, 0.0, -1.0,  1.0, 0.0,  1.0 },
                 { 0.0, 0.0,  0.0, -1.0, 1.0,  0.0 }
        }, new double[] { 3.0, 12.0, -1.0, 7.0, 1.0 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 2, 2, 2, 2, 2, 2 });
        Assert.assertEquals(0, optimum.getValue(), 1.0e-10);
    }

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                { 1.0,  3.0 }
        }, new double[] { 3.0, 1.0, 5.0 });


        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 1, 1 });
        Assert.assertEquals(2.0, optimum.getPoint()[0], 1.0e-8);
        Assert.assertEquals(1.0, optimum.getPoint()[1], 1.0e-8);

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                { 1.0,  3.0 }
        }, new double[] { 3.0, 1.0, 4.0 });


        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 1, 1 });
        Assert.assertTrue(optimum.getValue() > 0.1);


    }

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        circle.addPoint(110.0, -20.0);
        circle.addPoint( 35.0,  15.0);
        circle.addPoint( 45.0,  97.0);
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-30, 1e-30),
                                                    new BrentSolver(1e-15, 1e-13));
        PointValuePair optimum =
            optimizer.optimize(100, circle, GoalType.MINIMIZE, new double[] { 98.680, 47.345 });
        Vector2D center = new Vector2D(optimum.getPointRef()[0], optimum.getPointRef()[1]);
        Assert.assertEquals(69.960161753, circle.getRadius(center), 1.0e-8);

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     * Simple constructor with default settings.
     * The convergence check is set to a {@link SimpleValueChecker} and
     * the allowed number of evaluations is set to {@link Integer#MAX_VALUE}.
     */
    protected BaseAbstractMultivariateOptimizer() {
        this(new SimpleValueChecker());
    }

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     * must be one of {@link ConjugateGradientFormula#FLETCHER_REEVES} or {@link
     * ConjugateGradientFormula#POLAK_RIBIERE}.
     */
    public NonLinearConjugateGradientOptimizer(final ConjugateGradientFormula updateFormula) {
        this(updateFormula,
             new SimpleValueChecker());
    }

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                          int maxIterations, double stopFitness,
                          boolean isActiveCMA, int diagonalOnly, int checkFeasableCount,
                          RandomGenerator random, boolean generateStatistics) {
        this(lambda, inputSigma, maxIterations, stopFitness, isActiveCMA,
             diagonalOnly, checkFeasableCount, random, generateStatistics,
             new SimpleValueChecker());
    }

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    /**
     * Constructor using a default {@link SimpleValueChecker convergence
     * checker}.
     */
    public SimplexOptimizer() {
        this(new SimpleValueChecker());
    }

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    /**
     * @param rel Relative threshold.
     * @param abs Absolute threshold.
     */
    public SimplexOptimizer(double rel, double abs) {
        this(new SimpleValueChecker(rel, abs));
    }

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    public void testTrivial() {
        LinearProblem problem =
            new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });
        NonLinearConjugateGradientOptimizer optimizer =
            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1e-6, 1e-6));
        PointValuePair optimum =
            optimizer.optimize(100, problem, GoalType.MINIMIZE, new double[] { 0 });
        Assert.assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);
        Assert.assertEquals(0.0, optimum.getValue(), 1.0e-10);
    }

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Related Classes of org.apache.commons.math3.optimization.SimpleValueChecker

org.apache.commons.math3.analysis.differentiation.DerivativeStructure

org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction

org.apache.commons.math3.analysis.function.HarmonicOscillator

org.apache.commons.math3.analysis.function.Sin

org.apache.commons.math3.analysis.function.Sinc

org.apache.commons.math3.analysis.MultivariateFunction

org.apache.commons.math3.analysis.QuinticFunction

org.apache.commons.math3.analysis.solvers.BrentSolver

org.apache.commons.math3.analysis.UnivariateFunction

org.apache.commons.math3.complex.Complex

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