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

Package org.apache.commons.math3.optimization

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

org.apache.commons.math3.optimization.SimpleVectorValueChecker
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 for all vectors elements.
The {@link #converged(int,PointVectorValuePair,PointVectorValuePair) converged}method will also return {@code true} if the number of iterations has been set(see {@link #SimpleVectorValueChecker(double,double,int) this constructor}). @deprecated As of 3.1 (to be removed in 4.0). @since 3.0

        circle.addPoint(110.0, -20.0);
        circle.addPoint( 35.0,  15.0);
        circle.addPoint( 45.0,  97.0);


        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-30, 1.0e-30));


        optimizer.optimize(100, circle, new double[] { 0, 0, 0, 0, 0 },
                           new double[] { 1, 1, 1, 1, 1 },
                           new double[] { 98.680, 47.345 });
    }

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     * The convergence check is set to a {@link SimpleVectorValueChecker}.
     * @deprecated See {@link SimpleVectorValueChecker#SimpleVectorValueChecker()}
     */
    @Deprecated
    protected BaseAbstractMultivariateVectorOptimizer() {
        this(new SimpleVectorValueChecker());
    }

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    }


    @Test
    public void testMath798() {
        final double tol = 1e-14;
        final SimpleVectorValueChecker checker = new SimpleVectorValueChecker(tol, tol);
        final double[] init = new double[] { 0, 0 };
        final int maxEval = 3;


        final double[] lm = doMath798(new LevenbergMarquardtOptimizer(checker), maxEval, init);
        final double[] gn = doMath798(new GaussNewtonOptimizer(checker), maxEval, init);

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     * stringent.
     */
    @Test(expected=TooManyEvaluationsException.class)
    public void testMath798WithToleranceTooLow() {
        final double tol = 1e-100;
        final SimpleVectorValueChecker checker = new SimpleVectorValueChecker(tol, tol);
        final double[] init = new double[] { 0, 0 };
        final int maxEval = 10000; // Trying hard to fit.


        final double[] gn = doMath798(new GaussNewtonOptimizer(checker), maxEval, init);
    }

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    @Test
    public void testMath798WithToleranceTooLowButNoException() {
        final double tol = 1e-100;
        final double[] init = new double[] { 0, 0 };
        final int maxEval = 10000; // Trying hard to fit.
        final SimpleVectorValueChecker checker = new SimpleVectorValueChecker(tol, tol, maxEval);


        final double[] lm = doMath798(new LevenbergMarquardtOptimizer(checker), maxEval, init);
        final double[] gn = doMath798(new GaussNewtonOptimizer(checker), maxEval, init);


        for (int i = 0; i <= 1; i++) {

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    }


    @Test
    public void testRedundantUnsolvable() {
        // Gauss-Newton should not be able to solve redundant information
        checkUnsolvableProblem(new GaussNewtonOptimizer(true, new SimpleVectorValueChecker(1e-15, 1e-15)), false);
    }

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    public void testTrivial() {
        LinearProblem problem =
            new LinearProblem(new double[][] { { 2 } }, new double[] { 3 });


        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));


        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1 }, new double[] { 0 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        Assert.assertEquals(1.5, optimum.getPoint()[0], 1.0e-10);

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        LinearProblem problem =
            new LinearProblem(new double[][] { { 1.0, -1.0 }, { 0.0, 2.0 }, { 1.0, -2.0 } },
                              new double[] { 4.0, 6.0, 1.0 });


        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));


        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1, 1, 1 }, new double[] { 0, 0 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        Assert.assertEquals(7.0, optimum.getPoint()[0], 1.0e-10);

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                { 0, 0, 0, 0, 2, 0 },
                { 0, 0, 0, 0, 0, 2 }
        }, new double[] { 0.0, 1.1, 2.2, 3.3, 4.4, 5.5 });


        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));


        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1, 1, 1, 1, 1, 1 },
                               new double[] { 0, 0, 0, 0, 0, 0 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);

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                { -1,  1, 0 },
                {  0, -1, 1 }
        }, new double[] { 1, 1, 1});


        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));


        PointVectorValuePair optimum =
            optimizer.optimize(100, problem, problem.target, new double[] { 1, 1, 1 }, new double[] { 0, 0, 0 });
        Assert.assertEquals(0, optimizer.getRMS(), 1.0e-10);
        Assert.assertEquals(1.0, optimum.getPoint()[0], 1.0e-10);

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

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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