Package org.apache.commons.math3.optimization.general

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


        double maxError = 0;
        for (int degree = 0; degree < 10; ++degree) {
            PolynomialFunction p = buildRandomPolynomial(degree, randomizer);

            PolynomialFitter fitter =
                new PolynomialFitter(degree, new LevenbergMarquardtOptimizer());
            for (double x = -1.0; x < 1.0; x += 0.01) {
                fitter.addObservedPoint(1.0, x,
                                        p.value(x) + 0.1 * randomizer.nextGaussian());
            }

View Full Code Here


    }

    @Test
    public void testRedundantSolvable() {
        // Levenberg-Marquardt should handle redundant information gracefully
        checkUnsolvableProblem(new LevenbergMarquardtOptimizer(), true);
    }
View Full Code Here

public class HarmonicFitterTest {
    @Test(expected=NumberIsTooSmallException.class)
    public void testPreconditions1() {
        HarmonicFitter fitter =
            new HarmonicFitter(new LevenbergMarquardtOptimizer());

        fitter.fit();
    }
View Full Code Here

        final double w = 3.4;
        final double p = 4.1;
        HarmonicOscillator f = new HarmonicOscillator(a, w, p);

        HarmonicFitter fitter =
            new HarmonicFitter(new LevenbergMarquardtOptimizer());
        for (double x = 0.0; x < 1.3; x += 0.01) {
            fitter.addObservedPoint(1, x, f.value(x));
        }

        final double[] fitted = fitter.fit();
View Full Code Here

        final double w = 3.4;
        final double p = 4.1;
        HarmonicOscillator f = new HarmonicOscillator(a, w, p);

        HarmonicFitter fitter =
            new HarmonicFitter(new LevenbergMarquardtOptimizer());
        for (double x = 0.0; x < 10.0; x += 0.1) {
            fitter.addObservedPoint(1, x,
                                    f.value(x) + 0.01 * randomizer.nextGaussian());
        }

View Full Code Here

    @Test
    public void testTinyVariationsData() {
        Random randomizer = new Random(64925784252l);

        HarmonicFitter fitter =
            new HarmonicFitter(new LevenbergMarquardtOptimizer());
        for (double x = 0.0; x < 10.0; x += 0.1) {
            fitter.addObservedPoint(1, x, 1e-7 * randomizer.nextGaussian());
        }

        fitter.fit();
View Full Code Here

        final double w = 3.4;
        final double p = 4.1;
        HarmonicOscillator f = new HarmonicOscillator(a, w, p);

        HarmonicFitter fitter =
            new HarmonicFitter(new LevenbergMarquardtOptimizer());
        for (double x = 0.0; x < 10.0; x += 0.1) {
            fitter.addObservedPoint(1, x,
                                    f.value(x) + 0.01 * randomizer.nextGaussian());
        }

View Full Code Here

        final double w = 3.4;
        final double p = 4.1;
        HarmonicOscillator f = new HarmonicOscillator(a, w, p);

        HarmonicFitter fitter =
            new HarmonicFitter(new LevenbergMarquardtOptimizer());

        // build a regularly spaced array of measurements
        int size = 100;
        double[] xTab = new double[size];
        double[] yTab = new double[size];
View Full Code Here

public class CurveFitterTest {

    @Test
    public void testMath303() {

        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        CurveFitter fitter = new CurveFitter(optimizer);
        fitter.addObservedPoint(2.805d, 0.6934785852953367d);
        fitter.addObservedPoint(2.74333333333333d, 0.6306772025518496d);
        fitter.addObservedPoint(1.655d, 0.9474675497289684);
        fitter.addObservedPoint(1.725d, 0.9013594835804194d);
View Full Code Here

    }

    @Test
    public void testMath304() {

        LevenbergMarquardtOptimizer optimizer = new LevenbergMarquardtOptimizer();
        CurveFitter fitter = new CurveFitter(optimizer);
        fitter.addObservedPoint(2.805d, 0.6934785852953367d);
        fitter.addObservedPoint(2.74333333333333d, 0.6306772025518496d);
        fitter.addObservedPoint(1.655d, 0.9474675497289684);
        fitter.addObservedPoint(1.725d, 0.9013594835804194d);
View Full Code Here

TOP

Related Classes of org.apache.commons.math3.optimization.general.LevenbergMarquardtOptimizer

Copyright © 2018 www.massapicom. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.