Package org.apache.commons.math3.optimization

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


        circle.addPoint(110.0, -20.0);
        circle.addPoint( 35.015.0);
        circle.addPoint( 45.097.0);

        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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     * Simple constructor with default settings.
     * The convergence check is set to a {@link SimpleVectorValueChecker} and
     * the allowed number of evaluations is set to {@link Integer#MAX_VALUE}.
     */
    protected BaseAbstractMultivariateVectorOptimizer() {
        this(new SimpleVectorValueChecker());
    }
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     * @param useLU If {@code true}, the normal equations will be solved
     * using LU decomposition, otherwise they will be solved using QR
     * decomposition.
     */
    public GaussNewtonOptimizer(final boolean useLU) {
        this(useLU, new SimpleVectorValueChecker());
    }
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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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     * decomposition.
     * @deprecated See {@link SimpleVectorValueChecker#SimpleVectorValueChecker()}
     */
    @Deprecated
    public GaussNewtonOptimizer(final boolean useLU) {
        this(useLU, new SimpleVectorValueChecker());
    }
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public class GaussNewtonOptimizerTest
    extends AbstractLeastSquaresOptimizerAbstractTest {

    @Override
    public AbstractLeastSquaresOptimizer createOptimizer() {
        return new GaussNewtonOptimizer(new SimpleVectorValueChecker(1.0e-6, 1.0e-6));
    }
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