Package org.apache.commons.math3.optimization

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


    for (SiteWithPolynomial site : sites) {
     
      List<SiteWithPolynomial> nearestSites =
          nearestSiteMap.get(site);
     
      RealVector vector = new ArrayRealVector(SITES_FOR_APPROX);
      RealMatrix matrix = new Array2DRowRealMatrix(
          SITES_FOR_APPROX, DefaultPolynomial.NUM_COEFFS);
     
      for (int row = 0; row < SITES_FOR_APPROX; row++) {
        SiteWithPolynomial nearSite = nearestSites.get(row);
        DefaultPolynomial.populateMatrix(matrix, row, nearSite.pos.x, nearSite.pos.z);
        vector.setEntry(row, nearSite.pos.y);
      }
     
      QRDecomposition qr = new QRDecomposition(matrix);
      RealVector solution = qr.getSolver().solve(vector);
       
      double[] coeffs = solution.toArray();
     
      for (double coeff : coeffs) {
        if (coeff > 10e3) {
          continue calculatePolynomials;
        }
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                return Double.compare(weightedResidual(o1),
                                      weightedResidual(o2));
            }

            private double weightedResidual(final PointVectorValuePair pv) {
                final RealVector v = new ArrayRealVector(pv.getValueRef(), false);
                final RealVector r = target.subtract(v);
                return r.dotProduct(weight.operate(r));
            }
        };
    }
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        // Multi-start loop.
        for (int i = 0; i < starts; i++) {
            // CHECKSTYLE: stop IllegalCatch
            try {
                // Decrease number of allowed evaluations.
                optimData[maxEvalIndex] = new MaxEval(maxEval - totalEvaluations);
                // New start value.
                final double s = (i == 0) ?
                    startValue :
                    min + generator.nextDouble() * (max - min);
                optimData[searchIntervalIndex] = new SearchInterval(min, max, s);
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     * decomposition.
     * @deprecated See {@link SimpleVectorValueChecker#SimpleVectorValueChecker()}
     */
    @Deprecated
    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.

        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 class GaussNewtonOptimizerTest
    extends AbstractLeastSquaresOptimizerAbstractTest {

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