Package org.apache.commons.math3.optim

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

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    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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        }
        this.xDegree = xDegree;
        this.yDegree = yDegree;

        final double safeFactor = 1e2;
        final SimpleVectorValueChecker checker
            = new SimpleVectorValueChecker(safeFactor * Precision.EPSILON,
                                           safeFactor * Precision.SAFE_MIN);
        xFitter = new PolynomialFitter(new GaussNewtonOptimizer(false, checker));
        yFitter = new PolynomialFitter(new GaussNewtonOptimizer(false, checker));
    }
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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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        circle.addPoint(110.0, -20.0);
        circle.addPoint( 35.0,  15.0);
        circle.addPoint( 45.0,  97.0);

        GaussNewtonOptimizer optimizer
            = new GaussNewtonOptimizer(new SimpleVectorValueChecker(1e-30, 1e-30));

        optimizer.optimize(new MaxEval(100),
                           circle.getModelFunction(),
                           circle.getModelFunctionJacobian(),
                           new Target(new double[] { 0, 0, 0, 0, 0 }),
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        circle.addPoint(110.0, -20.0);
        circle.addPoint( 35.0,  15.0);
        circle.addPoint( 45.0,  97.0);

        LeastSquaresProblem lsp = builder(circle)
                .checkerPair(new SimpleVectorValueChecker(1e-30, 1e-30))
                .maxIterations(Integer.MAX_VALUE)
                .start(new double[]{98.680, 47.345})
                .build();

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

        LeastSquaresProblem lsp = builder(circle)
                .checkerPair(new SimpleVectorValueChecker(1e-30, 1e-30))
                .maxIterations(Integer.MAX_VALUE)
                .start(new double[]{98.680, 47.345})
                .build();

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

        LeastSquaresProblem lsp = builder(circle)
                .checkerPair(new SimpleVectorValueChecker(1e-30, 1e-30))
                .maxIterations(Integer.MAX_VALUE)
                .start(new double[]{98.680, 47.345})
                .build();

        optimizer.optimize(lsp);
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    /** default absolute tolerance of comparisons */
    public static final double TOl = 1e-10;

    public LeastSquaresBuilder base() {
        return new LeastSquaresBuilder()
                .checkerPair(new SimpleVectorValueChecker(1e-6, 1e-6))
                .maxEvaluations(100)
                .maxIterations(getMaxIterations());
    }
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Related Classes of org.apache.commons.math3.optim.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.interpolation.SmoothingPolynomialBicubicSplineInterpolator
  • 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
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