Example usage for org.apache.commons.math3.linear RealVector toArray

Introduction

In this page you can find the example usage for org.apache.commons.math3.linear RealVector toArray.

Prototype

public double[] toArray()

Source Link

Document

Convert the vector to an array of double s.

Usage

From source file:uk.ac.diamond.scisoft.analysis.optimize.ApacheOptimizer.java

/**
 * create a multivariateJacobianFunction from MVF and MMF (using builder?)
 * /*w  w w . j a va  2s  .c om*/
 */
private void internalLeastSquaresOptimize() {
    LeastSquaresOptimizer opt = createLeastSquaresOptimizer();

    try {

        LeastSquaresBuilder builder = new LeastSquaresBuilder().model(createJacobianFunction())
                .target(data.getData()).start(getParameterValues()).lazyEvaluation(false)
                .maxEvaluations(MAX_EVAL).maxIterations(MAX_ITER);

        builder.checker(new EvaluationRmsChecker(REL_TOL, ABS_TOL));

        if (weight != null) {
            builder.weight(MatrixUtils.createRealDiagonalMatrix(weight.getData()));
        }

        // TODO add checker, validator
        LeastSquaresProblem problem = builder.build();

        Optimum result = opt.optimize(problem);

        RealVector res = result.getPoint();
        setParameterValues(
                res instanceof ArrayRealVector ? ((ArrayRealVector) res).getDataRef() : res.toArray());
        try {
            RealVector err = result.getSigma(1e-14);

            //            sqrt(S / (n - m) * C[i][i]);
            double c = result.getCost();
            int n = data.getSize();
            int m = getParameterValues().length;

            double[] s = err instanceof ArrayRealVector ? ((ArrayRealVector) err).getDataRef() : err.toArray();

            errors = new double[s.length];

            for (int i = 0; i < errors.length; i++)
                errors[i] = Math.sqrt(((c * c) / ((n - m)) * (s[i] * s[i])));

        } catch (SingularMatrixException e) {
            logger.warn("Could not find errors as covariance matrix was singular");
        }

        logger.trace("Residual: {} from {}", result.getRMS(), Math.sqrt(calculateResidual()));
    } catch (Exception e) {
        logger.error("Problem with least squares optimizer", e);
        throw new IllegalArgumentException("Problem with least squares optimizer");
    }
}

From source file:USVProsjekt.ThrustAllocator.java

public double[] calculateOutput(double[] tau) throws Exception {
    //        long time1 = System.currentTimeMillis();
    // Sett opp p-vektoren med nskede verdier for tau (kraftvektor)
    p.setEntry(0, tau[0]);//from www  . j a  v  a  2  s  . c o  m
    p.setEntry(1, tau[1]);
    p.setEntry(2, tau[2]);

    // Oppsett for ulikheten A2*z <= C2*p
    RealVector v2 = C2.operate(p);

    for (int i = 0; i < 8; i++) {
        // Hver ulikhet settes opp som et LinearMultivariateRealFunction
        inequalities[i] = new LinearMultivariateRealFunction(A2.getRow(i), -v2.toArray()[i]);
    }
    // Optimaliseringsproblemet
    OptimizationRequest or = new OptimizationRequest();
    // Sett objektivfunksjonen
    or.setF0(objectiveFunction);

    // Sett ulikheten
    or.setFi(inequalities);

    // Sett likheten
    or.setA(A1);
    or.setB(p.getSubVector(0, 3).toArray());

    // Sett toleransen p resultatet. Lavere tall = strre nyaktighet
    or.setTolerance(1.E-1);

    // Optimalisering

    opt.setOptimizationRequest(or);
    int returnCode = opt.optimize();

    if (returnCode == OptimizationResponse.FAILED) {
        System.out.println("Optimization FAIL");
    }
    //        long time2 = System.currentTimeMillis()-time1;
    //System.out.println("Tidsbruk = " + time2);
    return opt.getOptimizationResponse().getSolution();

}