Package org.apache.commons.math3.linear

Examples of org.apache.commons.math3.linear.DiagonalMatrix

595
596
597
598
599
600
601
602
            final double[] weights = new double[target.length];
            Arrays.fill(weights, 1.0);
            return base()
                    .model(getModelFunction(), getModelFunctionJacobian())
                    .target(target)
                    .weight(new DiagonalMatrix(weights))
                    .start(new double[factors.getColumnDimension()]);
        }
View Full Code Here
39
40
41
42
43
44
45
     * Creates a diagonal weight matrix.
     *
     * @param weight List of the values of the diagonal.
     */
    public Weight(double[] weight) {
        weightMatrix = new DiagonalMatrix(weight);
    }
View Full Code Here
52
53
54
55
56
57
58
59
        Arrays.fill(weights, 1d);

        return new LeastSquaresBuilder()
                .model(problem.getModelFunction(), problem.getModelFunctionJacobian())
                .target(observed)
                .weight(new DiagonalMatrix(weights))
                .start(start);
    }
View Full Code Here
121
122
123
124
125
126
127
128
129
130
131
    @Test
    public void testComputeValueAndJacobian() {
        //setup
        final RealVector point = new ArrayRealVector(new double[]{1, 2});
        Evaluation evaluation = new LeastSquaresBuilder()
                .weight(new DiagonalMatrix(new double[]{16, 4}))
                .model(new MultivariateJacobianFunction() {
                    public Pair<RealVector, RealMatrix> value(RealVector actualPoint) {
                        //verify correct values passed in
                        Assert.assertArrayEquals(
                                point.toArray(), actualPoint.toArray(), Precision.EPSILON);
View Full Code Here
58
59
60
61
62
63
64
    public LeastSquaresBuilder builder(CircleProblem problem){
        return base()
                .model(problem.getModelFunction(), problem.getModelFunctionJacobian())
                .target(problem.target())
                .weight(new DiagonalMatrix(problem.weight()));
    }
View Full Code Here
191
192
193
194
195
196
197
198
199
200
201
        }

        final Optimum optimum = optimizer.optimize(
                builder(problem)
                        .target(dataPoints[1])
                        .weight(new DiagonalMatrix(weights))
                        .start(start)
                        .maxIterations(20)
                        .build()
        );
View Full Code Here
507
508
509
510
511
512
513
514
515
516
517
        LeastSquaresProblem problem = new LeastSquaresBuilder()
                .maxEvaluations(400 * (function.getN() + 1))
                .maxIterations(2000)
                .model(function.getModelFunction(), function.getModelFunctionJacobian())
                .target(function.getTarget())
                .weight(new DiagonalMatrix(function.getWeight()))
                .start(function.getStartPoint())
                .build();

        try {
            final Optimum optimum = optimizer.optimize(problem);
View Full Code Here
563
564
565
566
567
568
569
570
571
572
573
574
575
     * @return the square-root of the weight matrix.
     */
    private RealMatrix squareRoot(RealMatrix m) {
        if (m instanceof DiagonalMatrix) {
            final int dim = m.getRowDimension();
            final RealMatrix sqrtM = new DiagonalMatrix(dim);
            for (int i = 0; i < dim; i++) {
               sqrtM.setEntry(i, i, FastMath.sqrt(m.getEntry(i, i)));
            }
            return sqrtM;
        } else {
            final EigenDecomposition dec = new EigenDecomposition(m);
            return dec.getSquareRoot();
View Full Code Here
288
289
290
291
292
293
294
295
296
    LeastSquaresBuilder builder(StraightLineProblem problem){
        return new LeastSquaresBuilder()
                .model(problem.getModelFunction(), problem.getModelFunctionJacobian())
                .target(problem.target())
                .weight(new DiagonalMatrix(problem.weight()))
                //unused start point to avoid NPE
                .start(new double[2]);
    }
View Full Code Here
42
43
44
45
46
47
48
     * Creates a diagonal weight matrix.
     *
     * @param weight List of the values of the diagonal.
     */
    public Weight(double[] weight) {
        weightMatrix = new DiagonalMatrix(weight);
    }
View Full Code Here
TOP

Related Classes of org.apache.commons.math3.linear.DiagonalMatrix

  • 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.MultivariateFunction
  • org.apache.commons.math3.analysis.QuinticFunction
  • org.apache.commons.math3.analysis.solvers.BrentSolver
  • org.apache.commons.math3.analysis.UnivariateFunction
  • org.apache.commons.math3.complex.Complex
    • 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.