Package org.apache.commons.math3.linear

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


     * Creates a diagonal weight matrix.
     *
     * @param weight List of the values of the diagonal.
     */
    public Weight(double[] weight) {
        weightMatrix = new DiagonalMatrix(weight);
    }
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     * @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();
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     * Creates a diagonal weight matrix.
     *
     * @param weight List of the values of the diagonal.
     */
    public Weight(double[] weight) {
        weightMatrix = new DiagonalMatrix(weight);
    }
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     * Creates a diagonal weight matrix.
     *
     * @param weight List of the values of the diagonal.
     */
    public Weight(double[] weight) {
        weightMatrix = new DiagonalMatrix(weight);
    }
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     * @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();
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        return new LeastSquaresBuilder().
                maxEvaluations(Integer.MAX_VALUE).
                maxIterations(maxIter).
                start(startPoint).
                target(target).
                weight(new DiagonalMatrix(weights)).
                model(model.getModelFunction(), model.getModelFunctionJacobian()).
                build();

    }
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        return new LeastSquaresBuilder().
                maxEvaluations(Integer.MAX_VALUE).
                maxIterations(maxIter).
                start(initialGuess).
                target(target).
                weight(new DiagonalMatrix(weights)).
                model(model.getModelFunction(), model.getModelFunctionJacobian()).
                build();

    }
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     *         {@code problem} is not modified.
     */
    public static LeastSquaresProblem weightDiagonal(final LeastSquaresProblem problem,
                                                     final RealVector weights) {
        // TODO more efficient implementation
        return weightMatrix(problem, new DiagonalMatrix(weights.toArray()));
    }
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     * @return the square-root of the weight matrix.
     */
    private static RealMatrix squareRoot(final 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();
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        return new LeastSquaresBuilder().
                maxEvaluations(Integer.MAX_VALUE).
                maxIterations(maxIter).
                start(startPoint).
                target(target).
                weight(new DiagonalMatrix(weights)).
                model(model.getModelFunction(), model.getModelFunctionJacobian()).
                build();

    }
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