Package org.apache.commons.math.linear

Examples of org.apache.commons.math.linear.Array2DRowRealMatrix.walkInOptimizedOrder()

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                               1e-14);
        RealMatrix errors =
            new Array2DRowRealMatrix(regression.estimateRegressionParametersVariance(), false);
        final double[] s = { 1.0, -1.0 /  2.0, -1.0 /  3.0, -1.0 /  4.0, -1.0 /  5.0, -1.0 /  6.0 };
        RealMatrix referenceVariance = new Array2DRowRealMatrix(s.length, s.length);
        referenceVariance.walkInOptimizedOrder(new DefaultRealMatrixChangingVisitor() {
            @Override
            public double visit(int row, int column, double value)
                throws MatrixVisitorException {
                if (row == 0) {
                    return s[column];
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                }
                nordsieckTmp = updateHighOrderDerivativesPhase1(nordsieck);
                updateHighOrderDerivativesPhase2(scaled, predictedScaled, nordsieckTmp);

                // apply correction (C in the PECE sequence)
                error = nordsieckTmp.walkInOptimizedOrder(new Corrector(y, predictedScaled, yTmp));

                if (error >= 1.0) {
                    // reject the step and attempt to reduce error by stepsize control
                    final double factor = computeStepGrowShrinkFactor(error);
                    hNew = filterStep(stepSize * factor, forward, false);
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                               1e-14);
        RealMatrix errors =
            new Array2DRowRealMatrix(regression.estimateRegressionParametersVariance(), false);
        final double[] s = { 1.0, -1.0 /  2.0, -1.0 /  3.0, -1.0 /  4.0, -1.0 /  5.0, -1.0 /  6.0 };
        RealMatrix referenceVariance = new Array2DRowRealMatrix(s.length, s.length);
        referenceVariance.walkInOptimizedOrder(new DefaultRealMatrixChangingVisitor() {
            @Override
            public double visit(int row, int column, double value) {
                if (row == 0) {
                    return s[column];
                }
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                }
                final Array2DRowRealMatrix nordsieckTmp = updateHighOrderDerivativesPhase1(nordsieck);
                updateHighOrderDerivativesPhase2(scaled, predictedScaled, nordsieckTmp);

                // apply correction (C in the PECE sequence)
                error = nordsieckTmp.walkInOptimizedOrder(new Corrector(y, predictedScaled, yTmp));

                if (error <= 1.0) {

                    // evaluate a final estimate of the derivative (second E in the PECE sequence)
                    computeDerivatives(stepEnd, yTmp, yDot);
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                               1e-14);
        RealMatrix errors =
            new Array2DRowRealMatrix(regression.estimateRegressionParametersVariance(), false);
        final double[] s = { 1.0, -1.0 /  2.0, -1.0 /  3.0, -1.0 /  4.0, -1.0 /  5.0, -1.0 /  6.0 };
        RealMatrix referenceVariance = new Array2DRowRealMatrix(s.length, s.length);
        referenceVariance.walkInOptimizedOrder(new DefaultRealMatrixChangingVisitor() {
            @Override
            public double visit(int row, int column, double value)
                throws MatrixVisitorException {
                if (row == 0) {
                    return s[column];
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                }
                final Array2DRowRealMatrix nordsieckTmp = updateHighOrderDerivativesPhase1(nordsieck);
                updateHighOrderDerivativesPhase2(scaled, predictedScaled, nordsieckTmp);

                // apply correction (C in the PECE sequence)
                error = nordsieckTmp.walkInOptimizedOrder(new Corrector(y, predictedScaled, yTmp));

                if (error <= 1.0) {

                    // evaluate a final estimate of the derivative (second E in the PECE sequence)
                    computeDerivatives(stepEnd, yTmp, yDot);
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