Package org.apache.commons.math.ode.sampling

Examples of org.apache.commons.math.ode.sampling.NordsieckStepInterpolator.shift()

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            // discrete events handling
            System.arraycopy(yTmp, 0, y, 0, n);
            interpolator.reinitialize(stepEnd, stepSize, correctedScaled, nordsieckTmp);
            interpolator.storeTime(stepStart);
            interpolator.shift();
            interpolator.storeTime(stepEnd);
            stepStart = acceptStep(interpolator, y, yDot, t);
            scaled    = correctedScaled;
            nordsieck = nordsieckTmp;
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                }
            }

            // predict a first estimate of the state at step end
            final double stepEnd = stepStart + stepSize;
            interpolator.shift();
            interpolator.setInterpolatedTime(stepEnd);
            System.arraycopy(interpolator.getInterpolatedState(), 0, y, 0, y0.length);

            // evaluate the derivative
            computeDerivatives(stepEnd, y, yDot);
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                    updateHighOrderDerivativesPhase2(predictedScaled, correctedScaled, nordsieckTmp);

                    // discrete events handling
                    interpolatorTmp.reinitialize(stepEnd, stepSize, correctedScaled, nordsieckTmp);
                    interpolatorTmp.storeTime(stepStart);
                    interpolatorTmp.shift();
                    interpolatorTmp.storeTime(stepEnd);
                    if (manager.evaluateStep(interpolatorTmp)) {
                        final double dt = manager.getEventTime() - stepStart;
                        if (Math.abs(dt) <= Math.ulp(stepStart)) {
                            // rejecting the step would lead to a too small next step, we accept it
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                    updateHighOrderDerivativesPhase2(scaled, predictedScaled, nordsieckTmp);

                    // discrete events handling
                    interpolatorTmp.reinitialize(stepEnd, stepSize, predictedScaled, nordsieckTmp);
                    interpolatorTmp.storeTime(stepStart);
                    interpolatorTmp.shift();
                    interpolatorTmp.storeTime(stepEnd);
                    if (manager.evaluateStep(interpolatorTmp)) {
                        final double dt = manager.getEventTime() - stepStart;
                        if (Math.abs(dt) <= Math.ulp(stepStart)) {
                            // rejecting the step would lead to a too small next step, we accept it
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                    updateHighOrderDerivativesPhase2(scaled, predictedScaled, nordsieckTmp);

                    // discrete events handling
                    interpolatorTmp.reinitialize(stepEnd, stepSize, predictedScaled, nordsieckTmp);
                    interpolatorTmp.storeTime(stepStart);
                    interpolatorTmp.shift();
                    interpolatorTmp.storeTime(stepEnd);
                    if (manager.evaluateStep(interpolatorTmp)) {
                        final double dt = manager.getEventTime() - stepStart;
                        if (Math.abs(dt) <= Math.ulp(stepStart)) {
                            // we cannot simply truncate the step, reject the current computation
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                    updateHighOrderDerivativesPhase2(predictedScaled, correctedScaled, nordsieckTmp);

                    // discrete events handling
                    interpolatorTmp.reinitialize(stepEnd, stepSize, correctedScaled, nordsieckTmp);
                    interpolatorTmp.storeTime(stepStart);
                    interpolatorTmp.shift();
                    interpolatorTmp.storeTime(stepEnd);
                    if (manager.evaluateStep(interpolatorTmp)) {
                        final double dt = manager.getEventTime() - stepStart;
                        if (Math.abs(dt) <= Math.ulp(stepStart)) {
                            // we cannot simply truncate the step, reject the current computation
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