Package org.apache.commons.math3.ode.nonstiff

Examples of org.apache.commons.math3.ode.nonstiff.DormandPrince54Integrator.integrate()

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        SummaryStatistics residualsP0 = new SummaryStatistics();
        SummaryStatistics residualsP1 = new SummaryStatistics();
        for (double b = 2.88; b < 3.08; b += 0.001) {
            ParamBrusselator brusselator = new ParamBrusselator(b);
            double[] y = { 1.3, b };
            integ.integrate(brusselator, 0, y, 20.0, y);
            double[] yP = { 1.3, b + hP };
            brusselator.setParameter("b", b + hP);
            integ.integrate(brusselator, 0, yP, 20.0, yP);
            residualsP0.addValue((yP[0] - y[0]) / hP - brusselator.dYdP0());
            residualsP1.addValue((yP[1] - y[1]) / hP - brusselator.dYdP1());
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            ParamBrusselator brusselator = new ParamBrusselator(b);
            double[] y = { 1.3, b };
            integ.integrate(brusselator, 0, y, 20.0, y);
            double[] yP = { 1.3, b + hP };
            brusselator.setParameter("b", b + hP);
            integ.integrate(brusselator, 0, yP, 20.0, yP);
            residualsP0.addValue((yP[0] - y[0]) / hP - brusselator.dYdP0());
            residualsP1.addValue((yP[1] - y[1]) / hP - brusselator.dYdP1());
        }
        Assert.assertTrue((residualsP0.getMax() - residualsP0.getMin()) > 0.02);
        Assert.assertTrue((residualsP0.getMax() - residualsP0.getMin()) < 0.03);
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            efode.setTime(0);
            efode.setPrimaryState(z);
            jacob.registerVariationalEquations(efode);

            integ.setMaxEvaluations(5000);
            integ.integrate(efode, 20.0);
            jacob.getCurrentMainSetJacobian(dZdZ0);
            jacob.getCurrentParameterJacobian(ParamBrusselator.B, dZdP);
//            Assert.assertEquals(5000, integ.getMaxEvaluations());
//            Assert.assertTrue(integ.getEvaluations() > 1500);
//            Assert.assertTrue(integ.getEvaluations() < 2100);
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            efode.setTime(0);
            efode.setPrimaryState(z);
            jacob.registerVariationalEquations(efode);

            integ.setMaxEvaluations(5000);
            integ.integrate(efode, 20.0);
            jacob.getCurrentMainSetJacobian(dZdZ0);
            jacob.getCurrentParameterJacobian(Brusselator.B, dZdP);
//            Assert.assertEquals(5000, integ.getMaxEvaluations());
//            Assert.assertTrue(integ.getEvaluations() > 350);
//            Assert.assertTrue(integ.getEvaluations() < 510);
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        jacob.registerVariationalEquations(efode);

        integ.setMaxEvaluations(5000);

        double t = 18 * FastMath.PI;
        integ.integrate(efode, t);
        y = efode.getPrimaryState();
        for (int i = 0; i < y.length; ++i) {
            Assert.assertEquals(circle.exactY(t)[i], y[i], 1.0e-9);
        }

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        jacob.registerVariationalEquations(efode);

        integ.setMaxEvaluations(50000);

        double t = 18 * FastMath.PI;
        integ.integrate(efode, t);
        y = efode.getPrimaryState();
        for (int i = 0; i < y.length; ++i) {
            Assert.assertEquals(pcircle.exactY(t)[i], y[i], 1.0e-9);
        }

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        SummaryStatistics residualsP0 = new SummaryStatistics();
        SummaryStatistics residualsP1 = new SummaryStatistics();
        for (double b = 2.88; b < 3.08; b += 0.001) {
            Brusselator brusselator = new Brusselator(b);
            double[] y = { 1.3, b };
            integ.integrate(brusselator, 0, y, 20.0, y);
            double[] yP = { 1.3, b + hP };
            integ.integrate(brusselator, 0, yP, 20.0, yP);
            residualsP0.addValue((yP[0] - y[0]) / hP - brusselator.dYdP0());
            residualsP1.addValue((yP[1] - y[1]) / hP - brusselator.dYdP1());
        }
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        for (double b = 2.88; b < 3.08; b += 0.001) {
            Brusselator brusselator = new Brusselator(b);
            double[] y = { 1.3, b };
            integ.integrate(brusselator, 0, y, 20.0, y);
            double[] yP = { 1.3, b + hP };
            integ.integrate(brusselator, 0, yP, 20.0, yP);
            residualsP0.addValue((yP[0] - y[0]) / hP - brusselator.dYdP0());
            residualsP1.addValue((yP[1] - y[1]) / hP - brusselator.dYdP1());
        }
        Assert.assertTrue((residualsP0.getMax() - residualsP0.getMin()) > 500);
        Assert.assertTrue(residualsP0.getStandardDeviation() > 30);
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        SummaryStatistics residualsP0 = new SummaryStatistics();
        SummaryStatistics residualsP1 = new SummaryStatistics();
        for (double b = 2.88; b < 3.08; b += 0.001) {
            ParamBrusselator brusselator = new ParamBrusselator(b);
            double[] y = { 1.3, b };
            integ.integrate(brusselator, 0, y, 20.0, y);
            double[] yP = { 1.3, b + hP };
            brusselator.setParameter("b", b + hP);
            integ.integrate(brusselator, 0, yP, 20.0, yP);
            residualsP0.addValue((yP[0] - y[0]) / hP - brusselator.dYdP0());
            residualsP1.addValue((yP[1] - y[1]) / hP - brusselator.dYdP1());
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            ParamBrusselator brusselator = new ParamBrusselator(b);
            double[] y = { 1.3, b };
            integ.integrate(brusselator, 0, y, 20.0, y);
            double[] yP = { 1.3, b + hP };
            brusselator.setParameter("b", b + hP);
            integ.integrate(brusselator, 0, yP, 20.0, yP);
            residualsP0.addValue((yP[0] - y[0]) / hP - brusselator.dYdP0());
            residualsP1.addValue((yP[1] - y[1]) / hP - brusselator.dYdP1());
        }
        Assert.assertTrue((residualsP0.getMax() - residualsP0.getMin()) > 0.02);
        Assert.assertTrue((residualsP0.getMax() - residualsP0.getMin()) < 0.03);
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