Examples of org.apache.commons.math3.ode.TestProblem4$Stop

org.apache.commons.math3.ode.TestProblem4
This class is used in the junit tests for the ODE integrators.
This specific problem is the following differential equation :
```
 x'' = -x 
```
And when x decreases down to 0, the state should be changed as follows :
```
 x' -> -x' 
```
The theoretical solution of this problem is x = |sin(t+a)|

     * @param matrix matrix with columns representing variables to correlate
     * @return correlation matrix
     */
    public RealMatrix computeCorrelationMatrix(final RealMatrix matrix) {
        int nVars = matrix.getColumnDimension();
        RealMatrix outMatrix = new BlockRealMatrix(nVars, nVars);
        for (int i = 0; i < nVars; i++) {
            for (int j = 0; j < i; j++) {
                double corr = correlation(matrix.getColumn(i), matrix.getColumn(j));
                outMatrix.setEntry(i, j, corr);
                outMatrix.setEntry(j, i, corr);
            }
            outMatrix.setEntry(i, i, 1d);
        }
        return outMatrix;
    }

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        // solve the rectangular system in the least square sense
        // to get the best estimate of the Nordsieck vector [s2 ... sk]
        QRDecomposition decomposition;
        decomposition = new QRDecomposition(new Array2DRowRealMatrix(a, false));
        RealMatrix x = decomposition.getSolver().solve(new Array2DRowRealMatrix(b, false));
        return new Array2DRowRealMatrix(x.getData(), false);
    }

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        double[] qtf     = new double[nR];
        double[] work1   = new double[nC];
        double[] work2   = new double[nC];
        double[] work3   = new double[nC];


        final RealMatrix weightMatrixSqrt = getWeightSquareRoot();


        // Evaluate the function at the starting point and calculate its norm.
        double[] currentObjective = computeObjectiveValue(currentPoint);
        double[] currentResiduals = computeResiduals(currentObjective);
        PointVectorValuePair current = new PointVectorValuePair(currentPoint, currentObjective);
        double currentCost = computeCost(currentResiduals);


        // Outer loop.
        lmPar = 0;
        boolean firstIteration = true;
        final ConvergenceChecker<PointVectorValuePair> checker = getConvergenceChecker();
        while (true) {
            incrementIterationCount();


            final PointVectorValuePair previous = current;


            // QR decomposition of the jacobian matrix
            qrDecomposition(computeWeightedJacobian(currentPoint));


            weightedResidual = weightMatrixSqrt.operate(currentResiduals);
            for (int i = 0; i < nR; i++) {
                qtf[i] = weightedResidual[i];
            }


            // compute Qt.res

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    for (SiteWithPolynomial site : sites) {
      
      List<SiteWithPolynomial> nearestSites =
          nearestSiteMap.get(site);
      
      RealVector vector = new ArrayRealVector(SITES_FOR_APPROX);
      RealMatrix matrix = new Array2DRowRealMatrix(
          SITES_FOR_APPROX, DefaultPolynomial.NUM_COEFFS);
      
      for (int row = 0; row < SITES_FOR_APPROX; row++) {
        SiteWithPolynomial nearSite = nearestSites.get(row);
        DefaultPolynomial.populateMatrix(matrix, row, nearSite.pos.x, nearSite.pos.z);
        vector.setEntry(row, nearSite.pos.y);
      }
      
      QRDecomposition qr = new QRDecomposition(matrix);
      RealVector solution = qr.getSolver().solve(vector);
        
      double[] coeffs = solution.toArray();
      
      for (double coeff : coeffs) {
        if (coeff > 10e3) {
          continue calculatePolynomials;
        }

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                return Double.compare(weightedResidual(o1),
                                      weightedResidual(o2));
            }


            private double weightedResidual(final PointVectorValuePair pv) {
                final RealVector v = new ArrayRealVector(pv.getValueRef(), false);
                final RealVector r = target.subtract(v);
                return r.dotProduct(weight.operate(r));
            }
        };
    }

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            // predict a first estimate of the state at step end
            final double stepEnd = stepStart + stepSize;
            interpolator.shift();
            interpolator.setInterpolatedTime(stepEnd);
            final ExpandableStatefulODE expandable = getExpandable();
            final EquationsMapper primary = expandable.getPrimaryMapper();
            primary.insertEquationData(interpolator.getInterpolatedState(), y);
            int index = 0;
            for (final EquationsMapper secondary : expandable.getSecondaryMappers()) {
                secondary.insertEquationData(interpolator.getInterpolatedSecondaryState(index), y);
                ++index;
            }

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            // predict a first estimate of the state at step end
            final double stepEnd = stepStart + stepSize;
            interpolator.shift();
            interpolator.setInterpolatedTime(stepEnd);
            final ExpandableStatefulODE expandable = getExpandable();
            final EquationsMapper primary = expandable.getPrimaryMapper();
            primary.insertEquationData(interpolator.getInterpolatedState(), y);
            int index = 0;
            for (final EquationsMapper secondary : expandable.getSecondaryMappers()) {
                secondary.insertEquationData(interpolator.getInterpolatedSecondaryState(index), y);
                ++index;
            }


            // evaluate the derivative

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  @Test
  public void testEvents()
      throws DimensionMismatchException, NumberIsTooSmallException,
             MaxCountExceededException, NoBracketingException {


    TestProblem4 pb = new TestProblem4();
    double minStep = 0;
    double maxStep = pb.getFinalTime() - pb.getInitialTime();
    double scalAbsoluteTolerance = 1.0e-9;
    double scalRelativeTolerance = 0.01 * scalAbsoluteTolerance;


    FirstOrderIntegrator integ = new DormandPrince853Integrator(minStep, maxStep,
                                                                scalAbsoluteTolerance,
                                                                scalRelativeTolerance);
    TestProblemHandler handler = new TestProblemHandler(pb, integ);
    integ.addStepHandler(handler);
    EventHandler[] functions = pb.getEventsHandlers();
    double convergence = 1.0e-8 * maxStep;
    for (int l = 0; l < functions.length; ++l) {
      integ.addEventHandler(functions[l], Double.POSITIVE_INFINITY, convergence, 1000);
    }
    Assert.assertEquals(functions.length, integ.getEventHandlers().size());
    integ.integrate(pb,
                    pb.getInitialTime(), pb.getInitialState(),
                    pb.getFinalTime(), new double[pb.getDimension()]);


    Assert.assertEquals(0, handler.getMaximalValueError(), 2.1e-7);
    Assert.assertEquals(0, handler.getMaximalTimeError(), convergence);
    Assert.assertEquals(12.0, handler.getLastTime(), convergence);
    integ.clearEventHandlers();

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  @Test
  public void testEvents()
      throws DimensionMismatchException, NumberIsTooSmallException,
             MaxCountExceededException, NoBracketingException {


    TestProblem4 pb = new TestProblem4();
    double minStep = 0;
    double maxStep = pb.getFinalTime() - pb.getInitialTime();
    double scalAbsoluteTolerance = 1.0e-8;
    double scalRelativeTolerance = 0.01 * scalAbsoluteTolerance;


    FirstOrderIntegrator integ = new DormandPrince54Integrator(minStep, maxStep,
                                                               scalAbsoluteTolerance,
                                                               scalRelativeTolerance);
    TestProblemHandler handler = new TestProblemHandler(pb, integ);
    integ.addStepHandler(handler);
    EventHandler[] functions = pb.getEventsHandlers();
    double convergence = 1.0e-8 * maxStep;
    for (int l = 0; l < functions.length; ++l) {
      integ.addEventHandler(functions[l],
                                 Double.POSITIVE_INFINITY, convergence, 1000);
    }
    Assert.assertEquals(functions.length, integ.getEventHandlers().size());
    integ.integrate(pb,
                    pb.getInitialTime(), pb.getInitialState(),
                    pb.getFinalTime(), new double[pb.getDimension()]);


    Assert.assertTrue(handler.getMaximalValueError() < 5.0e-6);
    Assert.assertEquals(0, handler.getMaximalTimeError(), convergence);
    Assert.assertEquals(12.0, handler.getLastTime(), convergence);
    integ.clearEventHandlers();

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  @Test
  public void testEvents()
      throws DimensionMismatchException, NumberIsTooSmallException,
             MaxCountExceededException, NoBracketingException {


    TestProblem4 pb = new TestProblem4();
    double minStep = 0;
    double maxStep = pb.getFinalTime() - pb.getInitialTime();
    double scalAbsoluteTolerance = 1.0e-8;
    double scalRelativeTolerance = 0.01 * scalAbsoluteTolerance;


    FirstOrderIntegrator integ = new HighamHall54Integrator(minStep, maxStep,
                                                            scalAbsoluteTolerance,
                                                            scalRelativeTolerance);
    TestProblemHandler handler = new TestProblemHandler(pb, integ);
    integ.addStepHandler(handler);
    EventHandler[] functions = pb.getEventsHandlers();
    double convergence = 1.0e-8 * maxStep;
    for (int l = 0; l < functions.length; ++l) {
      integ.addEventHandler(functions[l],
                                 Double.POSITIVE_INFINITY, convergence, 1000);
    }
    Assert.assertEquals(functions.length, integ.getEventHandlers().size());
    integ.integrate(pb,
                    pb.getInitialTime(), pb.getInitialState(),
                    pb.getFinalTime(), new double[pb.getDimension()]);


    Assert.assertTrue(handler.getMaximalValueError() < 1.0e-7);
    Assert.assertEquals(0, handler.getMaximalTimeError(), convergence);
    Assert.assertEquals(12.0, handler.getLastTime(), convergence);
    integ.clearEventHandlers();

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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

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