Class DormandPrince54Integrator

All Implemented Interfaces:
FirstOrderIntegrator, ODEIntegrator

public class DormandPrince54Integrator extends EmbeddedRungeKuttaIntegrator
This class implements the 5(4) Dormand-Prince integrator for Ordinary Differential Equations.

This integrator is an embedded Runge-Kutta integrator of order 5(4) used in local extrapolation mode (i.e. the solution is computed using the high order formula) with stepsize control (and automatic step initialization) and continuous output. This method uses 7 functions evaluations per step. However, since this is an fsal, the last evaluation of one step is the same as the first evaluation of the next step and hence can be avoided. So the cost is really 6 functions evaluations per step.

This method has been published (whithout the continuous output that was added by Shampine in 1986) in the following article :

  A family of embedded Runge-Kutta formulae
  J. R. Dormand and P. J. Prince
  Journal of Computational and Applied Mathematics
  volume 6, no 1, 1980, pp. 19-26
 

Since:
1.2
  • Constructor Details

    • DormandPrince54Integrator

      public DormandPrince54Integrator(double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)
      Simple constructor. Build a fifth order Dormand-Prince integrator with the given step bounds
      Parameters:
      minStep - minimal step (must be positive even for backward integration), the last step can be smaller than this
      maxStep - maximal step (must be positive even for backward integration)
      scalAbsoluteTolerance - allowed absolute error
      scalRelativeTolerance - allowed relative error
    • DormandPrince54Integrator

      public DormandPrince54Integrator(double minStep, double maxStep, double[] vecAbsoluteTolerance, double[] vecRelativeTolerance)
      Simple constructor. Build a fifth order Dormand-Prince integrator with the given step bounds
      Parameters:
      minStep - minimal step (must be positive even for backward integration), the last step can be smaller than this
      maxStep - maximal step (must be positive even for backward integration)
      vecAbsoluteTolerance - allowed absolute error
      vecRelativeTolerance - allowed relative error
  • Method Details