Package org.hipparchus.ode

Class MultistepIntegrator

java.lang.Object

org.hipparchus.ode.AbstractIntegrator

org.hipparchus.ode.nonstiff.AdaptiveStepsizeIntegrator

org.hipparchus.ode.MultistepIntegrator

All Implemented Interfaces:

ODEIntegrator

Direct Known Subclasses:

AdamsIntegrator

public abstract class MultistepIntegrator
extends AdaptiveStepsizeIntegrator

This class is the base class for multistep integrators for Ordinary Differential Equations.

We define scaled derivatives s_i(n) at step n as: \[ \left\{\begin{align} s_1(n) &= h y'_n \text{ for first derivative}\\ s_2(n) &= \frac{h^2}{2} y_n'' \text{ for second derivative}\\ s_3(n) &= \frac{h^3}{6} y_n''' \text{ for third derivative}\\ &\cdots\\ s_k(n) &= \frac{h^k}{k!} y_n^{(k)} \text{ for } k^\mathrm{th} \text{ derivative} \end{align}\right. \]

Rather than storing several previous steps separately, this implementation uses the Nordsieck vector with higher degrees scaled derivatives all taken at the same step (y_n, s₁(n) and r_n) where r_n is defined as: \[ r_n = [ s_2(n), s_3(n) \ldots s_k(n) ]^T \] (we omit the k index in the notation for clarity)

Multistep integrators with Nordsieck representation are highly sensitive to large step changes because when the step is multiplied by factor a, the k^th component of the Nordsieck vector is multiplied by a^k and the last components are the least accurate ones. The default max growth factor is therefore set to a quite low value: 2^1/order.

See Also:

• AdamsBashforthIntegrator
• AdamsMoultonIntegrator

Field Summary

Fields

Modifier and Type	Field	Description
protected Array2DRowRealMatrix	nordsieck	Nordsieck matrix of the higher scaled derivatives.
protected double[]	scaled	First scaled derivative (h y').

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	MultistepIntegrator(String name, int nSteps, int order, double minStep, double maxStep, double[] vecAbsoluteTolerance, double[] vecRelativeTolerance)	Build a multistep integrator with the given stepsize bounds.
protected	MultistepIntegrator(String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)	Build a multistep integrator with the given stepsize bounds.

Method Summary

Modifier and Type	Method	Description
protected double	computeStepGrowShrinkFactor(double error)	Compute step grow/shrink factor according to normalized error.
double	getMaxGrowth()	Get the maximal growth factor for stepsize control.
double	getMinReduction()	Get the minimal reduction factor for stepsize control.
int	getNSteps()	Get the number of steps of the multistep method (excluding the one being computed).
double	getSafety()	Get the safety factor for stepsize control.
ODEIntegrator	getStarterIntegrator()	Get the starter integrator.
protected abstract Array2DRowRealMatrix	initializeHighOrderDerivatives(double h, double[] t, double[][] y, double[][] yDot)	Initialize the high order scaled derivatives at step start.
protected void	rescale(double newStepSize)	Rescale the instance.
void	setMaxGrowth(double maxGrowth)	Set the maximal growth factor for stepsize control.
void	setMinReduction(double minReduction)	Set the minimal reduction factor for stepsize control.
void	setSafety(double safety)	Set the safety factor for stepsize control.
void	setStarterIntegrator(ODEIntegrator starterIntegrator)	Set the starter integrator.
protected void	start(ExpandableODE equations, ODEState initialState, double finalTime)	Start the integration.

Methods inherited from class org.hipparchus.ode.nonstiff.AdaptiveStepsizeIntegrator

getMaxStep, getMinStep, getStepSizeHelper, initializeStep, resetInternalState, sanityChecks, setInitialStepSize, setStepSizeControl, setStepSizeControl

Methods inherited from class org.hipparchus.ode.AbstractIntegrator

acceptStep, addEventDetector, addStepEndHandler, addStepHandler, clearEventDetectors, clearStepEndHandlers, clearStepHandlers, computeDerivatives, getCurrentSignedStepsize, getEquations, getEvaluations, getEvaluationsCounter, getEventDetectors, getMaxEvaluations, getName, getStepEndHandlers, getStepHandlers, getStepSize, getStepStart, incrementEvaluations, initIntegration, isLastStep, resetOccurred, setIsLastStep, setMaxEvaluations, setStateInitialized, setStepSize, setStepStart

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.hipparchus.ode.ODEIntegrator

integrate, integrate

Field Details

scaled

protected double[] scaled

First scaled derivative (h y').

nordsieck

protected Array2DRowRealMatrix nordsieck

Nordsieck matrix of the higher scaled derivatives.

(h²/2 y'', h³/6 y''' ..., h^k/k! y^(k))

Constructor Details

MultistepIntegrator

protected MultistepIntegrator(String name,
 int nSteps,
 int order,
 double minStep,
 double maxStep,
 double scalAbsoluteTolerance,
 double scalRelativeTolerance)
                       throws MathIllegalArgumentException

Build a multistep integrator with the given stepsize bounds.

The default starter integrator is set to the Dormand-Prince 8(5,3) integrator with some defaults settings.

The default max growth factor is set to a quite low value: 2^1/order.

Parameters:

name - name of the method

nSteps - number of steps of the multistep method (excluding the one being computed)

order - order of the method

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

Throws:

MathIllegalArgumentException - if number of steps is smaller than 2

MultistepIntegrator

protected MultistepIntegrator(String name,
 int nSteps,
 int order,
 double minStep,
 double maxStep,
 double[] vecAbsoluteTolerance,
 double[] vecRelativeTolerance)

Build a multistep integrator with the given stepsize bounds.

The default starter integrator is set to the Dormand-Prince 8(5,3) integrator with some defaults settings.

The default max growth factor is set to a quite low value: 2^1/order.

Parameters:

name - name of the method

nSteps - number of steps of the multistep method (excluding the one being computed)

order - order of the method

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

getStarterIntegrator

public ODEIntegrator getStarterIntegrator()

Get the starter integrator.

Returns:

starter integrator

setStarterIntegrator

public void setStarterIntegrator(ODEIntegrator starterIntegrator)

Set the starter integrator.

The various step and event handlers for this starter integrator will be managed automatically by the multi-step integrator. Any user configuration for these elements will be cleared before use.

Parameters:

starterIntegrator - starter integrator

start

protected void start(ExpandableODE equations,
 ODEState initialState,
 double finalTime)
              throws MathIllegalArgumentException,
MathIllegalStateException

Start the integration.

This method computes one step using the underlying starter integrator, and initializes the Nordsieck vector at step start. The starter integrator purpose is only to establish initial conditions, it does not really change time by itself. The top level multistep integrator remains in charge of handling time propagation and events handling as it will starts its own computation right from the beginning. In a sense, the starter integrator can be seen as a dummy one and so it will never trigger any user event nor call any user step handler.

Parameters:

equations - complete set of differential equations to integrate

initialState - initial state (time, primary and secondary state vectors)

finalTime - target time for the integration (can be set to a value smaller than initialState.getTime() for backward integration)

Throws:

MathIllegalArgumentException - if arrays dimension do not match equations settings

MathIllegalArgumentException - if integration step is too small

MathIllegalStateException - if the number of functions evaluations is exceeded

MathIllegalArgumentException - if the location of an event cannot be bracketed

initializeHighOrderDerivatives

protected abstract Array2DRowRealMatrix initializeHighOrderDerivatives(double h,
 double[] t,
 double[][] y,
 double[][] yDot)

Initialize the high order scaled derivatives at step start.

Parameters:

h - step size to use for scaling

t - first steps times

y - first steps states

yDot - first steps derivatives

Returns:

Nordieck vector at first step (h²/2 y''_n, h³/6 y'''_n ... h^k/k! y^(k)_n)

getMinReduction

public double getMinReduction()

Get the minimal reduction factor for stepsize control.

Returns:

minimal reduction factor

setMinReduction

public void setMinReduction(double minReduction)

Set the minimal reduction factor for stepsize control.

Parameters:

minReduction - minimal reduction factor

getMaxGrowth

public double getMaxGrowth()

Get the maximal growth factor for stepsize control.

Returns:

maximal growth factor

setMaxGrowth

public void setMaxGrowth(double maxGrowth)

Set the maximal growth factor for stepsize control.

Parameters:

maxGrowth - maximal growth factor

getSafety

public double getSafety()

Get the safety factor for stepsize control.

Returns:

safety factor

setSafety

public void setSafety(double safety)

Set the safety factor for stepsize control.

Parameters:

safety - safety factor

getNSteps

public int getNSteps()

Get the number of steps of the multistep method (excluding the one being computed).

Returns:

number of steps of the multistep method (excluding the one being computed)

rescale

protected void rescale(double newStepSize)

Rescale the instance.

Since the scaled and Nordsieck arrays are shared with the caller, this method has the side effect of rescaling this arrays in the caller too.

Parameters:

newStepSize - new step size to use in the scaled and Nordsieck arrays

computeStepGrowShrinkFactor

protected double computeStepGrowShrinkFactor(double error)

Compute step grow/shrink factor according to normalized error.

Parameters:

error - normalized error of the current step

Returns:

grow/shrink factor for next step