Package org.hipparchus.ode.events

Class EventSlopeFilter<T extends ODEEventDetector>

java.lang.Object

org.hipparchus.ode.events.AbstractODEDetector<EventSlopeFilter<T>>

org.hipparchus.ode.events.EventSlopeFilter<T>

Type Parameters:

T - type of the event detector

All Implemented Interfaces:

ODEEventDetector

public class EventSlopeFilter<T extends ODEEventDetector>
extends AbstractODEDetector<EventSlopeFilter<T>>

Wrapper used to detect only increasing or decreasing events.

General events are defined implicitly by a g function crossing zero. This function needs to be continuous in the event neighborhood, and its sign must remain consistent between events. This implies that during an ODE integration, events triggered are alternately events for which the function increases from negative to positive values, and events for which the function decreases from positive to negative values.

Sometimes, users are only interested in one type of event (say increasing events for example) and not in the other type. In these cases, looking precisely for all events location and triggering events that will later be ignored is a waste of computing time.

Users can wrap a regular event detector in an instance of this class and provide this wrapping instance to the ODE solver in order to avoid wasting time looking for uninteresting events. The wrapper will intercept the calls to the g function and to the eventOccurred method in order to ignore uninteresting events. The wrapped regular event handler will the see only the interesting events, i.e. either only increasing events or decreasing events. the number of calls to the g function will also be reduced.

Since:

3.0

Field Summary

Fields inherited from class org.hipparchus.ode.events.AbstractODEDetector

DEFAULT_MAX_ITER, DEFAULT_MAXCHECK, DEFAULT_THRESHOLD

Constructor Summary

Constructors

Constructor	Description
EventSlopeFilter(T rawDetector, FilterType filter)	Wrap an event detector.

Method Summary

Modifier and Type	Method	Description
protected EventSlopeFilter<T>	create(AdaptableInterval newMaxCheck, int newMaxIter, BracketedUnivariateSolver<UnivariateFunction> newSolver, ODEEventHandler newHandler)	Build a new instance.
double	g(ODEStateAndDerivative state)	Compute the value of the switching function.
T	getDetector()	Get the wrapped raw detector.
void	init(ODEStateAndDerivative initialState, double finalTime)	Initialize event handler at the start of an ODE integration.

Methods inherited from class org.hipparchus.ode.events.AbstractODEDetector

getHandler, getMaxCheckInterval, getMaxIterationCount, getSolver, isForward, withHandler, withMaxCheck, withMaxCheck, withMaxIter, withSolver, withThreshold

Methods inherited from class java.lang.Object

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

Constructor Details

EventSlopeFilter

public EventSlopeFilter(T rawDetector,
 FilterType filter)

Wrap an event detector.

Parameters:

rawDetector - event detector to wrap

filter - filter to use

Since:

3.0

Method Details

create

protected EventSlopeFilter<T> create(AdaptableInterval newMaxCheck,
 int newMaxIter,
 BracketedUnivariateSolver<UnivariateFunction> newSolver,
 ODEEventHandler newHandler)

Build a new instance.

Specified by:

create in class AbstractODEDetector<EventSlopeFilter<T extends ODEEventDetector>>

Parameters:

newMaxCheck - maximum checking interval

newMaxIter - maximum number of iterations in the event time search

newSolver - root-finding algorithm to use to detect state events

newHandler - event handler to call at event occurrences

Returns:

a new instance of the appropriate sub-type

getDetector

public T getDetector()

Get the wrapped raw detector.

Returns:

the wrapped raw detector

init

public void init(ODEStateAndDerivative initialState,
 double finalTime)

Initialize event handler at the start of an ODE integration.

This method is called once at the start of the integration. It may be used by the event handler to initialize some internal data if needed.

The default implementation does nothing

This implementation sets the direction of integration and initializes the event handler. If a subclass overrides this method it should call super.init(s0, t).

Specified by:

init in interface ODEEventDetector

Overrides:

init in class AbstractODEDetector<EventSlopeFilter<T extends ODEEventDetector>>

Parameters:

initialState - initial time, state vector and derivative

finalTime - target time for the integration

g

public double g(ODEStateAndDerivative state)

Compute the value of the switching function.

The discrete events are generated when the sign of this switching function changes. The integrator will take care to change the stepsize in such a way these events occur exactly at step boundaries. The switching function must be continuous in its roots neighborhood (but not necessarily smooth), as the integrator will need to find its roots to locate precisely the events.

Also note that for the integrator to detect an event the sign of the switching function must have opposite signs just before and after the event. If this consistency is not preserved the integrator may not detect any events.

This need for consistency is sometimes tricky to achieve. A typical example is using an event to model a ball bouncing on the floor. The first idea to represent this would be to have g(state) = h(state) where h is the height above the floor at time state.getTime(). When g(state) reaches 0, the ball is on the floor, so it should bounce and the typical way to do this is to reverse its vertical velocity. However, this would mean that before the event g(state) was decreasing from positive values to 0, and after the event g(state) would be increasing from 0 to positive values again. Consistency is broken here! The solution here is to have g(state) = sign * h(state), where sign is a variable with initial value set to +1. Each time eventOccurred is called, sign is reset to -sign. This allows the g(state) function to remain continuous (and even smooth) even across events, despite h(state) is not. Basically, the event is used to fold h(state) at bounce points, and sign is used to unfold it back, so the solvers sees a g(state) function which behaves smoothly even across events.

This method is idempotent, that is calling this multiple times with the same state will result in the same value, with two exceptions. First, the definition of the g function may change when an event occurs on the handler, as in the above example. Second, the definition of the g function may change when the eventOccurred method of any other event handler in the same integrator returns Action.RESET_EVENTS, Action.RESET_DERIVATIVES, or Action.RESET_STATE.

Specified by:

g in interface ODEEventDetector

Specified by:

g in class AbstractODEDetector<EventSlopeFilter<T extends ODEEventDetector>>

Parameters:

state - current value of the independent time variable, state vector and derivative

Returns:

value of the g switching function

See Also:

• org.hipparchus.ode.events