Package org.hipparchus.ode.events

Interface ODEEventDetector

All Known Implementing Classes:
AbstractODEDetector, EventSlopeFilter
public interface ODEEventDetector
This interface represents a detector for discrete events triggered during ODE integration.

Some events can be triggered at discrete times as an ODE problem is solved. This occurs for example when the integration process should be stopped as some state is reached (G-stop facility) when the precise date is unknown a priori, or when the derivatives have discontinuities, or simply when the user wants to monitor some states boundaries crossings.

These events are defined as occurring when a g switching function sign changes.

Since events are only problem-dependent and are triggered by the independent time variable and the state vector, they can occur at virtually any time, unknown in advance. The integrators will take care to avoid sign changes inside the steps, they will reduce the step size when such an event is detected in order to put this event exactly at the end of the current step. This guarantees that step interpolation (which always has a one step scope) is relevant even in presence of discontinuities. This is independent from the stepsize control provided by integrators that monitor the local error (this event handling feature is available for all integrators, including fixed step ones).

Note that prior to Hipparchus 3.0, the methods in this interface were in the ODEEventHandler interface and the defunct EventHandlerConfiguration interface. The interfaces have been reorganized to allow different objects to be used in event detection and event handling, hence allowing users to reuse predefined events detectors with custom handlers.

Since:
3.0
See Also:

  • Method Details

    • getMaxCheckInterval

      AdaptableInterval getMaxCheckInterval()
      Get the maximal time interval between events handler checks.
      Returns:
      maximal time interval between events handler checks

    • getMaxIterationCount

      int getMaxIterationCount()
      Get the upper limit in the iteration count for event localization.
      Returns:
      upper limit in the iteration count for event localization

    • getSolver

      BracketedUnivariateSolver<UnivariateFunction> getSolver()
      Get the root-finding algorithm to use to detect state events.
      Returns:
      root-finding algorithm to use to detect state events

    • getHandler

      ODEEventHandler getHandler()
      Get the underlying event handler.
      Returns:
      underlying event handler

    • init

      default 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

      Parameters:
      initialState - initial time, state vector and derivative
      finalTime - target time for the integration

    • g

      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.

      Parameters:
      state - current value of the independent time variable, state vector and derivative
      Returns:
      value of the g switching function
      See Also: