Kinetic Framework

Daniel Russel

This chapter describes a framework for implementing kinetic data
structures and sweepline algorithms. If you just would like to use
existing kinetic data structures, please read
Chapter 70 instead. Readers wishing to brush up on
their familiarity with kinetic data structures or better understand
the terminology we use should read Section 70.2 of that
chapter. A brief overview of the framework can be found in
Section 70.3 (also of that chapter) and it too is
recommended reading. Here we dive right in to discussing to discussing
the architecture of the framework in
Section 71.1 and finally we give several
examples of using the framework to implement a kinetic data structure
in Section 71.3. The framework makes heavy use of
our *Polynomial_kernel* package to provide models of the
*Kinetic::FunctionKernel* concept.

The framework was first presented at ALENEX [GKR04].

This package provides a framework to allow exact implementation of
kinetic data structures and sweepline algorithms. Below we discuss in
detail each one of the first four major concepts which help in
implementing kinetic data structures: the *Kinetic::Simulator*,
the *Kinetic::Kernel*, the *Kinetic::ActiveObjectsTable* and the
*Kinetic::InstantaneousKernel*. The *Kinetic::FunctionKernel*
concept is discussed separately in Section
71.2.

**Figure 71.1: ** The figure, identical
to the one in the overview of the previous chapter, shows the
interaction between the *Kinetic::Sort<Traits, Visitor>* kinetic
data structure and the various pieces of our framework. Other, more
complicated, kinetic data structures will also use the
*Kinetic::InstantaneousKernel* in order to insert/remove
geometric primitives and audit themselves.
*Kinetic::Sort<Traits, Visitor>* uses the sorting functionality
in STL instead.

The *Kinetic::Simulator* is the central repository of all active events.
It maintains the event queue and can use its knowledge of the events
in the queue to find times for the kinetic data structures to easily
check their own correctness (this will be discussed in more detail
later in this section). Kinetic data structures call methods of the
*Kinetic::Simulator* to schedule new events, deschedule old ones and
access and change data contained in already scheduled events (the
operations on existing events are performed using a key which was
returned when the event was scheduled). For controlling the
simulation, methods in the *Kinetic::Simulator* allow stepping through
events, advancing time and even running the simulation backwards (that
is we run the simulation with the time running in the opposite
direction).

The kinetic sorting example in Figure 70.4.1 shows the
basic usage of the *Kinetic::Simulator*. First, the *Simulator*
is created by the *Kinetic::SimulationTraits*. The kinetic data structure
gets a handle to the simulator from the traits class and uses the
handle to add its events to the simulation. The *Kinetic::Simulator* is
then told to advance time up until the end of the simulation,
processing all events along the way.

Each event is represented by a *Kinetic::Simulator::Time* and an instance of a
model of the *Kinetic::Simulator::Event* concept. Models of the *Kinetic::Simulator::Event*
concept are responsible for taking the appropriate action in order to
handle the kinetic event they represent. Specifically, the
*Kinetic::Simulator::Event* concept specifies one method,
*Kinetic::Simulator::Event::process()*, that is called when the event occurs.
The body of the *Kinetic::Simulator::Event::process()* method typically
simply calls a method of the kinetic data structure that created the
event; for example in our kinetic sorting example, processing an event
means calling the *Kinetic::Sort<Traits, Visitor>::swap(Iterator)*
method of the kinetic sorting data structure.

In the model of the *Kinetic::Simulator* concept that we provide,
*Kinetic:Default_simulator<FunctionKernel, EventQueue>*, any model
of the *Kinetic::Simulator::Event* concept can be inserted as an
event. This ability implies that events can be mixed at run time,
which is essential when we want to support multiple kinetic data
structures operating on the same set of moving geometric primitives.

The *Kinetic::Simulator::Time* concept is defined by the simulator, typically to be
some representation of a root of a polynomial, taken from the
*Kinetic::FunctionKernel* (details of the algebraic side of the package
will be discussed in Section 71.2). For most
kinetic data structures *Kinetic::Simulator::Time* only needs to support
comparisons (we need to compare events, in order to process them in
the correct order) and a few other non-arithmetic operations.

When the failure times of certificates are sorted exactly (as opposed
to when we numerically approximate the roots of the certificate
polynomials) the correctness of kinetic data structures can be easily
verified. Let I be an open interval between the last event
processed and the next event to be processed. As was mentioned in the
introduction kinetic data structures do not change combinatorially in
I. In addition, although the static data structures can be
degenerate at the roots defining the two ends of the interval, they
are not, in general, degenerate in the interior. An independent check
of the integrity of kinetic data structures can be provided by, for
example, using an *Kinetic::InstantaneousKernel* (cf. Subsection
71.1.4) to rebuild the static version of the
structure from scratch at some time interior to I and compare it to
the kinetic version. This auditing can typically catch algorithmic or
programming errors much closer to the time they arise in the
simulation than, for example, using visual inspection. Such easy
auditing is one of the powerful advantages of having an exact
computational framework since, as with static data structures, when
using inexact computations differentiating between errors of
implementation and numeric errors is quite tricky.

Kinetic data structures receive alerts of appropriate times to audit
themselves using a notification framework. The same framework is also
used by the *Kinetic::ActiveObjectsTable* to alert kinetic data
structures when the set of primitives changes (see
Subsection 71.1.3). To use the notification
framework, the kinetic data structure creates a proxy object which
implements a standard *Listener* interface. It then registers this
proxy with the *Kinetic::Simulator*. When the
*Kinetic::Simulator* finds an appropriate time for the kinetic
data structures to audit themselves it calls the function
*Listener::new_notification(Type)* on each of the registered proxy
objects. A helper for creating such proxy objects, called
*Kinetic::Simulator_kds_listener<Listener, KDS>*, is provided by the
framework. It translates the notification into a function call
(*audit()*) on the kinetic data structure. Pointers in the
notification framework are reference counted appropriately to avoid
issues caused by the creation and destruction order of kinetic data
structures and the simulator. See Section 71.1.5.2 for a more
complete discussion of this part of the framework.

Internally the *Kinetic::Simulator* maintains a priority queue
containing the scheduled events. The type of the priority queue is a
template argument to our *Kinetic::Simulator* model and, as such, it can
be replaced by the user. In our package, we provide two different
types of priority queues, a heap and a two-list priority queue. A
two-list queue is a queue in which there is a sorted front list,
containing all events before some time and an unsorted back list. The
queue tries to maintain a small number of elements in the front list,
leaving most of them in the unsorted main pool. The two-list queue,
although an unconventional choice, is our default queue when using
exact computation because it minimizes comparisons involving events
that are far in the future. These events are likely to be deleted
before they are processed, so extra work done structuring them is
wasted. Our experiments have shown that, for example, the two-list
queue causes a 20% reduction in running time relative to a binary
heap for Delaunay triangulations with degree 3 polynomial motions and
20 points.

The *Kinetic::Kernel* is structured very much like static CGAL
kernels. It defines a number of primitives, which in the model
provided are *Kinetic::Kernel::Point_1*,
*Kinetic::Kernel::Point_2*, *Kinetic::Kernel::Point_3* and
*Kinetic::Kernel::Weighted_point_3*. The primitives are defined by
a set of Cartesian coordinates each of which is a function of time, a
*Kernel::MotionFunction*. In addition it defines constructions
and certificate generators which act on the primitives. The
certificate generators are the direct analog of the non-kinetic
predicates. Each certificate generator take a number of primitives as
arguments, but instead of producing an element from a discrete set
they produce a set of discrete failure times for the certificate.
These failure times are wrapped in a model of *Kinetic::Certificate*.

A *Kinetic::Certificate* is a simple object whose primary function is to
produce a *Kinetic::Simulator::Time* object representing the failure time of the
certificate. Since, the handling of most certificate failures
involves creating a new certificate whose certificate function is the
negation of the old certificate function, a *Kinetic::Certificate*
object caches any work that could be useful to isolate future roots of
the certificate function (such as the Sturm sequence of the
certificate function). To illustrate this further, if you have two
one-dimensional points with coordinate functions p_{0}(t) and
p_{1}(t), the certificate that the first moving point is after the
second corresponds to the inequality p_{0}(t) - p_{1}(t) > 0. When the
certificate fails and the two points cross, the new certificate is
p_{1}(t)- p_{0}(t) > 0, which is the negated version of the certificate
just processed and which has the same roots.

The model of *Kinetic::Kernel* provided includes the certificate
generators necessary for Delaunay triangulations (in one, two and
three dimensions) and regular triangulations (in 3D). New
certificates can be fairly easily added. An example is included in the
distributed code.

The *Kinetic::ActiveObjectsTable* stores a set of kinetic primitives.
Its purpose is to notify kinetic data structures when new primitives
are added, when primitives are removed or when a trajectories change.
Each primitive is uniquely identified by a Key, assigned by
the table when the primitive is added, that can be used to change or
remove it. We provide one model of the
*Kinetic::ActiveObjectsTable* concept, called
*Kinetic::Active_objects_vector<MovingObject>* which stores all the moving
primitives in an *std::vector<D>*.

Notifications of changes to the set of active objects are handled
using a setup similar to the *Kinetic::Simulator* audit time
notification. We provide a helper class,
*Kinetic::Active_objects_listener_helper<ActiveObjectsTable, KDS>*, which translates the notifications into *insert(Key)*,
*erase(Key)* or *set(Key)* function calls on the kinetic data
structure.

The *Kinetic::InstantaneousKernel* allows existing Cgal data structures
to be used on moving data as it appears at some instant of time.
Models of this concept are, by definition, models of a CGAL
Kernel or a traits class, and, therefore, can then be used as
the traits class of CGAL's algorithms and data structures.

Consider for example the kinetic Delaunay data structure in either two
or three dimensions. Internally, it uses a
*Delaunay_triangulation_2<Traits, Tds>* or
*Delaunay_triangulation_3<Traits, Tds>* to represent the
triangulation, instantiated with a model of the
*Kinetic::InstantaneousKernel* concept as its traits class. At
initialization, as well as at times during the simulation when we want
to insert a point to the kinetic Delaunay triangulation, a static
version of the Delaunay triangulation is conceptually instantiated.
More precisely, the time for the copy of the model of the
*Kinetic::InstantaneousKernel* stored in the Cgal triangulation is set
to be the current time (or rather, as discussed in the introduction, a
more convenient time determined by the *Kinetic::Simulator*
combinatorially equivalent to the current time). The kinetic data
structure then calls the
*Delaunay_triangulation_3<Traits, Tds>::insert(Point)* insert
method to insert the point. The static insert method called uses
various predicate functors on the moving points which evaluate to the
values that the predicates have at that instant in time. Removal is
handled in an analogous manner. Auditing of the geometric structure is
easily handled in a similar manner (in the case of Delaunay
triangulations by simply calling the *verify()* method after
setting the time).

We describe some coding conventions used, graphical display, notification and reference management support in the framework in the following sections.

A number of objects need to maintain pointers to other independent
objects. For example, each kinetic data structure must have access to
the *Kinetic::Simulator* so that it can schedule and deschedule
events. These pointers are all reference counted in order to guarantee
that they are always valid. We provide a standard reference counting
pointer and object base to facilitate this, namely
*Ref_counted<Object>*.

Each shared object in the framework defines a type *Handle* which is the
type for a reference counter pointer pointing to it. These should be
used for storing pointers to the objects in order to avoid dangling
pointers. In addition, many of the objects expect such pointers as
arguments.

Runtime events must be passed from *notifiers*, namely the
*Kinetic::ActiveObjectsTable* and the *Kinetic::Simulator* to
*listeners*, typically the kinetic data structures. For
example, kinetic data structures are notified when new primitives are
added to the *Kinetic::ActiveObjectsTable*. On reciving the
notification, it will add the new primitive to the combinatorial
structure it is maintaining. The events are passed using a simple,
standardized notification interface. To receive notifications, the
listener first defines a small proxy class which inherits from a
*Listener* base type provided by the notifier. On creation, the
*Listener* base class registers itself with the notifier on
construction (and unregisters itself on destruction).

When the some state of the notifier changes, it calls the
*new_notification* method on the listener proxy object provided
and passes it a label corresponding to the name of the field that
changed. The proxy object can then call an appropriate method on the
kinetic data structure or whetever the listening class is.

In order to unregister on destruction, the *Listener* must store a
(reference counted) pointer to the object providing notifications.
This pointer can be accessed through the *notifier()* field. The
*Listener* object stores a reference counted pointer to the
notifying object, while the notifying object stores a plain pointer to
the *Listener*. It can do this since the *Listener* is
guaranteed to unregister itself when it is destroyed. This avoids
circular reference counted pointers as well as dangling pointers.

The interface between the algebraic kernel and the kinetic data
structures package was kept quite minimal in order to ease the
implementation of various underlying computation models. The interface
is detailed in the reference page (*Kinetic::FunctionKernel*).

We provide models of the algebraic kernel that handle polynomial
*Kinetic::Function* objects. The provided models perform

- exact computations using Sturm sequences to isolate roots
- exact computations using Descartes rule of sign in order to isolate roots (Sturm sequences are also used in order to properly handle even multiplicity roots)
- filtered exact computations using Descartes rule of sign
- numeric (inexact) root approximations
- numeric root approximations which take advantage of certain assumptions that can be made about the types of polynomials solved in the process of evaluating kinetic data structures
- a wrapper for CORE::Expr which implements the required concepts.

There are several modifications we can make to how the roots are handled to optimize for the case of kinetic data structures. The first are motivated by the question of how to handle degeneracies (certificate functions which have roots at the same time). Naively, there is no way to differentiate between a certificate which fails immediately when it is created and one whose function is momentarily 0, but will be valid immediately in the future. In order to handle such degeneracies we ensure that all the certificate function generators produce certificate functions which are positive when the corresponding certificates are valid. Then, if we have a degeneracy we can differentiate between a certificate which fails immediately and one which is simply degenerate by looking at the sign of the certificate function immediately following the root (equivalently, by looking at the derivative). In addition, this allows us, under the assumption that computations are performed exactly, to check that all certificates are not invalid upon creation.

The assumption that certificates are positive when valid is particular useful when using numeric solvers. Without it there is no reliable way to tell whether a root near the current time is the certificate having become valid just before the current time, or failing shortly in the future. Testing the sign of the function immediately after the root reliably disambiguates the two cases.

In addition, we have to specially handle even roots of functions. For
the most part these can just be discarded as dropping an even root is
equivalent to perturbing the simulation to remove the degeneracy.
However, when we are using the *Kinetic::Simulator* to audit the
kinetic data structures, they most be broken up in to two, equal,
roots to avoid auditing at the degeneracy.

We provide a number of examples of different levels of usage of the kinetic data structures framework, both for kinetic data structures as well as sweepline algorithms.

To see how to use existing kinetic data structures, look at the examples in the previous chapter such as Section 70.4.1.

The here we cover implementing kinetic data structures. The examples explained are

- A trivial kinetic data structure which has all the parts of a full kinetic data structure but doesn't do much in Section 71.3.2.
- Adding a new type of certificate to a kernel in Section 71.3.3.

In order to see more detail about how to implement a kinetic data
structure, the best place to start is the source code for the kinetic
sorting data structure, *Kinetic::Sort<Traits, Visitor>*. Once you
are familiar with that, *Kinetic::Delaunay_2<Traits, Triangulation, Visitor>* is the next step in complexity.

We will first explain in detail how a typical kinetic data structure uses the various pieces of the framework, then move on to showing the actual code for a simpler data structure.

Here we will explain how the kinetic sorting data structure uses the various pieces of the package. A schematic of its relationship to the various components is shown in the UML diagram in Figure 71.1. In this subsection we abuse, for reasons of simplicity of presentation, the concept/model semantics: when we refer to concepts we actually refer to an instance of a model of them.

As with most kinetic data structures, *Kinetic::Sort<Traits, Visitor>* maintains some sort of combinatorial structure (in this
case a sorted doubly linked list), each element of which has a
corresponding certificate in the event queue maintained by the
simulator. In the case of sorting, there is one certificate maintained
for each ``edge'' between two consecutive elements in the list.

On creation, the data structure is passed a copy of the
*Kinetic::SimulationTraits* for this simulation, which it saves for
future use. It gets a handle to to the
*Kinetic::ActiveObjectsTable* by calling the
*Kinetic::SimulationTraits::active_points_1_table_handle()*
method and registers a proxy with the table in order to receive
notifications of changes to the point set. The
*Kinetic::SimulationTraits* method returns a handle to, rather
than a copy of, the *Kinetic::ActiveObjectsTable*, since the table must
be shared between all the kinetic data structures using these points.
The handles are reference counted pointers, thus saving the user from
worrying about cleaning things up properly.

When new points are added to the model of the
*Kinetic::ActiveObjectsTable*, the table calls the
*new_notification()* method on the proxy of the kinetic data
structure, which in turn calls the *insert(Point_key)* method of
the kinetic data structure. The *Point_key* here is the key which
uniquely identifies the newly inserted point in the table. The data
structure then requests an instance of a model of the
*Kinetic::InstantaneousKernel* from the
*Kinetic::SimulationTraits*. It sets the time on the
instantaneous kernel to the time value gotten from the
*Kinetic::Simulator::current_time_nt()* method. This method
returns a field number type that is between the previous and next
event, as discussed in the introduction. An instance of the
*Kinetic::InstantaneousKernel::Compare_x_1* predicate (wrapped in order to make it return *less*) and the STL
function *std::upper_bound()* are then used to insert the new
point in the sorted list. For each inserted object, the kinetic data
structure removes the no longer relevant certificate from the event
queue by calling the *Kinetic::Simulator::delete_event(Key)*
function and creates two new certificates using a
*Kinetic::Kernel::Compare_x_1* certificate functor. The new
certificates are inserted in the event queue by calling the
*Kinetic::Simulator::new_event(Time, Event)* method where
*Kinetic::Simulator::Event* is a proxy object which instructs the sort
kinetic data structure to swap two points when its *process()*
method is called.

Now that the kinetic data structure has been initialized, the
simulator is instructed to process all events. Each time an event
occurs, the simulator calls the *process()* method on the
corresponding proxy object. The proxy, in turn, tells the sort kinetic
data structure to swap the two points whose order has changed.

The *Kinetic::Simulator* can periodically instruct the kinetic data
structures to audit themselves. As is explained in
Section 71.1.1, a proxy object maps the notification on to an
*audit()* function call in the kinetic data structure. To audit
itself the kinetic data structure builds a list of all the current
points and uses *std::sort* to sort this list using a
comparison function gotten from the *Kinetic::InstantaneousKernel*.
This sorted list is compared to the maintained one to verify
correctness. This auditing could also have been done by evaluating the
*Kinetic::InstantaneousKernel* predicate for each sorted pair. Since
auditing a kinetic data structure typically requires at least linear
time in the size of the combinatorial structure, the auditing
procedure in between events is deactivated by default. The user can
however easily switch it on by defining the
*CGAL_CHECK_EXACTNESS* and *CGAL_CHECK_EXPENSIVE* CGAL
macros.

This general structure of the interaction between the kinetic data structure and the framework is shared by all of the provided kinetic data structures and has proved itself to go quite far.

To show how to implement such things, instead of presenting a full
kinetic data structure, we present a trivial one which maintains one
event in the queue which maintains one event in the queue, scheduled
to occur one time unit after the last change was made to the set of
active primitives. Two classes are defined, the *Trivial_event*,
and the *Trivial_kds*. The event classes must be declared outside
of the kinetic data structure so that the *operator<<* can be
defined for them.

The kinetic data structure maintains the invariant that it was one event in the queue at all times. This event ccurs one time unit after the last event or change in the set of objects occurs. As a result, the kinetic data structure has the main parts of a real one-it responds to changes in trajectories of the objects and certificate failures (when the event expires).

The public methods can be grouped into three sets which are shared with almost all other kinetic data structures:

*has_certificates*and*set_has_certificates*which checks/sets whether the kinetic data structure is currently maintaining certificates.*insert*,*set*,*erase*which are called by the*Kinetic::Active_objects_listener_helper*in response to the addition, modification, or deletion of an object to, in or from the simulation.*audit*which is called periodically by the*Kinetic::Simulator_kds_listener*when kinetic data structures can easily audit themselves.

In addition, it has one method which is called when a certificate fails. The name/existence of such methods depend on the nature of the kinetic data structure in question.

Like many kinetic data structures, it takes a *Kinetic::SimulationTraits*
as a template argument. This traits class defines the types needed for
the simulation and is responsible for instantiating them.

#include <CGAL/Kinetic/Ref_counted.h> #include <CGAL/Kinetic/Exact_simulation_traits.h> #include <CGAL/Kinetic/Active_objects_listener_helper.h> #include <CGAL/Kinetic/Simulator_kds_listener.h> ... // This must be external since operator<< has to be defined template <class KDS> struct Trivial_event { Trivial_event(){} Trivial_event(KDS* kds): kds_(kds) { } void process() const { kds_->process(); } KDS* kds_; }; template <class KDS> std::ostream &operator<<(std::ostream &out, const Trivial_event<KDS> &) { out << "\"An event\""; return out; } template <class Traits> struct Trivial_kds: CGAL::Kinetic::Ref_counted<Trivial_kds<Traits> > { typedef Trivial_kds<Traits> This; typedef typename Traits::Active_points_1_table::Data Point; typedef typename Traits::Simulator::Time Time; typedef typename Traits::Active_objects_table::Key Point_key; typedef typename Traits::Simulator::Event_key Event_key; typedef CGAL::Kinetic::Active_objects_listener_helper< typename Traits::Active_points_1_table::Listener, This> Active_objects_helper; typedef CGAL::Kinetic::Simulator_kds_listener< typename Traits::Simulator::Listener, This> Simulator_helper; typedef Trivial_event<This> Event; Trivial_kds(Traits tr): has_certificates_(true), tr_(tr), nth_(tr.active_points_1_table_handle(), this), sh_(tr.simulator_handle(), this){} // this method is called with the value true when the event is processed void process(bool tf) { event_= Event_key(); set_has_certificates(false); set_has_certificates(true); } void audit() const { ... } void set_has_certificates(bool tf) { typename Traits::Simulator::Handle sp= tr_.simulator_handle(); if (has_certificates_ != tf) { has_certificates_=tf; if (has_certificates_) { bool ev= event_; CGAL_assertion(!ev); Time t= CGAL::to_interval(sp->current_time()).second+1; event_= sp->new_event(t, Event(this)); } else if (event_) { sp->delete_event(event_); event_=Event_key(); } } } bool has_certificates() const { return has_certificates_; } void insert(Point_key k) { if (has_certificates_) { set_has_certificates(false); set_has_certificates(true); } } void set(Point_key k) { if (has_certificates_) { set_has_certificates(false); set_has_certificates(true); } } void erase(Point_key k) { if (has_certificates_) { set_has_certificates(false); set_has_certificates(true); } } ~Trivial_kds(){ set_has_certificates(false); } protected: bool has_certificates_; Event_key event_; Traits tr_; Active_objects_helper nth_; Simulator_helper sh_; };

The following example shows how to add a new type of certificate to a simulation.

First we code the actual certificate function generator. It must take some sort (or sorts) of kinetic primitives, compute some function from their coordinates.

template <class KineticKernel> struct Positive_x_f_2 { typedef typename KineticKernel::Certificate_function result_type; typedef typename KineticKernel::Point_2 argument_type; result_type operator()(const argument_type &p){ return result_type(p.x()- result_type(0)); } };

Then we define a kinetic kernel which includes this predicate. To do
this we wrap the function generator generator in a
*Kinetic::Certificate_generator<Kernel, Generator>*.
This wrapper uses the generator to create the certificate function and
then the *Kinetic::FunctionKernel* to solve the certificate
function. The result is wrapped in a *Kinetic::Certificate*
object.

template <class FunctionKernel> class My_kinetic_kernel: public CGAL::Kinetic::Cartesian<FunctionKernel> { typedef CGAL::Kinetic::Cartesian<FunctionKernel> P; typedef My_kinetic_kernel<FunctionKernel> This; public: typedef CGAL::Kinetic::internal::Certificate_generator<This, Positive_x_f_2<This> > Positive_x_2; Positive_x_2 positive_x_2_object() const { return Positive_x_2(P::function_kernel_object()); } };

Now we have the unfortunately rather messy part of assembling a new
*Kinetic::SimulationTraits* model. This is done in two steps for convenience.

struct My_simulation_traits { typedef My_simulation_traits This; typedef CGAL::Exact_predicates_exact_constructions_kernel Static_kernel; //typedef CGAL::Regular_triangulation_euclidean_traits_3<Static_kernel_base> Static_kernel; typedef CGAL::POLYNOMIAL::Polynomial<Static_kernel::FT> Function; typedef CGAL::POLYNOMIAL::Sturm_root_stack_traits<Function> Root_stack_traits; typedef CGAL::POLYNOMIAL::Sturm_root_stack<Root_stack_traits> Root_stack; typedef CGAL::POLYNOMIAL::Kernel<Function, Root_stack> Function_kernel; typedef CGAL::Kinetic::Handle_degeneracy_function_kernel<Function_kernel, false> Simulator_function_kernel_base; struct Simulator_function_kernel: public Simulator_function_kernel_base{}; typedef My_kinetic_kernel<Simulator_function_kernel> Kinetic_kernel; typedef CGAL::Kinetic::Two_list_pointer_event_queue<Function_kernel> Event_queue; typedef CGAL::Kinetic::Default_simulator<Simulator_function_kernel, Event_queue > Simulator; typedef CGAL::Kinetic::Active_objects_vector<Kinetic_kernel::Point_1> Active_points_1_table; typedef CGAL::Kinetic::Active_objects_vector<Kinetic_kernel::Point_2> Active_points_2_table; typedef CGAL::Kinetic::Active_objects_vector<Kinetic_kernel::Point_3> Active_points_3_table; // typedef Active_objects_vector<Kinetic_kernel::Weighted_point_3> Active_weighted_points_3_table; typedef CGAL::Kinetic::Default_instantaneous_kernel<This> Instantaneous_kernel; Active_points_1_table* active_points_1_table_handle() const { return ap1_.get();} Active_points_2_table* active_points_2_table_handle() const {return ap2_.get();} Active_points_3_table* active_points_3_table_handle() const {return ap3_.get();} //Active_weighted_points_3_table* active_weighted_points_3_table_handle() const {return awp3_.get();} Simulator* simulator_handle() const { return sim_.get();} const Static_kernel& static_kernel_object() const {return k_;} const Kinetic_kernel& kinetic_kernel_object() const {return kk_;} Instantaneous_kernel instantaneous_kernel_object() const { return Instantaneous_kernel(*this); } My_simulation_traits(const Simulator::Time &lb, const Simulator::Time &ub): sim_(new Simulator(lb, ub)), ap1_(new Active_points_1_table()), ap2_(new Active_points_2_table()), ap3_(new Active_points_3_table()) {} bool is_exact() const { return true; } protected: Simulator::Handle sim_; Active_points_1_table::Handle ap1_; Active_points_2_table::Handle ap2_; Active_points_3_table::Handle ap3_; //Active_weighted_points_3_table::Handle awp3_; Static_kernel k_; Kinetic_kernel kk_; Function_kernel fk_; };

Now the simulation traits can be used by a kinetic data structure.
Note that we define active point table for all dimensions. This is
needed by the *Kinetic::InstantaneousKernel*, even if they are not
used.

Next: Reference Manual

CGAL Open Source Project.
Release 3.9.
26 September 2011.