\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)

CGAL 4.8 - 2D and 3D Linear Geometry Kernel

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CGAL::Filtered_predicate< EP, FP, C2E, C2F > Class Template Reference
Kernel Classes

`#include <CGAL/Filtered_predicate.h>`

## Definition

`Filtered_predicate` is an adaptor for predicate function objects that allows one to produce efficient and exact predicates.

It is used to build `CGAL::Filtered_kernel<CK>` and can be used for other predicates too.

`EP` is the exact but supposedly slow predicate that is able to evaluate the predicate correctly. It will be called only when the filtering predicate, `FP`, cannot compute the correct result. This failure of `FP` must be done by throwing an exception.

To convert the geometric objects that are the arguments of the predicate, we use the function objects `C2E` and `C2F`, which must be of the form `Cartesian_converter` or `Homogeneous_converter`.

Example

The following example defines an efficient and exact version of the orientation predicate over three points using the Cartesian representation with double coordinates and without reference counting (`Simple_cartesian::Point_2`). Of course, the orientation predicate can already be found in the kernel, but you can follow this example to filter your own predicates. It uses the fast but inexact predicate based on interval arithmetic for filtering and the slow but exact predicate based on multi-precision floats when the filtering predicate fails.

File Filtered_kernel/Filtered_predicate.cpp

#include <CGAL/Simple_cartesian.h>
#include <CGAL/Filtered_predicate.h>
#include <CGAL/MP_Float.h>
#include <CGAL/Cartesian_converter.h>
typedef CGAL::Simple_cartesian<double> K;
typedef CGAL::Simple_cartesian<CGAL::Interval_nt_advanced> FK;
typedef CGAL::Simple_cartesian<CGAL::MP_Float> EK;
typedef CGAL::Cartesian_converter<K, EK> C2E;
typedef CGAL::Cartesian_converter<K, FK> C2F;
// Define my predicate, parameterized by a kernel.
template < typename K >
struct My_orientation_2
{
typedef typename K::RT RT;
typedef typename K::Point_2 Point_2;
typedef typename K::Orientation result_type;
result_type
operator()(const Point_2 &p, const Point_2 &q, const Point_2 &r) const
{
RT prx = p.x() - r.x();
RT pry = p.y() - r.y();
RT qrx = q.x() - r.x();
RT qry = q.y() - r.y();
return CGAL::sign( prx*qry - qrx*pry );
}
};
typedef CGAL::Filtered_predicate<My_orientation_2<EK>,
My_orientation_2<FK>, C2E, C2F> Orientation_2;
int main()
{
K::Point_2 p(1,2), q(2,3), r(3,4);
Orientation_2 orientation;
orientation(p, q, r);
return 0;
}

Examples:
  Filtered_kernel/Filtered_predicate.cpp.

## Types
typedef FP::result_type | result_type
| The return type of the function operators. More...

## Creation
| Filtered_predicate ()
| Default constructor.

## Operations
Similar function operators are defined for up to 7 arguments.
template<class A1 >
result_type | operator() (A1 a1)
| The unary function operator for unary predicates.
template<class A1 , class A2 >
result_type | operator() (A1 a1, A2 a2)
| The binary function operator for binary predicates.

## Member Typedef Documentation

template<typename EP , typename FP , typename C2E , typename C2F >

typedef FP::result_type CGAL::Filtered_predicate< EP, FP, C2E, C2F >::result_type

The return type of the function operators.

It must also be the same type as `EP::result_type`.