geos::algorithm Namespace Reference

Contains classes and interfaces implementing fundamental computational geometry algorithms. More...

Namespaces
namespace	distance
	Classes to compute distance metrics between geometries.
namespace	locate
	Classes which determine the Location of points in geometries.

Classes
class	Angle
	Utility functions for working with angles. More...
class	BoundaryNodeRule
	An interface for rules which determine whether node points which are in boundaries of lineal geometry components are in the boundary of the parent geometry collection. More...
class	CentralEndpointIntersector
	Computes an approximate intersection of two line segments by taking the most central of the endpoints of the segments. More...
class	Centroid
	Computes the centroid of a Geometry of any dimension. More...
class	CGAlgorithmsDD
	Implements basic computational geometry algorithms using extended precision float-point arithmetic. More...
class	ConvexHull
	Computes the convex hull of a Geometry. More...
class	Distance
	Functions to compute distance between basic geometric structures. More...
class	HCoordinate
	Represents a homogeneous coordinate in a 2-D coordinate space. More...
class	InteriorPointArea
	Computes a point in the interior of an areal geometry. The point will lie in the geometry interior in all except certain pathological cases. More...
class	InteriorPointLine
	Computes a point in the interior of an linear geometry. More...
class	InteriorPointPoint
	Computes a point in the interior of an point geometry. More...
class	Intersection
	Functions to compute intersection points between lines and line segments. More...
class	Length
	Functions for computing length. More...
class	LineIntersector
	A LineIntersector is an algorithm that can both test whether two line segments intersect and compute the intersection point if they do. More...
class	MinimumAreaRectangle
class	MinimumDiameter
	Computes the minimum diameter of a geom::Geometry. More...
class	NotRepresentableException
	Indicates that a HCoordinate has been computed which is not representable on the Cartesian plane. More...
class	Orientation
	Functions to compute the orientation of basic geometric structures including point triplets (triangles) and rings. More...
class	PointLocation
	Functions for locating points within basic geometric structures such as lines and rings. More...
class	PointLocator
	Computes the topological relationship (Location) of a single point to a Geometry. More...
class	PolygonNodeTopology
class	RayCrossingCounter
	Counts the number of segments crossed by a horizontal ray extending to the right from a given point, in an incremental fashion. More...
class	RobustDeterminant
	Implements an algorithm to compute the sign of a 2x2 determinant for double precision values robustly. More...

Functions
std::ostream &	operator<< (std::ostream &o, const HCoordinate &c)

Detailed Description

Contains classes and interfaces implementing fundamental computational geometry algorithms.

Robustness

Geometrical algorithms involve a combination of combinatorial and numerical computation. As with all numerical computation using finite-precision numbers, the algorithms chosen are susceptible to problems of robustness. A robustness problem occurs when a numerical calculation produces an incorrect answer for some inputs due to round-off errors. Robustness problems are especially serious in geometric computation, since they can result in errors during topology building.

There are many approaches to dealing with the problem of robustness in geometrical computation. Not surprisingly, most robust algorithms are substantially more complex and less performant than the non-robust versions. Fortunately, JTS is sensitive to robustness problems in only a few key functions (such as line intersection and the point-in-polygon test). There are efficient robust algorithms available for these functions, and these algorithms are implemented in JTS.

Computational Performance

Runtime performance is an important consideration for a production-quality implementation of geometric algorithms. The most computationally intensive algorithm used in JTS is intersection detection. JTS methods need to determine both all intersection between the line segments in a single Geometry (self-intersection) and all intersections between the line segments of two different Geometries.

The obvious naive algorithm for intersection detection (comparing every segment with every other) has unacceptably slow performance. There is a large literature of faster algorithms for intersection detection. Unfortunately, many of them involve substantial code complexity. JTS tries to balance code simplicity with performance gains. It uses some simple techniques to produce substantial performance gains for common types of input data.

Package Specification

• Java Topology Suite Technical Specifications
• OpenGIS Simple Features Specification for SQL