CGAL Namespace Reference

Classes
class	Distance_adapter
	A class that uses a point property map to adapt a distance class to work on a key as point type. More...
class	Euclidean_distance
	The class Euclidean_distance provides an implementation of the concept OrthogonalDistance, with the Euclidean distance ( \( l_2\) metric). More...
class	Euclidean_distance_sphere_point
	The class Euclidean_distance_sphere_point provides an implementation of the GeneralDistance concept for the Euclidean distance ( \( l_2\) metric) between a \( d\)-dimensional sphere and a point, and the Euclidean distance between a \( d\)-dimensional sphere and a \( d\)-dimensional iso-rectangle defined as a \(k\)- \(d\) tree rectangle. More...
class	Fair
	Implements the fair splitting rule. More...
class	Fuzzy_iso_box
	The class Fuzzy_iso_box implements fuzzy d-dimensional (closed) iso boxes. More...
class	Fuzzy_sphere
	The class Fuzzy_sphere implements fuzzy d-dimensional spheres. More...
class	Incremental_neighbor_search
	The class Incremental_neighbor_search implements incremental nearest and furthest neighbor searching on a tree. More...
class	K_neighbor_search
	The class K_neighbor_search implements approximate k-nearest and k-furthest neighbor searching using standard search on a tree using a general distance class. More...
class	Kd_tree
	The class Kd_tree defines a k-d tree. More...
class	Kd_tree_internal_node
class	Kd_tree_leaf_node
class	Kd_tree_node
	The class Kd_tree_node implements a node class for a k-d tree. More...
class	Kd_tree_rectangle
	The class Kd_tree_rectangle implements d-dimensional iso-rectangles and related operations, e.g., methods to compute bounding boxes of point sets. More...
class	Manhattan_distance_iso_box_point
	The class Manhattan_distance_iso_box_point provides an implementation of the GeneralDistance concept for the Manhattan distance ( \( l_1\) metric) between a d-dimensional iso-box and a d-dimensional point and the Manhattan distance between a d-dimensional iso-box and a d-dimensional iso-box defined as a k-d tree rectangle. More...
class	Median_of_max_spread
	Implements the median of max spread splitting rule. More...
class	Median_of_rectangle
	Implements the median of rectangle splitting rule. More...
class	Midpoint_of_max_spread
	Implements the midpoint of max spread splitting rule. More...
class	Midpoint_of_rectangle
	Implements the midpoint of rectangle splitting rule. More...
class	Orthogonal_incremental_neighbor_search
	The class Orthogonal_incremental_neighbor_search implements incremental nearest and furthest neighbor searching on a tree. More...
class	Orthogonal_k_neighbor_search
	The class Orthogonal_k_neighbor_search implements approximatek-nearest and k-furthest neighbor searching on a tree using an orthogonal distance class. More...
class	Plane_separator
	The class Plane_separator implements a plane separator, i.e., a hyperplane that is used to separate two half spaces. More...
class	Point_container
	A custom container for points used to build a tree. More...
class	Search_traits
	The class Search_traits can be used as a template parameter of the kd tree and the search classes. More...
class	Search_traits_2
	The class Search_traits_2 can be used as a template parameter of the kd tree and the search classes. More...
class	Search_traits_3
	The class Search_traits_3 can be used as a template parameter of the kd tree and the search classes. More...
class	Search_traits_adapter
	The class Search_traits_adapter can be used as a template parameter of the kd tree and the search classes. More...
class	Search_traits_d
	The class Search_traits_d can be used as a template parameter of the kd tree and the search classes. More...
class	Sliding_fair
	Implements the sliding fair splitting rule. More...
class	Sliding_midpoint
	Implements the sliding midpoint splitting rule. More...
class	Weighted_Minkowski_distance
	The class Weighted_Minkowski_distance provides an implementation of the concept OrthogonalDistance, with a weighted Minkowski metric on \( d\)-dimensional points defined by \( l_p(w)(r,q)= ({\Sigma_{i=1}^{i=d} \, w_i(r_i-q_i)^p})^{1/p}\) for \( 0 < p <\infty\) and defined by \( l_{\infty}(w)(r,q)=max \{w_i |r_i-q_i| \mid 1 \leq i \leq d\}\). More...