#include <type_traits>
#include <initializer_list>
#include <memory>
#include <algorithm>
#include <array>
#include <queue>
#include <deque>
#include <list>
#include <tuple>
#include <unordered_set>
#include <unordered_map>
#include <utility>
#include <fstream>
#include <meta/meta.hpp>
#include "ApproxMVBB/Config/Config.hpp"
#include "ApproxMVBB/Common/StaticAssert.hpp"
#include "ApproxMVBB/Common/SfinaeMacros.hpp"
#include "ApproxMVBB/Common/ContainerTag.hpp"
#include "ApproxMVBB/AABB.hpp"
Go to the source code of this file.
Classes |
struct | ApproxMVBB::KdTree::TreeTraits< TNodeData, TSplitHeuristic, TNode >::BaseTraits |
struct | ApproxMVBB::KdTree::TreeSimpleTraits< TNodeData, TNode >::BaseTraits |
class | ApproxMVBB::KdTree::NodeBase< TDerivedNode, Dimension >::BoundaryInformation |
struct | ApproxMVBB::KdTree::DefaultDistanceCompTraits< TPoint, TPointGetter > |
class | ApproxMVBB::KdTree::DefaultPointDataTraits< Dim, TPoint, TValue, TPointGetter, TDistanceCompTraits > |
struct | ApproxMVBB::KdTree::DistanceComp< TPoint, TPointGetter, DistSq > |
struct | ApproxMVBB::KdTree::EuclideanDistSq |
struct | ApproxMVBB::KdTree::Tree< TTraits >::isKNNTraits< KNNTraits< N, C > > |
class | ApproxMVBB::KdTree::Tree< TTraits >::KNearestPrioQueue< Container, Compare > |
struct | ApproxMVBB::KdTree::Tree< TTraits >::KNNTraits< TDistSq, TContainer > |
class | ApproxMVBB::KdTree::LinearQualityEvaluator |
class | ApproxMVBB::KdTree::NearestNeighbourFilter< TTraits > |
struct | ApproxMVBB::KdTree::NoData< Dim > |
class | ApproxMVBB::KdTree::Node< TTraits > |
class | ApproxMVBB::KdTree::NodeBase< TDerivedNode, Dimension > |
class | ApproxMVBB::KdTree::NodeSimple< TTraits, PD > |
struct | ApproxMVBB::KdTree::Tree< TTraits >::ParentInfo |
class | ApproxMVBB::KdTree::PointData< TTraits > |
struct | ApproxMVBB::KdTree::DefaultPointDataTraits< Dim, TPoint, TValue, TPointGetter, TDistanceCompTraits >::PointGetterImpl< T > |
struct | ApproxMVBB::KdTree::DefaultPointDataTraits< Dim, TPoint, TValue, TPointGetter, TDistanceCompTraits >::PointGetterImpl< TT * > |
struct | ApproxMVBB::KdTree::details::select< PD, T > |
struct | ApproxMVBB::KdTree::details::select< void, T > |
class | ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits > |
class | ApproxMVBB::KdTree::Tree< TTraits > |
class | ApproxMVBB::KdTree::TreeBase< Traits > |
class | ApproxMVBB::KdTree::TreeSimple< TTraits > |
struct | ApproxMVBB::KdTree::TreeSimpleTraits< TNodeData, TNode > |
class | ApproxMVBB::KdTree::TreeStatistics |
struct | ApproxMVBB::KdTree::TreeTraits< TNodeData, TSplitHeuristic, TNode > |
Namespaces |
namespace | ApproxMVBB |
| These are some container definitions.
|
namespace | ApproxMVBB::KdTree |
namespace | ApproxMVBB::KdTree::details |
Defines |
#define | DEFINE_KDTREE_BASENODETYPES(_Base_) |
#define | DEFINE_KDTREE_BASETYPES(__Traits__) |
Define Documentation
Value:using SplitAxisType = typename _Base_::SplitAxisType; \
using BoundaryInfoType = typename _Base_::BoundaryInfoType;
Definition at line 724 of file KdTree.hpp.
Value: \
using NodeDataType = typename __Traits__::NodeDataType; \
static const unsigned int Dimension = __Traits__::NodeDataType::Dimension; \
using NodeType = typename __Traits__::NodeType; \
\
using NodeContainerType = std::vector<NodeType *>; \
using LeafContainerType = NodeContainerType; \
using LeafNeighbourMapType = std::unordered_map<std::size_t, std::unordered_set<std::size_t> >;
Definition at line 62 of file KdTree.hpp.