Go to the documentation of this file.
32 #ifndef __NABO_PRIVATE_H
33 #define __NABO_PRIVATE_H
42 #define __CL_ENABLE_EXCEPTIONS
48 #define _UNUSED __attribute__ ((unused))
64 template<
typename T,
typename A,
typename B>
65 inline T
dist2(
const A& v0,
const B& v1)
67 return (v0 - v1).squaredNorm();
71 template<
typename T,
typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
88 virtual unsigned long knn(
const Matrix& query,
IndexMatrix& indices,
Matrix& dists2,
const Index k,
const T epsilon,
const unsigned optionFlags,
const T maxRadius)
const;
89 virtual unsigned long knn(
const Matrix& query,
IndexMatrix& indices,
Matrix& dists2,
const Vector& maxRadii,
const Index k = 1,
const T epsilon = 0,
const unsigned optionFlags = 0)
const;
93 template<
typename T,
typename Heap,
typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
129 inline uint32_t
getDim(
const uint32_t dimChildBucketSize)
const
130 {
return dimChildBucketSize &
dimMask; }
197 unsigned long onePointKnn(
const Matrix& query,
IndexMatrix& indices,
Matrix& dists2,
int i, Heap& heap, std::vector<T>& off,
const T maxError,
const T maxRadius2,
const bool allowSelfMatch,
const bool collectStatistics,
const bool sortResults)
const;
208 template<
bool allowSelfMatch,
bool collectStatistics>
209 unsigned long recurseKnn(
const T* query,
const unsigned n, T rd, Heap& heap, std::vector<T>& off,
const T maxError,
const T maxRadius2)
const;
214 virtual unsigned long knn(
const Matrix& query,
IndexMatrix& indices,
Matrix& dists2,
const Index k,
const T epsilon,
const unsigned optionFlags,
const T maxRadius)
const;
215 virtual unsigned long knn(
const Matrix& query,
IndexMatrix& indices,
Matrix& dists2,
const Vector& maxRadii,
const Index k = 1,
const T epsilon = 0,
const unsigned optionFlags = 0)
const;
221 template<
typename T,
typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
236 const cl_device_type deviceType;
237 cl::Context& context;
238 mutable cl::Kernel knnKernel;
239 cl::CommandQueue queue;
243 OpenCLSearch(
const CloudType& cloud,
const Index dim,
const unsigned creationOptionFlags,
const cl_device_type deviceType);
249 void initOpenCL(
const char* clFileName,
const char* kernelName,
const std::string& additionalDefines =
"");
252 virtual unsigned long knn(
const Matrix& query, IndexMatrix& indices, Matrix& dists2,
const Index k,
const T epsilon,
const unsigned optionFlags,
const T maxRadius)
const;
253 virtual unsigned long knn(
const Matrix& query, IndexMatrix& indices, Matrix& dists2,
const Vector& maxRadii,
const Index k = 1,
const T epsilon = 0,
const unsigned optionFlags = 0)
const;
257 template<
typename T,
typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
258 struct BruteForceSearchOpenCL:
public OpenCLSearch<T, CloudType>
264 using OpenCLSearch<T, CloudType>::initOpenCL;
267 BruteForceSearchOpenCL(
const CloudType& cloud,
const Index dim,
const unsigned creationOptionFlags,
const cl_device_type deviceType);
271 template<
typename T,
typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
272 struct KDTreeBalancedPtInLeavesStackOpenCL:
public OpenCLSearch<T, CloudType>
286 using OpenCLSearch<T, CloudType>::context;
287 using OpenCLSearch<T, CloudType>::knnKernel;
289 using OpenCLSearch<T, CloudType>::initOpenCL;
297 BuildPoint(
const Vector& pos = Vector(),
const size_t index = 0): pos(pos), index(index) {}
301 typedef std::vector<BuildPoint> BuildPoints;
303 typedef typename BuildPoints::iterator BuildPointsIt;
305 typedef typename BuildPoints::const_iterator BuildPointsCstIt;
311 CompareDim(
const size_t dim):dim(dim){}
314 bool operator() (
const BuildPoint& p0,
const BuildPoint& p1) {
return p0.pos(dim) < p1.pos(dim); }
322 Node(
const int dim = -1,
const T cutVal = 0):dim(dim), cutVal(cutVal) {}
326 typedef std::vector<Node> Nodes;
332 inline size_t childLeft(
size_t pos)
const {
return 2*pos + 1; }
333 inline size_t childRight(
size_t pos)
const {
return 2*pos + 2; }
334 inline size_t parent(
size_t pos)
const {
return (pos-1)/2; }
335 size_t getTreeDepth(
size_t size)
const;
336 size_t getTreeSize(
size_t size)
const;
339 void buildNodes(
const BuildPointsIt first,
const BuildPointsIt last,
const size_t pos,
const Vector minValues,
const Vector maxValues);
343 KDTreeBalancedPtInLeavesStackOpenCL(
const CloudType& cloud,
const Index dim,
const unsigned creationOptionFlags,
const cl_device_type deviceType);
347 template<
typename T,
typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
348 struct KDTreeBalancedPtInNodesStackOpenCL:
public OpenCLSearch<T, CloudType>
362 using OpenCLSearch<T, CloudType>::context;
363 using OpenCLSearch<T, CloudType>::knnKernel;
365 using OpenCLSearch<T, CloudType>::initOpenCL;
369 typedef Index BuildPoint;
371 typedef std::vector<BuildPoint> BuildPoints;
373 typedef typename BuildPoints::iterator BuildPointsIt;
375 typedef typename BuildPoints::const_iterator BuildPointsCstIt;
380 const CloudType& cloud;
382 CompareDim(
const CloudType& cloud,
const size_t dim): cloud(cloud), dim(dim){}
385 bool operator() (
const BuildPoint& p0,
const BuildPoint& p1) {
return cloud.coeff(dim, p0) < cloud.coeff(dim, p1); }
393 Node(
const int dim = -2,
const Index index = 0):dim(dim), index(index) {}
397 typedef std::vector<Node> Nodes;
403 inline size_t childLeft(
size_t pos)
const {
return 2*pos + 1; }
404 inline size_t childRight(
size_t pos)
const {
return 2*pos + 2; }
405 inline size_t parent(
size_t pos)
const {
return (pos-1)/2; }
406 size_t getTreeDepth(
size_t size)
const;
407 size_t getTreeSize(
size_t size)
const;
410 void buildNodes(
const BuildPointsIt first,
const BuildPointsIt last,
const size_t pos,
const Vector minValues,
const Vector maxValues);
414 KDTreeBalancedPtInNodesStackOpenCL(
const CloudType& cloud,
const Index dim,
const unsigned creationOptionFlags,
const cl_device_type deviceType);
417 #endif // HAVE_OPENCL
BuildPoints::const_iterator BuildPointsCstIt
const-iterator to indices of points during kd-tree construction
T cutVal
for split node, split value
const Index dim
the dimensionality of the data-point cloud
virtual unsigned long knn(const Matrix &query, IndexMatrix &indices, Matrix &dists2, const Index k, const T epsilon, const unsigned optionFlags, const T maxRadius) const
BucketEntry(const T *pt=0, const Index index=0)
create a new bucket entry for a point in the data
NearestNeighbourSearch< T, CloudType >::IndexVector IndexVector
std::vector< Node > Nodes
dense vector of search nodes, provides better memory performances than many small objects
KDTree, unbalanced, points in leaves, stack, implicit bounds, ANN_KD_SL_MIDPT, optimised implementati...
Node(const uint32_t bucketSize, const uint32_t bucketIndex)
construct a leaf node
const uint32_t dimBitCount
number of bits required to store dimension index + number of dimensions
KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt(const CloudType &cloud, const Index dim, const unsigned creationOptionFlags, const Parameters &additionalParameters)
constructor, calls NearestNeighbourSearch<T>(cloud)
const CloudType & cloud
the reference to the data-point cloud, which must remain valid during the lifetime of the NearestNeig...
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > CloudType
a column-major Eigen matrix in which each column is a point; this matrix has dim rows
NearestNeighbourSearch< T, CloudType >::Vector Vector
const unsigned creationOptionFlags
creation options
const T * pt
pointer to first value of point data, 0 if end of bucket
std::vector< Index > BuildPoints
indices of points during kd-tree construction
NearestNeighbourSearch< T, CloudType >::Vector Vector
uint32_t createDimChildBucketSize(const uint32_t dim, const uint32_t childIndex) const
create the compound index containing the dimension and the index of the child or the bucket size
Index index
index of point
unsigned long onePointKnn(const Matrix &query, IndexMatrix &indices, Matrix &dists2, int i, Heap &heap, std::vector< T > &off, const T maxError, const T maxRadius2, const bool allowSelfMatch, const bool collectStatistics, const bool sortResults) const
search one point, call recurseKnn with the correct template parameters
Nearest neighbour search interface, templatized on scalar type.
unsigned long recurseKnn(const T *query, const unsigned n, T rd, Heap &heap, std::vector< T > &off, const T maxError, const T maxRadius2) const
recursive search, strongly inspired by ANN and [Arya & Mount, Algorithms for fast vector quantization...
const uint32_t dimMask
mask to access dim
T dist2(const A &v0, const B &v1)
Euclidean distance.
std::vector< BucketEntry > Buckets
bucket data
Node(const uint32_t dimChild, const T cutVal)
construct a split node
virtual unsigned long knn(const Matrix &query, IndexMatrix &indices, Matrix &dists2, const Index k, const T epsilon, const unsigned optionFlags, const T maxRadius) const
NearestNeighbourSearch< T, CloudType >::IndexMatrix IndexMatrix
uint32_t getDim(const uint32_t dimChildBucketSize) const
get the dimension out of the compound index
NearestNeighbourSearch< T, CloudType >::IndexVector IndexVector
uint32_t getChildBucketSize(const uint32_t dimChildBucketSize) const
get the child index or the bucket size out of the coumpount index
const unsigned bucketSize
size of bucket
unsigned buildNodes(const BuildPointsIt first, const BuildPointsIt last, const Vector minValues, const Vector maxValues)
construct nodes for points [first..last[ inside the hyperrectangle [minValues..maxValues]
uint32_t dimChildBucketSize
cut dimension for split nodes (dimBitCount lsb), index of right node or number of bucket(rest)....
BuildPoints::iterator BuildPointsIt
iterator to indices of points during kd-tree construction
NearestNeighbourSearch< T, CloudType >::Matrix Matrix
NearestNeighbourSearch< T, CloudType >::Index Index
uint32_t bucketIndex
for leaf node, pointer to bucket
NearestNeighbourSearch< T, CloudType >::IndexMatrix IndexMatrix
NearestNeighbourSearch< T, CloudType >::Matrix Matrix
std::pair< T, T > getBounds(const BuildPointsIt first, const BuildPointsIt last, const unsigned dim)
return the bounds of points from [first..last[ on dimension dim
Brute-force nearest neighbour.
NearestNeighbourSearch< T, CloudType >::Index Index
BruteForceSearch(const CloudType &cloud, const Index dim, const unsigned creationOptionFlags)
constructor, calls NearestNeighbourSearch<T>(cloud)
libnabo
Author(s): Stéphane Magnenat
autogenerated on Fri Aug 2 2024 08:39:11