Namespaces
	anyimpl

	cuda

	lsh

	mpi

	serialization

Classes
struct	enable_if

struct	enable_if< true, T >

struct	disable_if

struct	disable_if< true, T >

struct	same_type

struct	same_type< T, T >

struct	needs_kdtree_distance

struct	needs_vector_space_distance

struct	is_kdtree_distance

struct	is_vector_space_distance

struct	DummyDistance

struct	valid_combination

struct	AutotunedIndexParams

class	AutotunedIndex

struct	squareDistance

struct	squareDistance< L2_Simple< ElementType >, ElementType >

struct	squareDistance< L2_3D< ElementType >, ElementType >

struct	squareDistance< L2< ElementType >, ElementType >

struct	squareDistance< HellingerDistance< ElementType >, ElementType >

struct	squareDistance< ChiSquareDistance< ElementType >, ElementType >

class	CenterChooser

class	RandomCenterChooser

class	GonzalesCenterChooser

class	KMeansppCenterChooser

class	GroupWiseCenterChooser

struct	CompositeIndexParams

class	CompositeIndex

struct	Accumulator

struct	Accumulator< unsigned char >

struct	Accumulator< unsigned short >

struct	Accumulator< unsigned int >

struct	Accumulator< char >

struct	Accumulator< short >

struct	Accumulator< int >

struct	L2_Simple

struct	L2_3D

struct	L2

struct	L1

struct	MinkowskiDistance

struct	MaxDistance

struct	HammingLUT

struct	HammingPopcnt

struct	Hamming

struct	HistIntersectionDistance

struct	HellingerDistance

struct	ChiSquareDistance

struct	KL_Divergence

struct	HierarchicalClusteringIndexParams

class	HierarchicalClusteringIndex

struct	KDTreeCuda3dIndexParams

class	KDTreeCuda3dIndex

class	CudaKdTreeBuilder

struct	KDTreeIndexParams

class	KDTreeIndex

struct	KDTreeSingleIndexParams

class	KDTreeSingleIndex

struct	KMeansIndexParams

class	KMeansIndex

struct	LinearIndexParams

class	LinearIndex

struct	LshIndexParams

class	LshIndex

class	IndexBase

class	NNIndex

struct	SavedIndexParams

class	Index

class	FLANNException

struct	flann_datatype_value

struct	flann_datatype_value< char >

struct	flann_datatype_value< short >

struct	flann_datatype_value< int >

struct	flann_datatype_value< unsigned char >

struct	flann_datatype_value< unsigned short >

struct	flann_datatype_value< unsigned int >

struct	flann_datatype_value< float >

struct	flann_datatype_value< double >

struct	flann_datatype_type

struct	flann_datatype_type< FLANN_INT8 >

struct	flann_datatype_type< FLANN_INT16 >

struct	flann_datatype_type< FLANN_INT32 >

struct	flann_datatype_type< FLANN_UINT8 >

struct	flann_datatype_type< FLANN_UINT16 >

struct	flann_datatype_type< FLANN_UINT32 >

struct	flann_datatype_type< FLANN_FLOAT32 >

struct	flann_datatype_type< FLANN_FLOAT64 >

struct	Request

struct	Response

class	PooledAllocator

class	any

class	DynamicBitset

class	Heap

class	IntervalHeap

class	BoundedHeap

class	Logger

class	Matrix_

class	Matrix

class	CreatorNotFound

class	ObjectFactory

struct	SearchParams

class	RandomGenerator

class	UniqueRandom

struct	BranchStruct

struct	DistanceIndex

class	ResultSet

class	KNNSimpleResultSet

class	KNNResultSet

class	KNNResultSet2

class	RadiusResultSet

class	KNNRadiusResultSet

class	CountRadiusResultSet

class	UniqueResultSet

class	KNNUniqueResultSet

class	RadiusUniqueResultSet

class	KNNRadiusUniqueResultSet

struct	IndexHeader

struct	IndexHeaderStruct

class	StartStopTimer

Typedefs
typedef unsigned char	uchar

typedef std::map< std::string, any >	IndexParams

Enumerations
enum	tri_type { FLANN_False = 0 , FLANN_True = 1 , FLANN_Undefined }

Functions
template<template< typename > class Index, typename Distance , typename T >
NNIndex< Distance > *	create_index_ (flann::Matrix< T > data, const flann::IndexParams &params, const Distance &distance, typename enable_if< valid_combination< Index, Distance, T >::value, void >::type *=0)

template<template< typename > class Index, typename Distance , typename T >
NNIndex< Distance > *	create_index_ (flann::Matrix< T > data, const flann::IndexParams &params, const Distance &distance, typename disable_if< valid_combination< Index, Distance, T >::value, void >::type *=0)

template<typename Distance >
NNIndex< Distance > *	create_index_by_type (const flann_algorithm_t index_type, const Matrix< typename Distance::ElementType > &dataset, const IndexParams &params, const Distance &distance)

template<typename Distance >
Distance::ResultType	ensureSquareDistance (typename Distance::ResultType dist)

std::ostream &	operator<< (std::ostream &stream, const cuda::kd_tree_builder_detail::SplitInfo &s)

void	log_verbosity (int level)

template<typename Distance >
int	hierarchicalClustering (const Matrix< typename Distance::ElementType > &points, Matrix< typename Distance::ResultType > &centers, const KMeansIndexParams &params, Distance d=Distance())

size_t	flann_datatype_size (flann_datatype_t type)

template<typename T >
void	save_to_file (const flann::Matrix< T > &dataset, const std::string &filename, const std::string &name)

template<typename T >
void	load_from_file (flann::Matrix< T > &dataset, const std::string &filename, const std::string &name)

template<typename T >
void	read_object (tcp::socket &sock, T &val)

template<typename T >
void	write_object (tcp::socket &sock, const T &val)

template<typename Distance >
void	find_nearest (const Matrix< typename Distance::ElementType > &dataset, typename Distance::ElementType query, size_t matches, size_t nn, size_t skip=0, Distance distance=Distance())

template<typename Distance >
void	compute_ground_truth (const Matrix< typename Distance::ElementType > &dataset, const Matrix< typename Distance::ElementType > &testset, Matrix< size_t > &matches, int skip=0, Distance d=Distance())

int	countCorrectMatches (size_t neighbors, size_t groundTruth, int n)

template<typename Distance >
Distance::ResultType	computeDistanceRaport (const Matrix< typename Distance::ElementType > &inputData, typename Distance::ElementType target, size_t neighbors, size_t *groundTruth, int veclen, int n, const Distance &distance)

template<typename Index , typename Distance >
float	search_with_ground_truth (Index &index, const Matrix< typename Distance::ElementType > &inputData, const Matrix< typename Distance::ElementType > &testData, const Matrix< size_t > &matches, int nn, int checks, float &time, typename Distance::ResultType &dist, const Distance &distance, int skipMatches)

template<typename Index , typename Distance >
float	test_index_checks (Index &index, const Matrix< typename Distance::ElementType > &inputData, const Matrix< typename Distance::ElementType > &testData, const Matrix< size_t > &matches, int checks, float &precision, const Distance &distance, int nn=1, int skipMatches=0)

template<typename Index , typename Distance >
float	test_index_precision (Index &index, const Matrix< typename Distance::ElementType > &inputData, const Matrix< typename Distance::ElementType > &testData, const Matrix< size_t > &matches, float precision, int &checks, const Distance &distance, int nn=1, int skipMatches=0)

template<typename Index , typename Distance >
void	test_index_precisions (Index &index, const Matrix< typename Distance::ElementType > &inputData, const Matrix< typename Distance::ElementType > &testData, const Matrix< int > &matches, float *precisions, int precisions_length, const Distance &distance, int nn=1, int skipMatches=0, float maxTime=0)

template<typename T >
void	addValue (int pos, float val, float vals, T point, T *points, int n)

template<typename T , typename F >
float	optimizeSimplexDownhill (T points, int n, F func, float vals=NULL)

template<typename T >
T *	allocate (size_t count=1)

std::ostream &	operator<< (std::ostream &out, const any &any_val)

bool	has_param (const IndexParams &params, std::string name)

template<typename T >
T	get_param (const IndexParams &params, std::string name, const T &default_value)

template<typename T >
T	get_param (const IndexParams &params, std::string name)

void	print_params (const IndexParams &params)

void	print_params (const SearchParams &params)

void	seed_random (unsigned int seed)

double	rand_double (double high=1.0, double low=0)

int	rand_int (int high=RAND_MAX, int low=0)

template<typename T >
Matrix< T >	random_sample (Matrix< T > &srcMatrix, size_t size, bool remove=false)

template<typename Index >
void	save_header (FILE *stream, const Index &index)

IndexHeader	load_header (FILE *stream)

Variables
const size_t	WORDSIZE =16

const size_t	BLOCKSIZE =8192

Typedef Documentation

◆ IndexParams

typedef std::map<std::string, any> flann::IndexParams

Definition at line 51 of file params.h.

◆ uchar

typedef unsigned char flann::uchar

Definition at line 41 of file matrix.h.

Enumeration Type Documentation

◆ tri_type

enum flann::tri_type

Enumerator
FLANN_False
FLANN_True
FLANN_Undefined

Definition at line 54 of file params.h.

Function Documentation

◆ addValue()

template<typename T >

void flann::addValue	(	int	pos,
		float	val,
		float *	vals,
		T *	point,
		T *	points,
		int	n
	)

Adds val to array vals (and point to array points) and keeping the arrays sorted by vals.

Definition at line 41 of file simplex_downhill.h.

References points, and cloudViewer::utility::swap().

Referenced by optimizeSimplexDownhill().

◆ allocate()

template<typename T >

T* flann::allocate ( size_t count = 1 )

Allocates (using C's malloc) a generic type T.

Params: count = number of instances to allocate. Returns: pointer (of type T*) to memory buffer

Definition at line 49 of file allocator.h.

References count.

◆ compute_ground_truth()

template<typename Distance >

void flann::compute_ground_truth	(	const Matrix< typename Distance::ElementType > &	dataset,
		const Matrix< typename Distance::ElementType > &	testset,
		Matrix< size_t > &	matches,
		int	skip = `0`,
		Distance	d = `Distance()`
	)

Definition at line 87 of file ground_truth.h.

References flann::Matrix_::cols, and flann::Matrix_::rows.

◆ computeDistanceRaport()

template<typename Distance >

Distance::ResultType flann::computeDistanceRaport	(	const Matrix< typename Distance::ElementType > &	inputData,
		typename Distance::ElementType *	target,
		size_t *	neighbors,
		size_t *	groundTruth,
		int	veclen,
		int	n,
		const Distance &	distance
	)

Definition at line 64 of file index_testing.h.

◆ countCorrectMatches()

int flann::countCorrectMatches	(	size_t *	neighbors,
		size_t *	groundTruth,
		int	n
	)

inline

Definition at line 48 of file index_testing.h.

References count.

Referenced by search_with_ground_truth().

◆ create_index_() [1/2]

template<template< typename > class Index, typename Distance , typename T >

NNIndex<Distance>* flann::create_index_	(	flann::Matrix< T >	data,
		const flann::IndexParams &	params,
		const Distance &	distance,
		typename disable_if< valid_combination< Index, Distance, T >::value, void >::type *	= `0`
	)

inline

Definition at line 136 of file all_indices.h.

References NULL.

◆ create_index_() [2/2]

template<template< typename > class Index, typename Distance , typename T >

NNIndex<Distance>* flann::create_index_	(	flann::Matrix< T >	data,
		const flann::IndexParams &	params,
		const Distance &	distance,
		typename enable_if< valid_combination< Index, Distance, T >::value, void >::type *	= `0`
	)

inline

Definition at line 129 of file all_indices.h.

References params.

◆ create_index_by_type()

template<typename Distance >

NNIndex<Distance>* flann::create_index_by_type	(	const flann_algorithm_t	index_type,
		const Matrix< typename Distance::ElementType > &	dataset,
		const IndexParams &	params,
		const Distance &	distance
	)

inline

#define this symbol before including flann.h to enable GPU search algorithms. But you have to link libflann_cuda then!

Definition at line 144 of file all_indices.h.

References FLANN_INDEX_AUTOTUNED, FLANN_INDEX_COMPOSITE, FLANN_INDEX_HIERARCHICAL, FLANN_INDEX_KDTREE, FLANN_INDEX_KDTREE_SINGLE, FLANN_INDEX_KMEANS, FLANN_INDEX_LINEAR, FLANN_INDEX_LSH, NULL, and params.

Referenced by flann::AutotunedIndex< Distance >::buildIndex().

◆ ensureSquareDistance()

template<typename Distance >

Distance::ResultType flann::ensureSquareDistance ( typename Distance::ResultType dist )

Definition at line 63 of file center_chooser.h.

References dist().

◆ find_nearest()

template<typename Distance >

void flann::find_nearest	(	const Matrix< typename Distance::ElementType > &	dataset,
		typename Distance::ElementType *	query,
		size_t *	matches,
		size_t	nn,
		size_t	skip = `0`,
		Distance	distance = `Distance()`
	)

Definition at line 42 of file ground_truth.h.

References flann::Matrix_::cols, flann::Matrix_::rows, and std::swap().

◆ flann_datatype_size()

size_t flann::flann_datatype_size ( flann_datatype_t type )

inline

Definition at line 196 of file general.h.

References FLANN_FLOAT32, FLANN_FLOAT64, FLANN_INT16, FLANN_INT32, FLANN_INT64, FLANN_INT8, FLANN_UINT16, FLANN_UINT32, FLANN_UINT64, FLANN_UINT8, and type.

Referenced by flann::Matrix_::Matrix_().

◆ get_param() [1/2]

template<typename T >

T flann::get_param	(	const IndexParams &	params,
		std::string	name
	)

Definition at line 107 of file params.h.

References name, and params.

◆ get_param() [2/2]

template<typename T >

T flann::get_param	(	const IndexParams &	params,
		std::string	name,
		const T &	default_value
	)

Definition at line 95 of file params.h.

References name, and params.

Referenced by flann::AutotunedIndex< Distance >::AutotunedIndex(), flann::HierarchicalClusteringIndex< Distance >::HierarchicalClusteringIndex(), flann::KDTreeCuda3dIndex< Distance >::KDTreeCuda3dIndex(), flann::KDTreeIndex< Distance >::KDTreeIndex(), flann::KDTreeSingleIndex< Distance >::KDTreeSingleIndex(), flann::KMeansIndex< Distance >::KMeansIndex(), and flann::NNIndex< Distance >::serialize().

◆ has_param()

bool flann::has_param	(	const IndexParams &	params,
		std::string	name
	)

inline

Definition at line 89 of file params.h.

References name, and params.

Referenced by update_flann_parameters().

◆ hierarchicalClustering()

template<typename Distance >

int flann::hierarchicalClustering	(	const Matrix< typename Distance::ElementType > &	points,
		Matrix< typename Distance::ResultType > &	centers,
		const KMeansIndexParams &	params,
		Distance	d = `Distance()`
	)

Performs a hierarchical clustering of the points passed as argument and then takes a cut in the the clustering tree to return a flat clustering.

Parameters

[in]	points	Points to be clustered
	centers	The computed cluster centres. Matrix should be preallocated and centers.rows is the number of clusters requested.
	params	Clustering parameters (The same as for flann::KMeansIndex)
	d	Distance to be used for clustering (eg: flann::L2)

Returns: number of clusters computed (can be different than clusters.rows and is the highest number of the form (branching-1)*K+1 smaller than clusters.rows).

Definition at line 424 of file flann.hpp.

References flann::KMeansIndex< Distance >::buildIndex(), flann::KMeansIndex< Distance >::getClusterCenters(), params, and points.

◆ load_from_file()

template<typename T >

void flann::load_from_file	(	flann::Matrix< T > &	dataset,
		const std::string &	filename,
		const std::string &	name
	)

Definition at line 130 of file hdf5.h.

References CHECK_ERROR, filename, name, and NULL.

Referenced by flann::mpi::Index< Distance >::Index(), and main().

◆ load_header()

IndexHeader flann::load_header ( FILE * stream )

inline

Parameters

stream - Stream to load from

Returns: Index header

Definition at line 106 of file saving.h.

References FLANN_SIGNATURE_, flann::IndexHeader::h, and flann::IndexHeaderStruct::signature.

◆ log_verbosity()

void flann::log_verbosity ( int level )

inline

Sets the log level used for all flann functions

Parameters

level Verbosity level

Definition at line 54 of file flann.hpp.

References flann::Logger::setLevel().

Referenced by flann_log_verbosity().

◆ operator<<() [1/2]

std::ostream& flann::operator<<	(	std::ostream &	out,
		const any &	any_val
	)

inline

Definition at line 288 of file any.h.

◆ operator<<() [2/2]

std::ostream& flann::operator<<	(	std::ostream &	stream,
		const cuda::kd_tree_builder_detail::SplitInfo &	s
	)

Definition at line 396 of file kdtree_cuda_builder.h.

References flann::cuda::kd_tree_builder_detail::SplitInfo::left, flann::cuda::kd_tree_builder_detail::SplitInfo::right, flann::cuda::kd_tree_builder_detail::SplitInfo::split_dim, and flann::cuda::kd_tree_builder_detail::SplitInfo::split_val.

◆ optimizeSimplexDownhill()

template<typename T , typename F >

float flann::optimizeSimplexDownhill	(	T *	points,
		int	n,
		F	func,
		float *	vals = `NULL`
	)

Simplex downhill optimization function. Preconditions: points is a 2D mattrix of size (n+1) x n func is the cost function taking n an array of n params and returning float vals is the cost function in the n+1 simplex points, if NULL it will be computed

Postcondition: returns optimum value and points[0..n] are the optimum parameters

Definition at line 69 of file simplex_downhill.h.

References addValue(), flann::Logger::info(), NULL, and points.

◆ print_params() [1/2]

void flann::print_params ( const IndexParams & params )

inline

Definition at line 118 of file params.h.

References QtCompat::endl(), and params.

Referenced by flann::AutotunedIndex< Distance >::buildIndex().

◆ print_params() [2/2]

void flann::print_params ( const SearchParams & params )

inline

Definition at line 127 of file params.h.

References QtCompat::endl(), and params.

◆ rand_double()

double flann::rand_double	(	double	high = `1.0`,
		double	low = `0`
	)

inline

Generates a random double value.

Parameters

high	Upper limit
low	Lower limit

Returns: Random double value

Definition at line 63 of file random.h.

Referenced by flann::KMeansppCenterChooser< Distance >::operator()().

◆ rand_int()

int flann::rand_int	(	int	high = `RAND_MAX`,
		int	low = `0`
	)

inline

Generates a random integer value.

Parameters

high	Upper limit
low	Lower limit

Returns: Random integer value

Definition at line 74 of file random.h.

Referenced by flann::GonzalesCenterChooser< Distance >::operator()(), flann::KMeansppCenterChooser< Distance >::operator()(), flann::GroupWiseCenterChooser< Distance >::operator()(), flann::RandomGenerator::operator()(), and random_sample().

◆ random_sample()

template<typename T >

Matrix<T> flann::random_sample	(	Matrix< T > &	srcMatrix,
		size_t	size,
		bool	remove = `false`
	)

Definition at line 40 of file sampling.h.

References flann::Matrix_::cols, copy, flann::UniqueRandom::next(), rand_int(), flann::Matrix_::rows, and size.

Referenced by CP::CutPursuit_KL< T >::init_labels(), CP::CutPursuit_L2< T >::init_labels(), and CP::CutPursuit_SPG< T >::init_labels().

◆ read_object()

template<typename T >

void flann::read_object	(	tcp::socket &	sock,
		T &	val
	)

Definition at line 72 of file queries.h.

References size.

Referenced by flann::mpi::Client::knnSearch().

◆ save_header()

template<typename Index >

void flann::save_header	(	FILE *	stream,
		const Index &	index
	)

Saves index header to stream

Parameters

stream	- Stream to save to
index	- The index to save

Definition at line 89 of file saving.h.

References flann::IndexHeaderStruct::cols, flann::IndexHeaderStruct::data_type, flann::Index< Distance >::getType(), flann::IndexHeader::h, flann::IndexHeaderStruct::index_type, flann::IndexHeaderStruct::rows, flann::Index< Distance >::size(), and flann::Index< Distance >::veclen().

◆ save_to_file()

template<typename T >

void flann::save_to_file	(	const flann::Matrix< T > &	dataset,
		const std::string &	filename,
		const std::string &	name
	)

Definition at line 78 of file hdf5.h.

References CHECK_ERROR, flann::Matrix_::cols, filename, name, NULL, flann::Matrix< T >::ptr(), and flann::Matrix_::rows.

◆ search_with_ground_truth()

template<typename Index , typename Distance >

float flann::search_with_ground_truth	(	Index &	index,
		const Matrix< typename Distance::ElementType > &	inputData,
		const Matrix< typename Distance::ElementType > &	testData,
		const Matrix< size_t > &	matches,
		int	nn,
		int	checks,
		float &	time,
		typename Distance::ResultType &	dist,
		const Distance &	distance,
		int	skipMatches
	)

Definition at line 86 of file index_testing.h.

References flann::Matrix_::cols, countCorrectMatches(), dist(), flann::Logger::info(), flann::Index< Distance >::knnSearch(), flann::Matrix_::rows, flann::StartStopTimer::start(), flann::StartStopTimer::stop(), and flann::StartStopTimer::value.

Referenced by test_index_checks(), test_index_precision(), and test_index_precisions().

◆ seed_random()

void flann::seed_random ( unsigned int seed )

inline

Seeds the random number generator

Parameters

seed	Random seed

Definition at line 49 of file random.h.

Referenced by init_flann_parameters().

◆ test_index_checks()

template<typename Index , typename Distance >

float flann::test_index_checks	(	Index &	index,
		const Matrix< typename Distance::ElementType > &	inputData,
		const Matrix< typename Distance::ElementType > &	testData,
		const Matrix< size_t > &	matches,
		int	checks,
		float &	precision,
		const Distance &	distance,
		int	nn = `1`,
		int	skipMatches = `0`
	)

Definition at line 142 of file index_testing.h.

References dist(), flann::Logger::info(), and search_with_ground_truth().

◆ test_index_precision()

template<typename Index , typename Distance >

float flann::test_index_precision	(	Index &	index,
		const Matrix< typename Distance::ElementType > &	inputData,
		const Matrix< typename Distance::ElementType > &	testData,
		const Matrix< size_t > &	matches,
		float	precision,
		int &	checks,
		const Distance &	distance,
		int	nn = `1`,
		int	skipMatches = `0`
	)

Definition at line 159 of file index_testing.h.

References dist(), fabs(), flann::Logger::info(), and search_with_ground_truth().

◆ test_index_precisions()

template<typename Index , typename Distance >

void flann::test_index_precisions	(	Index &	index,
		const Matrix< typename Distance::ElementType > &	inputData,
		const Matrix< typename Distance::ElementType > &	testData,
		const Matrix< int > &	matches,
		float *	precisions,
		int	precisions_length,
		const Distance &	distance,
		int	nn = `1`,
		int	skipMatches = `0`,
		float	maxTime = `0`
	)

Definition at line 232 of file index_testing.h.

References dist(), fabs(), flann::Logger::info(), and search_with_ground_truth().

◆ write_object()

template<typename T >

void flann::write_object	(	tcp::socket &	sock,
		const T &	val
	)

Definition at line 86 of file queries.h.

References size.

Referenced by flann::mpi::Client::knnSearch().

Variable Documentation

◆ BLOCKSIZE

const size_t flann::BLOCKSIZE =8192

Definition at line 73 of file allocator.h.

Referenced by flann::PooledAllocator::allocateMemory().

◆ WORDSIZE

const size_t flann::WORDSIZE =16

Pooled storage allocator

The following routines allow for the efficient allocation of storage in small chunks from a specified pool. Rather than allowing each structure to be freed individually, an entire pool of storage is freed at once. This method has two advantages over just using malloc() and free(). First, it is far more efficient for allocating small objects, as there is no overhead for remembering all the information needed to free each object or consolidating fragmented memory. Second, the decision about how long to keep an object is made at the time of allocation, and there is no need to track down all the objects to free them.

Definition at line 72 of file allocator.h.

Referenced by flann::PooledAllocator::allocateMemory().

Namespaces

Classes

Typedefs

Enumerations

Functions

Variables

Typedef Documentation

◆ IndexParams

◆ uchar

Enumeration Type Documentation

◆ tri_type

Function Documentation

◆ addValue()

◆ allocate()

◆ compute_ground_truth()

◆ computeDistanceRaport()

◆ countCorrectMatches()

◆ create_index_() [1/2]

◆ create_index_() [2/2]

◆ create_index_by_type()

◆ ensureSquareDistance()

◆ find_nearest()

◆ flann_datatype_size()

◆ get_param() [1/2]

◆ get_param() [2/2]

◆ has_param()

◆ hierarchicalClustering()

◆ load_from_file()

◆ load_header()

◆ log_verbosity()

◆ operator<<() [1/2]

◆ operator<<() [2/2]

◆ optimizeSimplexDownhill()

◆ print_params() [1/2]

◆ print_params() [2/2]

◆ rand_double()

◆ rand_int()

◆ random_sample()

◆ read_object()

◆ save_header()

◆ save_to_file()

◆ search_with_ground_truth()

◆ seed_random()

◆ test_index_checks()

◆ test_index_precision()

◆ test_index_precisions()

◆ write_object()

Variable Documentation

◆ BLOCKSIZE

◆ WORDSIZE