MetricKnn provides a set of pre-defined indexes. More...

#include <mknn_predefined_index.hpp>

Static Public Member Functions
Help functions.
static void	helpListIndexes ()
	Lists to standard output all pre-defined indexes.

static void	helpPrintIndex (std::string id_index)
	Prints to standard output the help for a index. More...

static bool	testIndexId (std::string id_index)
	Tests whether the given string references a valid pre-defined index. More...

Linear Scan.
static IndexParams	LinearScan_indexParams ()
	Resolves searches using the linear scan algorithm. More...

static ResolverParams	LinearScan_resolverExactNearestNeighbors (long long knn, double range, long long max_threads)
	Creates a new resolver for exact search of the K nearest neighbors using the linear scan index. More...

static ResolverParams	LinearScan_resolverExactFarthestNeighbors (long long knn, long long max_threads)
	Creates a new resolver for exact search of the K farthest neighbors using the linear scan index. More...

LAESA.
static IndexParams	Laesa_indexParams (long long num_pivots)
	Resolves searches using the LAESA algorithm. More...

static ResolverParams	Laesa_resolverExactNearestNeighbors (long long knn, double range, long long max_threads)
	Creates a new resolver for exact search using the LAESA index. More...

static ResolverParams	Laesa_resolverApproximateNearestNeighbors (long long knn, double range, long long max_threads, double approximation_percentage)

Snake Table.
static IndexParams	SnakeTable_indexParams (long long num_pivots)
	Resolves searches using a Snake Table. More...

static ResolverParams	SnakeTable_resolverExactNearestNeighbors (long long knn, double range, long long max_threads)
	Creates a new resolver for exact search using the SnakeTable index. More...

FLANN Indexes.
static IndexParams	FlannLinearScan_indexParams ()
	Resolves searches using the FLANN's implementation of linear scan algorithm. More...

static IndexParams	FlannKdTree_indexParams (long long num_trees)
	Resolves searches using FLANN's implementation of kd-tree. More...

static IndexParams	FlannKmeansTree_indexParams (long long branching, long long iterations)
	Resolves searches using FLANN's implementation of k-means tree. More...

static IndexParams	FlannLSH_indexParams (long long table_number, long long key_size, long long multi_probe_level)
	Resolves searches using FLANN's implementation of Local Sensitive Hashing. More...

static IndexParams	FlannAutoIndex_indexParams (double target_precision, double build_weight, double memory_weight, double sample_fraction)
	Resolves searches using FLANN's automatic selection of the best algorithm. More...

static ResolverParams	Flann_resolverExactNearestNeighbors (long long knn, long long max_threads)
	Creates a new resolver for exact searches using FLANN's indexes. More...

static ResolverParams	Flann_resolverApproximateNearestNeighbors (long long knn, long long max_threads, long long num_checks)
	Creates a new resolver for approximate searches using FLANN's indexes. More...

Detailed Description

MetricKnn provides a set of pre-defined indexes.

The complete list of pre-defined indexes provided by MetricKnn can be printed by calling PredefIndex::helpListIndexes. The parameters supported by each index can be printed by calling PredefIndex::helpPrintIndex.

Member Function Documentation

static ResolverParams mknn::PredefIndex::Flann_resolverApproximateNearestNeighbors	(	long long	knn,
		long long	max_threads,
		long long	num_checks
	)

static

Creates a new resolver for approximate searches using FLANN's indexes.

Parameters

knn	number of nearest neighbors to return. A value < 1 means 1.
max_threads	the maximum number of threads to be used.
num_checks	how many leafs to check in one search. A value >= 1, where a value closer to 1 means faster (but lower quality) search.

Returns: an object with the configuration of a similarity search.

static ResolverParams mknn::PredefIndex::Flann_resolverExactNearestNeighbors	(	long long	knn,
		long long	max_threads
	)

static

Creates a new resolver for exact searches using FLANN's indexes.

Parameters

knn	number of nearest neighbors to return. A value < 1 means 1.
max_threads	the maximum number of threads to be used.

Returns: an object with the configuration of a similarity search.

static IndexParams mknn::PredefIndex::FlannAutoIndex_indexParams	(	double	target_precision,
		double	build_weight,
		double	memory_weight,
		double	sample_fraction
	)

static

Resolves searches using FLANN's automatic selection of the best algorithm.

This method is just an interface to FLANN library. See FLANN's documentation http://www.cs.ubc.ca/research/flann/ .

Parameters

target_precision	precision desired
build_weight	build tree time weighting factor
memory_weight	index memory weigthing factor
sample_fraction	what fraction of the dataset to use for autotuning

Returns: the new index (must be released with delete)

static IndexParams mknn::PredefIndex::FlannKdTree_indexParams ( long long num_trees )

static

Resolves searches using FLANN's implementation of kd-tree.

This method is just an interface to FLANN library. See FLANN's documentation http://www.cs.ubc.ca/research/flann/ .

Parameters

num_trees Amount of trees to build.

Returns: the new index (must be released with delete)

static IndexParams mknn::PredefIndex::FlannKmeansTree_indexParams	(	long long	branching,
		long long	iterations
	)

static

Resolves searches using FLANN's implementation of k-means tree.

This method is just an interface to FLANN library. See FLANN's documentation http://www.cs.ubc.ca/research/flann/ .

Parameters

branching	branching factor. Number of centroids at each level.
iterations	max iterations to perform in one kmeans clustering.

Returns: the new index (must be released with delete)

static IndexParams mknn::PredefIndex::FlannLinearScan_indexParams ( )

static

Resolves searches using the FLANN's implementation of linear scan algorithm.

This method is just an interface to FLANN library. See FLANN's documentation http://www.cs.ubc.ca/research/flann/ .

Returns: the new index (must be released with delete)

static IndexParams mknn::PredefIndex::FlannLSH_indexParams	(	long long	table_number,
		long long	key_size,
		long long	multi_probe_level
	)

static

Resolves searches using FLANN's implementation of Local Sensitive Hashing.

This method is just an interface to FLANN library. See FLANN's documentation http://www.cs.ubc.ca/research/flann/ .

Parameters

table_number	The number of hash tables to use
key_size	The length of the key in the hash tables
multi_probe_level	Number of levels to use in multi-probe LSH, 0 for standard LSH

Returns: the new index (must be released with delete)

static void mknn::PredefIndex::helpPrintIndex ( std::string id_index )

static

Prints to standard output the help for a index.

Parameters

id_index the unique identifier of a pre-defined index.

static IndexParams mknn::PredefIndex::Laesa_indexParams ( long long num_pivots )

static

Resolves searches using the LAESA algorithm.

In order to obtain the exact nearest neighbors, the distance dist_factory must satisfy the metric properties, otherwise the exact search will be incorrect.

Parameters

num_pivots Amount of pivots to compute and store in memory.

Returns: the new index (must be released with delete)

static ResolverParams mknn::PredefIndex::Laesa_resolverApproximateNearestNeighbors	(	long long	knn,
		double	range,
		long long	max_threads,
		double	approximation_percentage
	)

static

Parameters

knn	number of nearest neighbors to return. A value < 1 means 1.
range	the search range. A value <= 0 or the constant `DBL_MAX` mean maximum range.
max_threads	the maximum number of threads to be used.
approximation_percentage	The amount of distance evaluation to compute. A value between 0 and 1, where a value closer to 0 means faster (but lower quality) search.

Returns: an object with the configuration of a similarity search.

static ResolverParams mknn::PredefIndex::Laesa_resolverExactNearestNeighbors	(	long long	knn,
		double	range,
		long long	max_threads
	)

static

Creates a new resolver for exact search using the LAESA index.

Parameters

knn	number of nearest neighbors to return. A value < 1 means 1.
range	the search range. A value <= 0 or constant `DBL_MAX` mean maximum range.
max_threads	the maximum number of threads to be used.

Returns: an object with the configuration of a similarity search.

static IndexParams mknn::PredefIndex::LinearScan_indexParams ( )

static

Resolves searches using the linear scan algorithm.

The algorithm compares each query object to each object in search_dataset sequentially and retrieves the nearest objects.

Returns: the new index (must be released with delete)

static ResolverParams mknn::PredefIndex::LinearScan_resolverExactFarthestNeighbors	(	long long	knn,
		long long	max_threads
	)

static

Creates a new resolver for exact search of the K farthest neighbors using the linear scan index.

Parameters

knn	number of farthest neighbors to return. A value < 1 means 1.
max_threads	the maximum number of threads to be used.

Returns: an object with the configuration of a similarity search.

static ResolverParams mknn::PredefIndex::LinearScan_resolverExactNearestNeighbors	(	long long	knn,
		double	range,
		long long	max_threads
	)

static

Creates a new resolver for exact search of the K nearest neighbors using the linear scan index.

Parameters

knn	number of nearest neighbors to return. A value < 1 means 1.
range	the search range. A value <= 0 or constant `DBL_MAX` mean maximum range.
max_threads	the maximum number of threads to be used.

Returns: an object with the configuration of a similarity search.

static IndexParams mknn::PredefIndex::SnakeTable_indexParams ( long long num_pivots )

static

Resolves searches using a Snake Table.

In order to obtain the exact nearest neighbors, the distance dist_factory must satisfy the metric properties, otherwise the exact search will be incorrect.

Parameters

num_pivots Amount of pivots to store in memory.

Returns: the new index (must be released with delete)

static ResolverParams mknn::PredefIndex::SnakeTable_resolverExactNearestNeighbors	(	long long	knn,
		double	range,
		long long	max_threads
	)

static

Creates a new resolver for exact search using the SnakeTable index.

Parameters

knn	number of nearest neighbors to return. A value < 1 means 1.
range	the search range. A value <= 0 or constant `DBL_MAX` mean maximum range.
max_threads	the maximum number of threads to be used.

Returns: an object with the configuration of a similarity search.

static bool mknn::PredefIndex::testIndexId ( std::string id_index )

static

Tests whether the given string references a valid pre-defined index.

Parameters

id_index the unique identifier of a pre-defined index.

Returns: true whether id_index corresponds to a pre-defined index, and false otherwise.

The documentation for this class was generated from the following file:

src/metricknn/metricknn_cpp/mknn_predefined_index.hpp

Static Public Member Functions

Detailed Description

Member Function Documentation