Package elki.index.tree.spatial.rstarvariants.strategies.bulk

Class AdaptiveSortTileRecursiveBulkSplit

java.lang.Object

elki.index.tree.spatial.rstarvariants.strategies.bulk.AbstractBulkSplit

elki.index.tree.spatial.rstarvariants.strategies.bulk.AdaptiveSortTileRecursiveBulkSplit

All Implemented Interfaces:

BulkSplit

public class AdaptiveSortTileRecursiveBulkSplit
extends AbstractBulkSplit

This is variation of the original STR bulk load for non-rectangular data spaces. Instead of iterating through the dimensions and splitting each by (approximately) the same factor, this variation tries to adjust the factor to the extends of the data space. I.e. if the data set is twice as wide as high, this should produce twice as many partitions on the X than on the Y axis. Whether or not this offers benefits greatly depends on the distance queries used. But for symmetric distances, the resulting pages should be more rectangular, which often is beneficial. See SortTileRecursiveBulkSplit for the original STR bulk load.

Since:

0.6.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	AdaptiveSortTileRecursiveBulkSplit.Par	Parameterization class.

Field Summary

Fields

Modifier and Type	Field	Description
static AdaptiveSortTileRecursiveBulkSplit	STATIC	Static instance.

Constructor Summary

Constructors

Constructor	Description
AdaptiveSortTileRecursiveBulkSplit()

Method Summary

Modifier and Type	Method	Description
<T extends elki.data.spatial.SpatialComparable> java.util.List<java.util.List<T>>	partition(java.util.List<T> spatialObjects, int minEntries, int maxEntries)	Partitions the specified feature vectors
protected <T extends elki.data.spatial.SpatialComparable> void	strPartition(java.util.List<T> objs, int start, int end, int depth, int dims, int maxEntries, elki.data.spatial.SpatialSingleMeanComparator c, java.util.List<java.util.List<T>> ret)	Recursively partition.

Methods inherited from class elki.index.tree.spatial.rstarvariants.strategies.bulk.AbstractBulkSplit

chooseBulkSplitPoint, trivialPartition

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

STATIC

public static final AdaptiveSortTileRecursiveBulkSplit STATIC

Static instance.

Constructor Detail

AdaptiveSortTileRecursiveBulkSplit

public AdaptiveSortTileRecursiveBulkSplit()

Method Detail

partition

public <T extends elki.data.spatial.SpatialComparable> java.util.List<java.util.List<T>> partition(java.util.List<T> spatialObjects,
                                                                                                   int minEntries,
                                                                                                   int maxEntries)

Description copied from interface: BulkSplit

Partitions the specified feature vectors

Type Parameters:

T - actual type we split

Parameters:

spatialObjects - the spatial objects to be partitioned

minEntries - the minimum number of entries in a partition

maxEntries - the maximum number of entries in a partition

Returns:

the partition of the specified spatial objects

strPartition

protected <T extends elki.data.spatial.SpatialComparable> void strPartition(java.util.List<T> objs,
                                                                            int start,
                                                                            int end,
                                                                            int depth,
                                                                            int dims,
                                                                            int maxEntries,
                                                                            elki.data.spatial.SpatialSingleMeanComparator c,
                                                                            java.util.List<java.util.List<T>> ret)

Recursively partition.

Type Parameters:

T - data type

Parameters:

objs - Object list

start - Subinterval start

end - Subinterval end

depth - Iteration depth (must be less than dimensionality!)

dims - Total number of dimensions

maxEntries - Maximum page size

c - Comparison helper

ret - Output list