de.lmu.ifi.dbs.elki.index.distancematrix

Class PrecomputedSimilarityMatrix<O>

java.lang.Object

de.lmu.ifi.dbs.elki.index.AbstractIndex<O>

de.lmu.ifi.dbs.elki.index.distancematrix.PrecomputedSimilarityMatrix<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Index, SimilarityIndex<O>, SimilarityRangeIndex<O>, Result

public class PrecomputedSimilarityMatrix<O>
extends AbstractIndex<O>
implements SimilarityIndex<O>, SimilarityRangeIndex<O>

Precomputed similarity matrix, for a small data set.

This class uses a linear memory layout (not a ragged array), and assumes symmetry as well as strictness. This way, it only stores the upper triangle matrix with double precision. It has to store (n-1) * (n-2) similarity values in memory, requiring 8 * (n-1) * (n-2) bytes. Since Java has a size limit of arrays of 31 bits (signed integer), we can store at most \(2^16\) objects (precisely, 65536 objects) in a single array, which needs about 16 GB of RAM.

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	PrecomputedSimilarityMatrix.Factory<O> Factory for the index.
private class	PrecomputedSimilarityMatrix.PrecomputedSimilarityQuery Similarity query using the precomputed matrix.
private class	PrecomputedSimilarityMatrix.PrecomputedSimilarityRangeQuery Range query using the distance matrix.

Field Summary

Fields

Modifier and Type	Field and Description
private DBIDRange	ids DBID range.
private static Logging	LOG Class logger.
private double[]	matrix Similarity matrix.
protected SimilarityFunction<? super O>	similarityFunction Nested similarity function.
protected SimilarityQuery<O>	similarityQuery Nested similarity query.
private int	size Size of DBID range.

Fields inherited from class de.lmu.ifi.dbs.elki.index.AbstractIndex

relation

Constructor Summary

Constructors

Constructor and Description
PrecomputedSimilarityMatrix(Relation<O> relation, SimilarityFunction<? super O> similarityFunction) Constructor.

Method Summary

Modifier and Type	Method and Description
java.lang.String	getLongName() A "pretty" name for the result, for use in titles, captions and menus.
private int	getOffset(int x, int y) Array offset computation.
java.lang.String	getShortName() A short name for the result, useful for file names.
SimilarityQuery<O>	getSimilarityQuery(SimilarityFunction<? super O> similarityFunction, java.lang.Object... hints) Get a similarity query object for the given similarity function.
RangeQuery<O>	getSimilarityRangeQuery(SimilarityQuery<O> simQuery, java.lang.Object... hints) Get a range query object for the given distance query and k.
void	initialize() Initialize the index.
void	logStatistics() Send statistics to the logger, if enabled.
protected static int	triangleSize(int x) Compute the size of a complete x by x triangle (minus diagonal)

Methods inherited from class java.lang.Object

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

Field Detail

LOG

private static final Logging LOG

Class logger.

similarityFunction

protected final SimilarityFunction<? super O> similarityFunction

Nested similarity function.

similarityQuery

protected SimilarityQuery<O> similarityQuery

Nested similarity query.

matrix

private double[] matrix

Similarity matrix.

ids

private DBIDRange ids

DBID range.

size

private int size

Size of DBID range.

Constructor Detail

PrecomputedSimilarityMatrix

public PrecomputedSimilarityMatrix(Relation<O> relation,
                                   SimilarityFunction<? super O> similarityFunction)

Constructor.

Parameters:

relation - Data relation

similarityFunction - Similarity function

Method Detail

initialize

public void initialize()

Description copied from interface: Index

Initialize the index. For static indexes, this is the moment the index is bulk loaded.

Specified by:

initialize in interface Index

triangleSize

protected static int triangleSize(int x)

Compute the size of a complete x by x triangle (minus diagonal)

Parameters:

x - Offset

Returns:

Size of complete triangle

getOffset

private int getOffset(int x,
                      int y)

Array offset computation.

Parameters:

x - X parameter

y - Y parameter

Returns:

Array offset

logStatistics

public void logStatistics()

Description copied from interface: Index

Send statistics to the logger, if enabled. Note: you must have set the logging level appropriately before initializing the index! Otherwise, the index might not have collected the desired statistics.

Specified by:

logStatistics in interface Index

getLongName

public java.lang.String getLongName()

Description copied from interface: Result

A "pretty" name for the result, for use in titles, captions and menus.

Specified by:

getLongName in interface Result

Specified by:

getLongName in class AbstractIndex<O>

Returns:

result name

getShortName

public java.lang.String getShortName()

Description copied from interface: Result

A short name for the result, useful for file names.

Specified by:

getShortName in interface Result

Specified by:

getShortName in class AbstractIndex<O>

Returns:

result name

getSimilarityQuery

public SimilarityQuery<O> getSimilarityQuery(SimilarityFunction<? super O> similarityFunction,
                                             java.lang.Object... hints)

Description copied from interface: SimilarityIndex

Get a similarity query object for the given similarity function.

Specified by:

getSimilarityQuery in interface SimilarityIndex<O>

Parameters:

similarityFunction - Similarity function to use.

hints - Hints for the optimizer

Returns:

similarity query object or null

getSimilarityRangeQuery

public RangeQuery<O> getSimilarityRangeQuery(SimilarityQuery<O> simQuery,
                                             java.lang.Object... hints)

Description copied from interface: SimilarityRangeIndex

Get a range query object for the given distance query and k. This function MAY return null, when the given distance is not supported!

Specified by:

getSimilarityRangeQuery in interface SimilarityRangeIndex<O>

Parameters:

simQuery - Similarity query

hints - Hints for the optimizer

Returns:

KNN Query object or null