de.lmu.ifi.dbs.elki.distance.distancefunction
Class PCABasedCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>>

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable
          de.lmu.ifi.dbs.elki.distance.AbstractMeasurementFunction<O,D>
              de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDistanceFunction<O,D>
                  de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPreprocessorBasedDistanceFunction<O,P,D>
                      de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractCorrelationDistanceFunction<O,P,D>
                          de.lmu.ifi.dbs.elki.distance.distancefunction.PCABasedCorrelationDistanceFunction<O,P,D>

All Implemented Interfaces:

DistanceFunction<O,D>, MeasurementFunction<O,D>, Loggable, Parameterizable

public class PCABasedCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>>
extends AbstractCorrelationDistanceFunction<O,P,D>

Provides the Correlation distance for real valued vectors.

Author:

Elke Achtert

Field Summary

static AssociationID	ASSOCIATION_ID The Assocoiation ID for the association to be set by the preprocessor.
static double	DEFAULT_DELTA The default value for delta.
static String	DEFAULT_PREPROCESSOR_CLASS The default preprocessor class name.
private double	delta The threshold of a distance between a vector q and a given space that indicates that q adds a new dimension to the space.
static String	DELTA_D Description for parameter delta.
static String	DELTA_P Option string for parameter delta.
static String	PREPROCESSOR_CLASS_D Description for parameter preprocessor.
static Class<HiCOPreprocessor>	PREPROCESSOR_SUPER_CLASS The super class for the preprocessor.

Fields inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractCorrelationDistanceFunction

SEPARATOR

Fields inherited from class de.lmu.ifi.dbs.elki.distance.AbstractMeasurementFunction

INFINITY_PATTERN

Fields inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable

optionHandler

Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debug

Constructor Summary

PCABasedCorrelationDistanceFunction()
Provides a CorrelationDistanceFunction with a pattern defined to accept Strings that define an Integer followed by a separator followed by a Double.

Method Summary

private void	adjust(Matrix v, Matrix e_czech, Matrix vector, int corrDim) Inserts the specified vector into the given orthonormal matrix v at column corrDim.
int	correlationDistance(LocalPCA<O> pca1, LocalPCA<O> pca2, int dimensionality) Computes the correlation distance between the two subspaces defined by the specified PCAs.
(package private) D	correlationDistance(O dv1, O dv2) Computes the correlation distance between the two specified vectors.
private double	euclideanDistance(O dv1, O dv2) Computes the Euklidean distance between the given two vectors.
(package private) AssociationID	getAssociationID() Returns the assocoiation ID for the association to be set by the preprocessor.
(package private) String	getDefaultPreprocessorClassName() Returns the name of the default preprocessor.
(package private) String	getPreprocessorClassDescription() Returns the description for parameter preprocessor.
(package private) Class<HiCOPreprocessor>	getPreprocessorSuperClassName() Returns the super class for the preprocessor.
D	infiniteDistance() Provides an infinite distance.
D	nullDistance() Provides a null distance.
String[]	setParameters(String[] args) Sets the values for the parameters delta and preprocessor if specified.
D	undefinedDistance() Provides an undefined distance.
D	valueOf(String pattern) Provides a distance suitable to this DistanceFunction based on the given pattern.

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractCorrelationDistanceFunction

description, distance

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractPreprocessorBasedDistanceFunction

getAttributeSettings, getPreprocessor, setDatabase

Methods inherited from class de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDistanceFunction

distance, distance, isInfiniteDistance, isNullDistance, isUndefinedDistance

Methods inherited from class de.lmu.ifi.dbs.elki.distance.AbstractMeasurementFunction

getDatabase, matches, requiredInputPattern, setRequiredInputPattern

Methods inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable

addOption, checkGlobalParameterConstraints, deleteOption, description, description, getParameters, getParameterValue, getPossibleOptions, inlineDescription, isSet, setParameters

Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debugFine, debugFiner, debugFinest, exception, message, progress, progress, progress, verbose, verbose, warning

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.distance.MeasurementFunction

requiredInputPattern

Methods inherited from interface de.lmu.ifi.dbs.elki.utilities.optionhandling.Parameterizable

checkGlobalParameterConstraints, getParameters, getPossibleOptions, inlineDescription

Field Detail

ASSOCIATION_ID

public static final AssociationID ASSOCIATION_ID

The Assocoiation ID for the association to be set by the preprocessor.

PREPROCESSOR_SUPER_CLASS

public static final Class<HiCOPreprocessor> PREPROCESSOR_SUPER_CLASS

The super class for the preprocessor.

DEFAULT_PREPROCESSOR_CLASS

public static final String DEFAULT_PREPROCESSOR_CLASS

The default preprocessor class name.

PREPROCESSOR_CLASS_D

public static final String PREPROCESSOR_CLASS_D

Description for parameter preprocessor.

DEFAULT_DELTA

public static final double DEFAULT_DELTA

The default value for delta.

See Also:

Constant Field Values

DELTA_P

public static final String DELTA_P

Option string for parameter delta.

See Also:

Constant Field Values

DELTA_D

public static final String DELTA_D

Description for parameter delta.

See Also:

Constant Field Values

delta

private double delta

The threshold of a distance between a vector q and a given space that indicates that q adds a new dimension to the space.

Constructor Detail

PCABasedCorrelationDistanceFunction

public PCABasedCorrelationDistanceFunction()

Provides a CorrelationDistanceFunction with a pattern defined to accept Strings that define an Integer followed by a separator followed by a Double.

Method Detail

setParameters

public String[] setParameters(String[] args)
                       throws ParameterException

Sets the values for the parameters delta and preprocessor if specified. If the parameters are not specified default values are set.

Specified by:

setParameters in interface Parameterizable

Overrides:

setParameters in class AbstractPreprocessorBasedDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>>

Parameters:

args - parameters to set the attributes accordingly to

Returns:

String[] an array containing the unused parameters

Throws:

ParameterException - in case of wrong parameter-setting

See Also:

Parameterizable.setParameters(String[])

valueOf

public D valueOf(String pattern)
                                         throws IllegalArgumentException

Provides a distance suitable to this DistanceFunction based on the given pattern.

Parameters:

pattern - A pattern defining a distance suitable to this DistanceFunction

Returns:

a distance suitable to this DistanceFunction based on the given pattern

Throws:

IllegalArgumentException - if the given pattern is not compatible with the requirements of this DistanceFunction

infiniteDistance

public D infiniteDistance()

Provides an infinite distance.

Returns:

an infinite distance

nullDistance

public D nullDistance()

Provides a null distance.

Returns:

a null distance

undefinedDistance

public D undefinedDistance()

Provides an undefined distance.

Returns:

an undefined distance

correlationDistance

D correlationDistance(O dv1,
                      O dv2)

Description copied from class: AbstractCorrelationDistanceFunction

Computes the correlation distance between the two specified vectors.

Specified by:

correlationDistance in class AbstractCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>>

Parameters:

dv1 - first RealVector

dv2 - second RealVector

Returns:

the correlation distance between the two specified vectors

See Also:

AbstractCorrelationDistanceFunction.correlationDistance(de.lmu.ifi.dbs.elki.data.RealVector, de.lmu.ifi.dbs.elki.data.RealVector)

correlationDistance

public int correlationDistance(LocalPCA<O> pca1,
                               LocalPCA<O> pca2,
                               int dimensionality)

Computes the correlation distance between the two subspaces defined by the specified PCAs.

Parameters:

pca1 - first PCA

pca2 - second PCA

dimensionality - the dimensionality of the data space

Returns:

the correlation distance between the two subspaces defined by the specified PCAs

adjust

private void adjust(Matrix v,
                    Matrix e_czech,
                    Matrix vector,
                    int corrDim)

Inserts the specified vector into the given orthonormal matrix v at column corrDim. After insertion the matrix v is orthonormalized and column corrDim of matrix e_czech is set to the corrDim-th unit vector..

Parameters:

v - the orthonormal matrix of the eigenvectors

e_czech - the selection matrix of the strong eigenvectors

vector - the vector to be inserted

corrDim - the column at which the vector should be inserted

euclideanDistance

private double euclideanDistance(O dv1,
                                 O dv2)

Computes the Euklidean distance between the given two vectors.

Parameters:

dv1 - first NumberVector

dv2 - second NumberVector

Returns:

the Euklidean distance between the given two vectors

getDefaultPreprocessorClassName

String getDefaultPreprocessorClassName()

Returns the name of the default preprocessor.

Specified by:

getDefaultPreprocessorClassName in class AbstractCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>>

getPreprocessorClassDescription

String getPreprocessorClassDescription()

Returns the description for parameter preprocessor.

Specified by:

getPreprocessorClassDescription in class AbstractCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>>

getPreprocessorSuperClassName

Class<HiCOPreprocessor> getPreprocessorSuperClassName()

Returns the super class for the preprocessor.

Specified by:

getPreprocessorSuperClassName in class AbstractCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>>

getAssociationID

AssociationID getAssociationID()

Returns the assocoiation ID for the association to be set by the preprocessor.

Specified by:

getAssociationID in class AbstractCorrelationDistanceFunction<O extends RealVector<O,?>,P extends Preprocessor<O>,D extends CorrelationDistance<D>>