de.lmu.ifi.dbs.elki.distance.distancefunction.subspace
Class DimensionsSelectingEuclideanDistanceFunction<V extends NumberVector<V,?>>

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,DoubleDistance>
                  de.lmu.ifi.dbs.elki.distance.distancefunction.AbstractDoubleDistanceFunction<V>
                      de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.AbstractDimensionsSelectingDoubleDistanceFunction<V>
                          de.lmu.ifi.dbs.elki.distance.distancefunction.subspace.DimensionsSelectingEuclideanDistanceFunction<V>

Type Parameters:

V - the type of NumberVector to compute the distances in between

All Implemented Interfaces:

DistanceFunction<V,DoubleDistance>, MeasurementFunction<V,DoubleDistance>, SpatialDistanceFunction<V,DoubleDistance>, Parameterizable

public class DimensionsSelectingEuclideanDistanceFunction<V extends NumberVector<V,?>>
extends AbstractDimensionsSelectingDoubleDistanceFunction<V>
implements SpatialDistanceFunction<V,DoubleDistance>

Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions.

Author:

Elke Achtert

Field Summary

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

DIMS_ID

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, logger

Constructor Summary

DimensionsSelectingEuclideanDistanceFunction()
Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions

Method Summary

DoubleDistance	centerDistance(HyperBoundingBox mbr1, HyperBoundingBox mbr2) Computes the distance between the centroids of the two given MBRs according to this distance function.
DoubleDistance	distance(HyperBoundingBox mbr1, HyperBoundingBox mbr2) Computes the distance between the two given MBRs according to this distance function.
DoubleDistance	distance(V v1, V v2) Provides the Euclidean distance between two given feature vectors in the selected dimensions.
DoubleDistance	minDist(HyperBoundingBox mbr, Integer id) Computes the minimum distance between the given MBR and the FeatureVector object with the given id according to this distance function.
DoubleDistance	minDist(HyperBoundingBox mbr, V v) Computes the minimum distance between the given MBR and the FeatureVector object according to this distance function.
String	shortDescription() Returns the required input pattern.

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

getSelectedDimensions, setParameters, setSelectedDimensions

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

infiniteDistance, nullDistance, undefinedDistance, valueOf

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, setDatabase, setRequiredInputPattern

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

addOption, addParameterizable, addParameterizable, checkGlobalParameterConstraints, collectOptions, getAttributeSettings, getParameters, rememberParametersExcept, removeOption, removeParameterizable

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

debugFine, debugFiner, debugFinest, exception, progress, 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.distancefunction.DistanceFunction

distance, distance

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

infiniteDistance, isInfiniteDistance, isNullDistance, isUndefinedDistance, nullDistance, requiredInputPattern, setDatabase, undefinedDistance, valueOf

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

checkGlobalParameterConstraints, collectOptions, getParameters, setParameters

Constructor Detail

DimensionsSelectingEuclideanDistanceFunction

public DimensionsSelectingEuclideanDistanceFunction()

Provides a distance function that computes the Euclidean distance between feature vectors only in specified dimensions

Method Detail

distance

public DoubleDistance distance(V v1,
                               V v2)

Provides the Euclidean distance between two given feature vectors in the selected dimensions.

Specified by:

distance in interface DistanceFunction<V extends NumberVector<V,?>,DoubleDistance>

Parameters:

v1 - first feature vector

v2 - second feature vector

Returns:

the Euclidean distance between two given feature vectors in the selected dimensions

shortDescription

public String shortDescription()

Description copied from class: AbstractMeasurementFunction

Returns the required input pattern.

Specified by:

shortDescription in interface Parameterizable

Overrides:

shortDescription in class AbstractMeasurementFunction<V extends NumberVector<V,?>,DoubleDistance>

Returns:

Description of the class

minDist

public DoubleDistance minDist(HyperBoundingBox mbr,
                              V v)

Description copied from interface: SpatialDistanceFunction

Computes the minimum distance between the given MBR and the FeatureVector object according to this distance function.

Specified by:

minDist in interface SpatialDistanceFunction<V extends NumberVector<V,?>,DoubleDistance>

Parameters:

mbr - the MBR object

v - the FeatureVector object

Returns:

the minimum distance between the given MBR and the FeatureVector object according to this distance function

minDist

public DoubleDistance minDist(HyperBoundingBox mbr,
                              Integer id)

Description copied from interface: SpatialDistanceFunction

Computes the minimum distance between the given MBR and the FeatureVector object with the given id according to this distance function.

Specified by:

minDist in interface SpatialDistanceFunction<V extends NumberVector<V,?>,DoubleDistance>

Parameters:

mbr - the MBR object

id - the id of the FeatureVector object

Returns:

the minimum distance between the given MBR and the FeatureVector object according to this distance function

distance

public DoubleDistance distance(HyperBoundingBox mbr1,
                               HyperBoundingBox mbr2)

Description copied from interface: SpatialDistanceFunction

Computes the distance between the two given MBRs according to this distance function.

Specified by:

distance in interface SpatialDistanceFunction<V extends NumberVector<V,?>,DoubleDistance>

Parameters:

mbr1 - the first MBR object

mbr2 - the second MBR object

Returns:

the distance between the two given MBRs according to this distance function

centerDistance

public DoubleDistance centerDistance(HyperBoundingBox mbr1,
                                     HyperBoundingBox mbr2)

Description copied from interface: SpatialDistanceFunction

Computes the distance between the centroids of the two given MBRs according to this distance function.

Specified by:

centerDistance in interface SpatialDistanceFunction<V extends NumberVector<V,?>,DoubleDistance>

Parameters:

mbr1 - the first MBR object

mbr2 - the second MBR object

Returns:

the distance between the centroids of the two given MBRs according to this distance function