de.lmu.ifi.dbs.elki.distance.distancefunction
Class ManhattanDistanceFunction<T extends NumberVector<T,?>>

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<T>
                      de.lmu.ifi.dbs.elki.distance.distancefunction.ManhattanDistanceFunction<T>

All Implemented Interfaces:

DistanceFunction<T,DoubleDistance>, MeasurementFunction<T,DoubleDistance>, Loggable, Parameterizable

public class ManhattanDistanceFunction<T extends NumberVector<T,?>>
extends AbstractDoubleDistanceFunction<T>

Manhattan distance function to compute the Manhattan distance for a pair of NumberVectors.

Author:

Arthur Zimek

Field Summary

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

ManhattanDistanceFunction()
Provides a Manhattan distance function that can compute the Manhattan distance (that is a DoubleDistance) for FeatureVectors.

Method Summary

DoubleDistance

distance(T o1, T o2) Computes the distance between two given DatabaseObjects according to this distance function.

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, checkGlobalParameterConstraints, deleteOption, description, description, description, getAttributeSettings, getParameters, getParameterValue, getPossibleOptions, inlineDescription, isSet, setParameters, 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, setDatabase

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

checkGlobalParameterConstraints, description, getAttributeSettings, getParameters, getPossibleOptions, inlineDescription, setParameters

Constructor Detail

ManhattanDistanceFunction

public ManhattanDistanceFunction()

Provides a Manhattan distance function that can compute the Manhattan distance (that is a DoubleDistance) for FeatureVectors.

Method Detail

distance

public DoubleDistance distance(T o1,
                               T o2)

Description copied from interface: DistanceFunction

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

Parameters:

o1 - first DatabaseObject

o2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function

See Also:

DistanceFunction.distance(de.lmu.ifi.dbs.elki.data.DatabaseObject, de.lmu.ifi.dbs.elki.data.DatabaseObject)