de.lmu.ifi.dbs.elki.normalization
Class AttributeWiseRealVectorNormalization<V extends RealVector<V,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable
          de.lmu.ifi.dbs.elki.normalization.AbstractNormalization<V>
              de.lmu.ifi.dbs.elki.normalization.AttributeWiseRealVectorNormalization<V>

All Implemented Interfaces:

Loggable, Normalization<V>, Parameterizable

public class AttributeWiseRealVectorNormalization<V extends RealVector<V,?>>
extends AbstractNormalization<V>

Class to perform and undo a normalization on real vectors with respect to given minimum and maximum in each dimension.

Author:

Elke Achtert

Field Summary

private double[]	maxima Stores the maximum in each dimension.
static String	MAXIMA_D Description for parameter minima.
static String	MAXIMA_P Parameter for maxima.
private double[]	minima Stores the minimum in each dimension.
static String	MINIMA_D Description for parameter minima.
static String	MINIMA_P Parameter for minima.

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

AttributeWiseRealVectorNormalization()
Sets minima and maxima parameter to the optionhandler.

Method Summary

String	description() Returns a description of the class and the required parameters.
private void	determineMinMax(List<ObjectAndAssociations<V>> objectAndAssociationsList) Determines the minima and maxima values in each dimension of the given featureVectors.
private void	determineMinMax(V[] featureVectors) Determines the minima and maxima values in each dimension of the given featureVectors.
private double	factor(int dimension) Returns a factor for normalization in a certain dimension.
List<AttributeSettings>	getAttributeSettings() Returns the settings of all options assigned to the option handler.
private void	initMinMax(int dimensionality) Initializes the min and max array.
List<V>	normalize(List<V> featureVectors) Performs a normalization on a set of feature vectors.
List<ObjectAndAssociations<V>>	normalizeObjects(List<ObjectAndAssociations<V>> objectAndAssociationsList) Performs a normalization on a list of database objects and their associations.
List<V>	restore(List<V> featureVectors) Transforms a set of feature vectores to the original attribute ranges.
V	restore(V featureVector) Transforms a feature vector to the original attribute ranges.
String[]	setParameters(String[] args) Sets the attributes of the class accordingly to the given parameters.
String	toString(String pre) Returns a string representation of this normalization.
LinearEquationSystem	transform(LinearEquationSystem linearEquationSystem) Transforms a linear equation system describing linear dependencies derived on the normalized space into a linear equation system describing linear dependencies quantitatively adapted to the original space.
private void	updateMinMax(V featureVector) Updates the min and max array according to the specified feature vector.

Methods inherited from class de.lmu.ifi.dbs.elki.normalization.AbstractNormalization

toString

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, wait, wait, wait

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

checkGlobalParameterConstraints, getParameters, getPossibleOptions, inlineDescription

Field Detail

MINIMA_P

public static final String MINIMA_P

Parameter for minima.

See Also:

Constant Field Values

MINIMA_D

public static final String MINIMA_D

Description for parameter minima.

See Also:

Constant Field Values

MAXIMA_P

public static final String MAXIMA_P

Parameter for maxima.

See Also:

Constant Field Values

MAXIMA_D

public static final String MAXIMA_D

Description for parameter minima.

See Also:

Constant Field Values

maxima

private double[] maxima

Stores the maximum in each dimension.

minima

private double[] minima

Stores the minimum in each dimension.

Constructor Detail

AttributeWiseRealVectorNormalization

public AttributeWiseRealVectorNormalization()

Sets minima and maxima parameter to the optionhandler.

Method Detail

normalizeObjects

public List<ObjectAndAssociations<V>> normalizeObjects(List<ObjectAndAssociations<V>> objectAndAssociationsList)
                                                                        throws NonNumericFeaturesException

Description copied from interface: Normalization

Performs a normalization on a list of database objects and their associations.

Parameters:

objectAndAssociationsList - the list of database objects and their associations

Returns:

a list of normalized database objects and their associations corresponding to the given list

Throws:

NonNumericFeaturesException - if feature vectors differ in length or values are not suitable to normalization

See Also:

Normalization.normalizeObjects(java.util.List)

normalize

public List<V> normalize(List<V> featureVectors)
                                          throws NonNumericFeaturesException

Description copied from interface: Normalization

Performs a normalization on a set of feature vectors.

Parameters:

featureVectors - a set of feature vectors to be normalized

Returns:

a set of normalized feature vectors corresponding to the given feature vectors but being different objects

Throws:

NonNumericFeaturesException - if feature vectors differ in length or values are not suitable to normalization

See Also:

Normalization.normalize(java.util.List)

restore

public V restore(V featureVector)
                                  throws NonNumericFeaturesException

Description copied from interface: Normalization

Transforms a feature vector to the original attribute ranges.

Parameters:

featureVector - a feature vector to be transformed into original space

Returns:

a feature vector transformed into original space corresponding to the given feature vector

Throws:

NonNumericFeaturesException - feature vector is not compatible with values initialized during normalization

See Also:

Normalization.restore(de.lmu.ifi.dbs.elki.data.DatabaseObject)

restore

public List<V> restore(List<V> featureVectors)
                                        throws NonNumericFeaturesException

Description copied from interface: Normalization

Transforms a set of feature vectores to the original attribute ranges.

Parameters:

featureVectors - a set of feature vectors to be transformed into original space

Returns:

a set of feature vectors transformed into original space corresponding to the given feature vectors

Throws:

NonNumericFeaturesException - if feature vectors differ in length or are not compatible with values initialized during normalization

See Also:

Normalization.restore(java.util.List)

transform

public LinearEquationSystem transform(LinearEquationSystem linearEquationSystem)
                               throws NonNumericFeaturesException

Description copied from interface: Normalization

Transforms a linear equation system describing linear dependencies derived on the normalized space into a linear equation system describing linear dependencies quantitatively adapted to the original space.

Parameters:

linearEquationSystem - the linear equation system to be transformed

Returns:

a linear equation system describing linear dependencies derived on the normalized space transformed into a linear equation system describing linear dependencies quantitatively adapted to the original space

Throws:

NonNumericFeaturesException - if specified linear equation system is not compatible with values initialized during normalization

See Also:

Normalization.transform(de.lmu.ifi.dbs.elki.math.linearalgebra.LinearEquationSystem)

toString

public String toString(String pre)

Returns a string representation of this normalization. The specified prefix pre will be the prefix of each new line. This method is used to write the parameters of a normalization to a result of an algorithm using this normalization.

Parameters:

pre - the prefix of each new line

Returns:

a string representation of this normalization

description

public String description()

Returns a description of the class and the required parameters.

This description should be suitable for a usage description.

Specified by:

description in interface Parameterizable

Overrides:

description in class AbstractParameterizable

Returns:

String a description of the class and the required parameters

See Also:

Parameterizable.description()

setParameters

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

Sets the attributes of the class accordingly to the given parameters. Returns a new String array containing those entries of the given array that are neither expected nor used by this Parameterizable.

Specified by:

setParameters in interface Parameterizable

Overrides:

setParameters in class AbstractParameterizable

Parameters:

args - parameters to set the attributes accordingly to

Returns:

String[] an array containing the unused parameters

Throws:

IllegalArgumentException - in case of wrong parameter-setting

ParameterException - in case of wrong parameter-setting

See Also:

Parameterizable.setParameters(String[])

getAttributeSettings

public List<AttributeSettings> getAttributeSettings()

Description copied from class: AbstractParameterizable

Returns the settings of all options assigned to the option handler.

Specified by:

getAttributeSettings in interface Parameterizable

Overrides:

getAttributeSettings in class AbstractParameterizable

Returns:

the setting of the attributes of the parameterizable

See Also:

Parameterizable.getAttributeSettings()

factor

private double factor(int dimension)

Returns a factor for normalization in a certain dimension.

The provided factor is the maximum-minimum in the specified dimension, if these two values differ, otherwise it is the maximum if this value differs from 0, otherwise it is 1.

Parameters:

dimension - the dimension to get a factor for normalization

Returns:

a factor for normalization in a certain dimension

determineMinMax

private void determineMinMax(V[] featureVectors)

Determines the minima and maxima values in each dimension of the given featureVectors.

Parameters:

featureVectors - the list of feature vectors

determineMinMax

private void determineMinMax(List<ObjectAndAssociations<V>> objectAndAssociationsList)

Determines the minima and maxima values in each dimension of the given featureVectors.

Parameters:

objectAndAssociationsList - the list of feature vectors and their associtions

initMinMax

private void initMinMax(int dimensionality)

Initializes the min and max array.

Parameters:

dimensionality - the dimensionality of the feature vectors to be normalized

updateMinMax

private void updateMinMax(V featureVector)

Updates the min and max array according to the specified feature vector.

Parameters:

featureVector - the feature vector