de.lmu.ifi.dbs.elki.data
Class SparseDoubleVector

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.data.AbstractDatabaseObject
          de.lmu.ifi.dbs.elki.data.NumberVector<V,N>
              de.lmu.ifi.dbs.elki.data.RealVector<SparseDoubleVector,Double>
                  de.lmu.ifi.dbs.elki.data.SparseDoubleVector

All Implemented Interfaces:

WekaObject<WekaNumericAttribute>, DatabaseObject, FeatureVector<SparseDoubleVector,Double>, SpatialComparable, SpatialObject, Loggable

public class SparseDoubleVector
extends RealVector<SparseDoubleVector,Double>

A SparseDoubleVector is to store real values approximately as double values.

Class for storing a DoubleVector as a sparse vector. A SparseDoubleVector only requires storage for those attribute values that are non-zero.

Author:

Elke Achtert

Field Summary

private int	dimensionality The dimensionality of this feature vector.
private Map<Integer,Double>	values Mapping of indices and corresponding values.

Fields inherited from class de.lmu.ifi.dbs.elki.data.NumberVector

ATTRIBUTE_SEPARATOR

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

debug

Constructor Summary

SparseDoubleVector(double[] values)
Provides a SparseDoubleVector consisting of double values according to the specified mapping of indices and values.

SparseDoubleVector(Map<Integer,Double> values, int dimensionality)
Provides a SparseDoubleVector consisting of double values according to the specified mapping of indices and values.

Method Summary

Vector	getColumnVector() Returns a Vector representing in one column and getDimensionality() rows the values of this FeatureVector.
int	getDimensionality() The dimensionality of the vector space whereof this FeatureVector is an element.
Matrix	getRowVector() Returns a Matrix representing in one row and getDimensionality() columns the values of this FeatureVector.
Double	getValue(int dimension) Returns the value in the specified dimension.
private double[]	getValues() Returns an array consisting of the values of this feature vector.
SparseDoubleVector	multiplicate(double k) Returns a new FeatureVector that is the result of a scalar multiplication with the given scalar.
SparseDoubleVector	negativeVector() Returns the additive inverse to this FeatureVector.
SparseDoubleVector	newInstance(double[] values) Returns a new RealVector of N for the given values.
SparseDoubleVector	nullVector() Provides a null vector of the same Feature Vector Space as this FeatureVector (that is, of the same dimensionality).
SparseDoubleVector	plus(SparseDoubleVector fv) Returns a new FeatureVector that is the sum of this FeatureVector and the given FeatureVector.
SparseDoubleVector	randomInstance(Double min, Double max, Random random) Returns a FeatureVector of T with random values between min and max.
SparseDoubleVector	randomInstance(Random random) Returns a FeatureVector of T with uniformly distributed (0-1) random values.
String	toString() Returns a String representation of the FeatureVector as a line that is suitable to be printed in a sequential file.

Methods inherited from class de.lmu.ifi.dbs.elki.data.NumberVector

equals, getAttributes, getMax, getMin, newInstance

Methods inherited from class de.lmu.ifi.dbs.elki.data.AbstractDatabaseObject

getID, setID

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, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface de.lmu.ifi.dbs.elki.data.DatabaseObject

getID, setID

Methods inherited from interface de.lmu.ifi.dbs.elki.index.tree.spatial.SpatialObject

getID

Field Detail

values

private Map<Integer,Double> values

Mapping of indices and corresponding values. Only non-zero values will to be stored.

dimensionality

private final int dimensionality

The dimensionality of this feature vector.

Constructor Detail

SparseDoubleVector

public SparseDoubleVector(Map<Integer,Double> values,
                          int dimensionality)

Provides a SparseDoubleVector consisting of double values according to the specified mapping of indices and values.

Parameters:

values - the values to be set as values of the real vector

dimensionality - the dimensionality of this feature vector

SparseDoubleVector

public SparseDoubleVector(double[] values)

Provides a SparseDoubleVector consisting of double values according to the specified mapping of indices and values.

Parameters:

values - the values to be set as values of the real vector

Method Detail

newInstance

public SparseDoubleVector newInstance(double[] values)

Description copied from class: RealVector

Returns a new RealVector of N for the given values.

Specified by:

newInstance in class RealVector<SparseDoubleVector,Double>

Parameters:

values - the values of the featureVector

Returns:

a new FeatureVector of T for the given values

See Also:

RealVector.newInstance(double[])

randomInstance

public SparseDoubleVector randomInstance(Random random)

Description copied from interface: FeatureVector

Returns a FeatureVector of T with uniformly distributed (0-1) random values.

Parameters:

random - a Random instance

Returns:

a FeatureVector of T with random values

See Also:

FeatureVector.randomInstance(java.util.Random)

randomInstance

public SparseDoubleVector randomInstance(Double min,
                                         Double max,
                                         Random random)

Description copied from interface: FeatureVector

Returns a FeatureVector of T with random values between min and max.

Parameters:

min - minimum of random value

max - maximu of random value

random - a random instance

Returns:

a FeatureVector of T with random values between min and max

See Also:

FeatureVector.randomInstance(Number, Number, java.util.Random)

getDimensionality

public int getDimensionality()

Description copied from interface: FeatureVector

The dimensionality of the vector space whereof this FeatureVector is an element.

Returns:

the number of dimensions of this FeatureVector

See Also:

FeatureVector.getDimensionality()

getValue

public Double getValue(int dimension)

Description copied from interface: FeatureVector

Returns the value in the specified dimension.

Parameters:

dimension - the desired dimension, where 1 ≤ dimension ≤ this.getDimensionality()

Returns:

the value in the specified dimension

See Also:

FeatureVector.getValue(int)

getColumnVector

public Vector getColumnVector()

Description copied from interface: FeatureVector

Returns a Vector representing in one column and getDimensionality() rows the values of this FeatureVector.

Returns:

a Matrix representing in one column and getDimensionality() rows the values of this FeatureVector

See Also:

FeatureVector.getColumnVector()

getRowVector

public Matrix getRowVector()

Description copied from interface: FeatureVector

Returns a Matrix representing in one row and getDimensionality() columns the values of this FeatureVector.

Returns:

a Matrix representing in one row and getDimensionality() columns the values of this FeatureVector

See Also:

FeatureVector.getRowVector()

plus

public SparseDoubleVector plus(SparseDoubleVector fv)

Description copied from interface: FeatureVector

Returns a new FeatureVector that is the sum of this FeatureVector and the given FeatureVector.

Parameters:

fv - a FeatureVector to be added to this Featurevector

Returns:

a new FeatureVector that is the sum of this FeatureVector and the given FeatureVector

See Also:

FeatureVector.plus(FeatureVector)

nullVector

public SparseDoubleVector nullVector()

Description copied from interface: FeatureVector

Provides a null vector of the same Feature Vector Space as this FeatureVector (that is, of the same dimensionality).

Returns:

a null vector of the same Feature Vector Space as this FeatureVector (that is, of the same dimensionality)

See Also:

FeatureVector.nullVector()

negativeVector

public SparseDoubleVector negativeVector()

Description copied from interface: FeatureVector

Returns the additive inverse to this FeatureVector.

Returns:

the additive inverse to this FeatureVector

See Also:

FeatureVector.negativeVector()

multiplicate

public SparseDoubleVector multiplicate(double k)

Description copied from interface: FeatureVector

Returns a new FeatureVector that is the result of a scalar multiplication with the given scalar.

Parameters:

k - a scalar to multiply this FeatureVector with

Returns:

a new FeatureVector that is the result of a scalar multiplication with the given scalar

See Also:

FeatureVector.multiplicate(double)

toString

public String toString()

Description copied from interface: FeatureVector

Returns a String representation of the FeatureVector as a line that is suitable to be printed in a sequential file.

Specified by:

toString in interface FeatureVector<SparseDoubleVector,Double>

Overrides:

toString in class Object

Returns:

a String representation of the FeatureVector

See Also:

FeatureVector.toString()

getValues

private double[] getValues()

Returns an array consisting of the values of this feature vector.

Returns:

an array consisting of the values of this feature vector