de.lmu.ifi.dbs.elki.data

Class SparseDoubleVector

java.lang.Object

de.lmu.ifi.dbs.elki.data.AbstractNumberVector<Double>

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

All Implemented Interfaces:

FeatureVector<Double>, NumberVector<Double>, SparseFeatureVector<Double>, SparseNumberVector<Double>, SpatialComparable

public class SparseDoubleVector
extends AbstractNumberVector<Double>
implements SparseNumberVector<Double>

A SparseDoubleVector is to store real values as double values.

A SparseDoubleVector only requires storage for those attribute values that are non-zero.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SparseDoubleVector.Factory Factory class.

Field Summary

Fields

Modifier and Type	Field and Description
private int	dimensionality The dimensionality of this feature vector.
static gnu.trove.map.TIntDoubleMap	EMPTYMAP Empty map.
static SparseDoubleVector.Factory	FACTORY Static instance.
private int[]	indexes Indexes of values.
private double[]	values Stored values.

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

ATTRIBUTE_SEPARATOR

Constructor Summary

Constructors

Constructor and Description
SparseDoubleVector(double[] values) Provides a SparseDoubleVector consisting of double values according to the specified mapping of indices and values.
SparseDoubleVector(int[] indexes, double[] values, int dimensionality) Direct constructor.
SparseDoubleVector(gnu.trove.map.TIntDoubleMap values, int dimensionality) Provides a SparseDoubleVector consisting of double values according to the specified mapping of indices and values.

Method Summary

Methods

Modifier and Type	Method and Description
double	doubleValue(int dimension) Returns the value in the specified dimension as double.
Vector	getColumnVector() Returns a Vector representing in one column and getDimensionality() rows the values of this NumberVector of V.
int	getDimensionality() The dimensionality of the vector space where of this FeatureVector of V is an element.
private int	getMaxDim() Get the maximum dimensionality.
BitSet	getNotNullMask() Bit set of non-null features.
Double	getValue(int dimension) Deprecated.
private double[]	getValues() Returns an array consisting of the values of this feature vector.
long	longValue(int dimension) Returns the value in the specified dimension as long.
void	setDimensionality(int dimensionality) Sets the dimensionality to the new value.
String	toString() Provides a String representation of this SparseDoubleVector as suitable for SparseNumberVectorLabelParser .

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

byteValue, floatValue, getMax, getMin, intValue, shortValue

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.data.NumberVector

byteValue, floatValue, intValue, shortValue

Methods inherited from interface de.lmu.ifi.dbs.elki.data.spatial.SpatialComparable

getMax, getMin

Field Detail

FACTORY

public static final SparseDoubleVector.Factory FACTORY

Static instance.

indexes

private final int[] indexes

Indexes of values.

values

private final double[] values

Stored values.

dimensionality

private int dimensionality

The dimensionality of this feature vector.

EMPTYMAP

public static final gnu.trove.map.TIntDoubleMap EMPTYMAP

Empty map.

Constructor Detail

SparseDoubleVector

public SparseDoubleVector(int[] indexes,
                  double[] values,
                  int dimensionality)

Direct constructor.

Parameters:

indexes - Indexes Must be sorted!

values - Associated value.

dimensionality - "true" dimensionality

SparseDoubleVector

public SparseDoubleVector(gnu.trove.map.TIntDoubleMap values,
                  int dimensionality)
                   throws IllegalArgumentException

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

Throws:

IllegalArgumentException - if the given dimensionality is too small to cover the given values (i.e., the maximum index of any value not zero is bigger than the given dimensionality)

SparseDoubleVector

public SparseDoubleVector(double[] values)
                   throws IllegalArgumentException

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

Throws:

IllegalArgumentException - if the given dimensionality is too small to cover the given values (i.e., the maximum index of any value not zero is bigger than the given dimensionality)

Method Detail

getMaxDim

private int getMaxDim()

Get the maximum dimensionality.

Returns:

the maximum dimensionality seen

getDimensionality

public int getDimensionality()

Description copied from interface: FeatureVector

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

Specified by:

getDimensionality in interface FeatureVector<Double>

Specified by:

getDimensionality in interface SpatialComparable

Returns:

the number of dimensions of this FeatureVector of V

setDimensionality

public void setDimensionality(int dimensionality)
                       throws IllegalArgumentException

Sets the dimensionality to the new value.

Specified by:

setDimensionality in interface SparseNumberVector<Double>

Parameters:

dimensionality - the new dimensionality

Throws:

IllegalArgumentException - if the given dimensionality is too small to cover the given values (i.e., the maximum index of any value not zero is bigger than the given dimensionality)

getValue

@Deprecated
public Double getValue(int dimension)

Deprecated.

Description copied from interface: FeatureVector

Returns the value in the specified dimension.

Specified by:

getValue in interface FeatureVector<Double>

Specified by:

getValue in interface NumberVector<Double>

Parameters:

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

Returns:

the value in the specified dimension

doubleValue

public double doubleValue(int dimension)

Description copied from interface: NumberVector

Returns the value in the specified dimension as double. Note: this might seem redundant with respect to getValue(dim).doubleValue(), but usually this is much more efficient due to boxing/unboxing cost.

Specified by:

doubleValue in interface NumberVector<Double>

Parameters:

dimension - the desired dimension, where 0 ≤ dimension < this.getDimensionality()

Returns:

the value in the specified dimension

longValue

public long longValue(int dimension)

Description copied from interface: NumberVector

Returns the value in the specified dimension as long. Note: this might seem redundant with respect to getValue(dim).longValue(), but usually this is much more efficient due to boxing/unboxing cost.

Specified by:

longValue in interface NumberVector<Double>

Parameters:

dimension - the desired dimension, where 0 ≤ dimension < this.getDimensionality()

Returns:

the value in the specified dimension

getColumnVector

public Vector getColumnVector()

Description copied from interface: NumberVector

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

Specified by:

getColumnVector in interface NumberVector<Double>

Returns:

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

toString

public String toString()

Provides a String representation of this SparseDoubleVector as suitable for SparseNumberVectorLabelParser .

The returned String is a single line with entries separated by AbstractNumberVector.ATTRIBUTE_SEPARATOR. The first entry gives the number of values actually not zero. Following entries are pairs of Integer and Double where the Integer gives the index of the dimensionality and the Double gives the corresponding value.

Example: a vector (0,1.2,1.3,0)^T would result in the String
2 2 1.2 3 1.3

Specified by:

toString in interface FeatureVector<Double>

Overrides:

toString in class Object

Returns:

a String representation of this SparseDoubleVector

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

getNotNullMask

public BitSet getNotNullMask()

Description copied from interface: SparseFeatureVector

Bit set of non-null features.

Specified by:

getNotNullMask in interface SparseFeatureVector<Double>

Returns:

Bit set