gov.sandia.cognition.math.matrix.mtj

Class SparseVector

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.math.AbstractRing<VectorType>

gov.sandia.cognition.math.matrix.AbstractVectorSpace<Vector,VectorEntry>

gov.sandia.cognition.math.matrix.AbstractVector

gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector

gov.sandia.cognition.math.matrix.mtj.SparseVector

All Implemented Interfaces:

Vector, Vectorizable, VectorSpace<Vector,VectorEntry>, Ring<Vector>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable, java.lang.Iterable<VectorEntry>

@CodeReview(reviewer="Justin Basilico",
            date="2006-07-27",
            changesNeeded=false,
            comments="Looks good.")
public class SparseVector
extends AbstractMTJVector

A vector that only stores the nonzero elements, relies on MTJ's SparseVector. It has fast traversal by skipping nonzero elements but has slow indexing.

Since:

1.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface gov.sandia.cognition.math.matrix.Vector

Vector.IndexValueConsumer, Vector.IndexValueTransform

Nested classes/interfaces inherited from interface gov.sandia.cognition.math.matrix.VectorSpace

VectorSpace.Entry

Field Summary

Fields inherited from class gov.sandia.cognition.math.matrix.AbstractVector

DEFAULT_DELIMITER

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	SparseVector(int numDimensions) Creates a new instance of SparseVector with no initial size.
protected	SparseVector(int numDimensions, int initialNonZeros) Creates a new instance of SparseVector with a specified initial size.
protected	SparseVector(no.uib.cipr.matrix.sparse.SparseVector internalVector) Creates a new copy of SparseVector.
protected	SparseVector(Vector vector) Creates a new copy of SparseVector.

Method Summary

Modifier and Type	Method and Description
void	compact() Compacts the SparseVector, getting rid of any zero'ed elements.
int	countNonZeros() Counts the number of non-zero entries in the vector.
double	euclideanDistanceSquared(Vector other) Squared Euclidean distance between this and other, which is the 2-norm between the difference of the Vectors
void	forEachElement(Vector.IndexValueConsumer consumer) Applies the given function to each element in this vector.
void	forEachEntry(Vector.IndexValueConsumer consumer) Applies the given function to each active entry in this vector.
void	forEachNonZero(Vector.IndexValueConsumer consumer) Applies the given function to each non-zero entry in this vector.
int	getEntryCount() Gets the number of active entries in the vector.
protected no.uib.cipr.matrix.sparse.SparseVector	getInternalVector() Getter for internalVector
double	getMaxValue() The maximum value associated with any key in the vector.
double	getMinValue() The minimum value associated with any key in the vector.
int	getNumElementsUsed() Deprecated.
SparseVectorFactory<?>	getVectorFactory() Gets a vector factory associated with this kind of vector.
boolean	isSparse() Returns true if this vector has a potentially sparse underlying structure.
SparseRowMatrix	outerProduct(AbstractMTJVector other) Computes the outer matrix product between the two vectors
void	setElement(int index, double value) Sets the zero-based indexed element in the Vector from the specified value
protected void	setInternalVector(no.uib.cipr.matrix.sparse.SparseVector internalVector) Setter for the internal MTJ vector.
protected void	setInternalVector(no.uib.cipr.matrix.Vector internalVector) Setter for internalVector
SparseVector	stack(Vector other) Stacks "other" below "this" and returns the stacked Vector
SparseVector	subVector(int minIndex, int maxIndex) Gets a subvector of "this", specified by the inclusive indices
double	sum() Computes the sum of the elements in the vector.
java.lang.String	toString() Prints the SparseVector in "Index: Value" format.
void	transformNonZerosEquals(UnivariateScalarFunction function) Applies the given function to each of the non-zero elements of this vector and sets them to the result.
void	transformNonZerosEquals(Vector.IndexValueTransform function) Applies the given function to each of the non-zero elements of this vector and sets them to the result.

Methods inherited from class gov.sandia.cognition.math.matrix.mtj.AbstractMTJVector

clone, dotProduct, dotProduct, dotTimesEquals, get, getDimensionality, getElement, increment, iterator, minusEquals, minusEquals, norm2, norm2Squared, outerProduct, plusEquals, plusEquals, scaledMinusEquals, scaledPlusEquals, scaledPlusEquals, scaleEquals, set, times, times, zero

Methods inherited from class gov.sandia.cognition.math.matrix.AbstractVector

assertDimensionalityEquals, assertEqualDimensionality, assertSameDimensionality, checkSameDimensionality, convertFromVector, convertToVector, decrement, decrement, dotDivide, dotDivideEquals, equals, equals, hashCode, increment, toArray, toString, toString, transform, transform, transformEquals, transformEquals, transformNonZeros, transformNonZeros, valuesAsList

Methods inherited from class gov.sandia.cognition.math.matrix.AbstractVectorSpace

angle, cosine, dot, euclideanDistance, isUnitVector, isUnitVector, isZero, norm, norm1, normInfinity, unitVector, unitVectorEquals

Methods inherited from class gov.sandia.cognition.math.AbstractRing

dotTimes, isZero, minus, negative, negativeEquals, plus, scale, scaledMinus, scaledMinusEquals, scaledPlus

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.math.matrix.VectorSpace

angle, cosine, dot, euclideanDistance, isUnitVector, isUnitVector, norm, norm1, normInfinity, unitVector, unitVectorEquals

Methods inherited from interface gov.sandia.cognition.math.Ring

dotTimes, isZero, isZero, minus, negative, negativeEquals, plus, scale, scaledMinus, scaledMinusEquals, scaledPlus

Methods inherited from interface java.lang.Iterable

forEach, spliterator

Constructor Detail

SparseVector

protected SparseVector(int numDimensions)

Creates a new instance of SparseVector with no initial size.

Parameters:

numDimensions - Maximum number of entries in the SparseVector.

SparseVector

protected SparseVector(int numDimensions,
                       int initialNonZeros)

Creates a new instance of SparseVector with a specified initial size.

Parameters:

numDimensions - Maximum number of entries in the SparseVector.

initialNonZeros - Initial size of the SparseVector.

SparseVector

protected SparseVector(no.uib.cipr.matrix.sparse.SparseVector internalVector)

Creates a new copy of SparseVector.

Parameters:

internalVector - Internal MTJ-based vector to set into this.

SparseVector

protected SparseVector(Vector vector)

Creates a new copy of SparseVector.

Parameters:

vector - Vector to copy into this, will not be modified.

Method Detail

getEntryCount

public int getEntryCount()

Description copied from interface: Vector

Gets the number of active entries in the vector. Must be between zero and the dimensionality.

Returns:

The number of active entries in the vector.

getNumElementsUsed

@Deprecated
public int getNumElementsUsed()

Deprecated.

Gets the number of elements used inside the sparse vector, equals the allocation size of the vector.

Returns:

The number of nonzero elements in the SparseVector.

setElement

public void setElement(int index,
                       double value)

Description copied from interface: Vector

Sets the zero-based indexed element in the Vector from the specified value

Specified by:

setElement in interface Vector

Overrides:

setElement in class AbstractMTJVector

Parameters:

index - zero-based index

value - value to set the element in the Vector

getInternalVector

protected no.uib.cipr.matrix.sparse.SparseVector getInternalVector()

Description copied from class: AbstractMTJVector

Getter for internalVector

Overrides:

getInternalVector in class AbstractMTJVector

Returns:

MTJ-based internal vector that does the heavy lifting

setInternalVector

protected void setInternalVector(no.uib.cipr.matrix.Vector internalVector)

Description copied from class: AbstractMTJVector

Setter for internalVector

Overrides:

setInternalVector in class AbstractMTJVector

Parameters:

internalVector - internal MTJ-based vector that does the heavy lifting

setInternalVector

protected void setInternalVector(no.uib.cipr.matrix.sparse.SparseVector internalVector)

Setter for the internal MTJ vector.

Parameters:

internalVector - Internal MTJ-based vector.

euclideanDistanceSquared

public double euclideanDistanceSquared(Vector other)

Description copied from interface: VectorSpace

Squared Euclidean distance between this and other, which is the 2-norm between the difference of the Vectors

Specified by:

euclideanDistanceSquared in interface VectorSpace<Vector,VectorEntry>

Overrides:

euclideanDistanceSquared in class AbstractVector

Parameters:

other - Vector to which to compute the squared distance, must be the same dimension as this

Returns:

this.minus( other ).norm2Squared(), which is [0,\infty)

outerProduct

public SparseRowMatrix outerProduct(AbstractMTJVector other)

Description copied from class: AbstractMTJVector

Computes the outer matrix product between the two vectors

Specified by:

outerProduct in class AbstractMTJVector

Parameters:

other - post-multiplied Vector with which to compute the outer product

Returns:

Outer matrix product, which will have dimensions (this.getDimensionality x other.getDimensionality) and WILL BE singular

toString

public java.lang.String toString()

Prints the SparseVector in "Index: Value" format.

Specified by:

toString in interface Vector

Overrides:

toString in class AbstractVector

Returns:

String containing the representation of the SparseVector

compact

public void compact()

Compacts the SparseVector, getting rid of any zero'ed elements.

stack

public SparseVector stack(Vector other)

Description copied from interface: Vector

Stacks "other" below "this" and returns the stacked Vector

Specified by:

stack in interface Vector

Overrides:

stack in class AbstractVector

Parameters:

other - Vector to stack below "this"

Returns:

stacked Vector

transformNonZerosEquals

public void transformNonZerosEquals(UnivariateScalarFunction function)

Description copied from interface: Vector

Applies the given function to each of the non-zero elements of this vector and sets them to the result.

Specified by:

transformNonZerosEquals in interface Vector

Overrides:

transformNonZerosEquals in class AbstractVector

Parameters:

function - The function from double to double to apply to the non-zero elements.

transformNonZerosEquals

public void transformNonZerosEquals(Vector.IndexValueTransform function)

Description copied from interface: Vector

Applies the given function to each of the non-zero elements of this vector and sets them to the result.

Specified by:

transformNonZerosEquals in interface Vector

Overrides:

transformNonZerosEquals in class AbstractVector

Parameters:

function - The function from index and value to double to apply to non-zero elements.

forEachElement

public void forEachElement(Vector.IndexValueConsumer consumer)

Description copied from interface: Vector

Applies the given function to each element in this vector. This is a dense operation that includes all values, even on a sparse vector.

Specified by:

forEachElement in interface Vector

Overrides:

forEachElement in class AbstractVector

Parameters:

consumer - The consumer for the entries. It is called for each element in the vector, in order by increasing index.

forEachEntry

public void forEachEntry(Vector.IndexValueConsumer consumer)

Description copied from interface: Vector

Applies the given function to each active entry in this vector. This can be faster than looping over the entries using an iterator.

Specified by:

forEachEntry in interface Vector

Overrides:

forEachEntry in class AbstractVector

Parameters:

consumer - The consumer for the entries. It is called for each active entry in the vector, in order by increasing index.

forEachNonZero

public void forEachNonZero(Vector.IndexValueConsumer consumer)

Description copied from interface: Vector

Applies the given function to each non-zero entry in this vector. This can be faster than looping over the entries using an iterator.

Specified by:

forEachNonZero in interface Vector

Overrides:

forEachNonZero in class AbstractVector

Parameters:

consumer - The consumer for the non-zero entries. It is called for each non-zero entry in the vector, in order by increasing index.

isSparse

public boolean isSparse()

Description copied from interface: Vector

Returns true if this vector has a potentially sparse underlying structure. This can indicate that it is faster to only process the non-zero elements rather than to do dense operations on it. Of course, even with a sparse structure, there may be no zero elements or conversely even with a non-sparse (dense) structure there may be many zero elements.

Returns:

True if the vector has a potentially sparse structure. Otherwise, false.

sum

public double sum()

Description copied from interface: VectorSpace

Computes the sum of the elements in the vector.

Specified by:

sum in interface VectorSpace<Vector,VectorEntry>

Overrides:

sum in class AbstractVectorSpace<Vector,VectorEntry>

Returns:

The sum of the elements in the vector.

getMinValue

public double getMinValue()

Description copied from interface: VectorSpace

The minimum value associated with any key in the vector.

Returns:

The minimum value associated with any key in the vector. If the vector is empty, then Double.POSITIVE_INFINITY is returned.

getMaxValue

public double getMaxValue()

Description copied from interface: VectorSpace

The maximum value associated with any key in the vector.

Returns:

The maximum value associated with any key in the vector. If the vector is empty, then Double.NEGATIVE_INFINITY is returned.

countNonZeros

public int countNonZeros()

Description copied from interface: Vector

Counts the number of non-zero entries in the vector. Must be between zero and the dimensionality. This operation may require evaluating all entries in the vector based on the implementation.

Returns:

The number of non-zero values in the vector.

getVectorFactory

public SparseVectorFactory<?> getVectorFactory()

Description copied from interface: Vector

Gets a vector factory associated with this kind of vector.

Returns:

The associated factory.

subVector

public SparseVector subVector(int minIndex,
                              int maxIndex)

Description copied from interface: Vector

Gets a subvector of "this", specified by the inclusive indices

Parameters:

minIndex - minimum index to get (inclusive)

maxIndex - maximum index to get (inclusive)

Returns:

vector of dimension (maxIndex-minIndex+1)