org.openimaj.feature

Class SparseLongFV

java.lang.Object

org.openimaj.feature.SparseLongFV

All Implemented Interfaces:

Serializable, Cloneable, FeatureVector, Readable, ReadableASCII, ReadableBinary, ReadWriteable, Writeable, WriteableASCII, WriteableBinary, Concatenatable<SparseLongFV,SparseLongFV>

public class SparseLongFV
extends Object
implements FeatureVector, Concatenatable<SparseLongFV,SparseLongFV>

A sparse one-dimensional feature vector of long-valued elements.

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
SparseLongArray	values The underlying data backing the feature vector

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	SparseLongFV() Construct an empty FV with zero length
	SparseLongFV(int nbins) Construct empty FV with given number of bins
	SparseLongFV(long[] values) Construct from native array
	SparseLongFV(SparseLongArray values) Construct from sparse array

Method Summary

Methods

Modifier and Type	Method and Description
String	asciiHeader() Header for ascii input.
DoubleFV	asDoubleFV() Convert the FV to a DoubleFV representation
double[]	asDoubleVector() Convert the FV to a 1-dimensional double array representation
byte[]	binaryHeader() Header for binary input.
SparseLongFV	concatenate(List<SparseLongFV> ins) Concatenate all the inputs with this, returning a new object that is the result of the concatenation.
SparseLongFV	concatenate(SparseLongFV... ins) Concatenate all the inputs with this, returning a new object that is the result of the concatenation.
SparseLongArray	getVector() Get the underlying data array.
int	length() Get the length of this vector
DoubleFV	normaliseFV() Normalise the FV to unit length
DoubleFV	normaliseFV(double p) Lp Norm of the FV.
DoubleFV	normaliseFV(double[] min, double[] max) Element-wise normalisation to 0..1 using separated expected minimum and maximum values for each element of the underlying feature vector.
DoubleFV	normaliseFV(double min, double max) Min-Max normalisation of the FV.
void	readASCII(Scanner in) Read internal state from in.
void	readBinary(DataInput in) Read internal state from in.
void	writeASCII(PrintWriter out) Write the content of this as ascii to out.
void	writeBinary(DataOutput out) Write the content of this as binary to out.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

values

public SparseLongArray values

The underlying data backing the feature vector

Constructor Detail

SparseLongFV

protected SparseLongFV()

Construct an empty FV with zero length

SparseLongFV

public SparseLongFV(int nbins)

Construct empty FV with given number of bins

Parameters:

nbins - the number of bins in each dimension

SparseLongFV

public SparseLongFV(SparseLongArray values)

Construct from sparse array

Parameters:

values - the array of values

SparseLongFV

public SparseLongFV(long[] values)

Construct from native array

Parameters:

values - the array of values

Method Detail

readASCII

public void readASCII(Scanner in)
               throws IOException

Description copied from interface: ReadableASCII

Read internal state from in.

Specified by:

readASCII in interface ReadableASCII

Parameters:

in - source to read from.

Throws:

IOException - an error reading input

asciiHeader

public String asciiHeader()

Description copied from interface: ReadableASCII

Header for ascii input. Will be automatically read by IOUtils when using readASCII().

Specified by:

asciiHeader in interface ReadableASCII

Specified by:

asciiHeader in interface WriteableASCII

Returns:

header

readBinary

public void readBinary(DataInput in)
                throws IOException

Description copied from interface: ReadableBinary

Read internal state from in.

Specified by:

readBinary in interface ReadableBinary

Parameters:

in - source to read from.

Throws:

IOException - an error reading input

binaryHeader

public byte[] binaryHeader()

Description copied from interface: ReadableBinary

Header for binary input. Will be automatically read by IOUtils when using readBinary().

Specified by:

binaryHeader in interface ReadableBinary

Specified by:

binaryHeader in interface WriteableBinary

Returns:

header

writeASCII

public void writeASCII(PrintWriter out)
                throws IOException

Description copied from interface: WriteableASCII

Write the content of this as ascii to out.

Specified by:

writeASCII in interface WriteableASCII

Parameters:

out - sink to write to

Throws:

IOException - an error writing to out

writeBinary

public void writeBinary(DataOutput out)
                 throws IOException

Description copied from interface: WriteableBinary

Write the content of this as binary to out.

Specified by:

writeBinary in interface WriteableBinary

Parameters:

out - sink to write to

Throws:

IOException - an error writing to out

getVector

public SparseLongArray getVector()

Description copied from interface: FeatureVector

Get the underlying data array.

Specified by:

getVector in interface FeatureVector

Returns:

underlying data

length

public int length()

Description copied from interface: FeatureVector

Get the length of this vector

Specified by:

length in interface FeatureVector

Returns:

the length of this vector

normaliseFV

public DoubleFV normaliseFV(double[] min,
                   double[] max)

Description copied from interface: FeatureVector

Element-wise normalisation to 0..1 using separated expected minimum and maximum values for each element of the underlying feature vector.

Specified by:

normaliseFV in interface FeatureVector

Parameters:

min - an array containing the minimum expected values

max - an array containing the maximum expected values

Returns:

copy of the feature vector with each value normalised to 0..1

normaliseFV

public DoubleFV normaliseFV(double min,
                   double max)

Description copied from interface: FeatureVector

Min-Max normalisation of the FV. Each element of the underlying feature vector is normalised to 0..1 based on the provided minimum and maximum expected values.

Specified by:

normaliseFV in interface FeatureVector

Parameters:

min - the minimum expected value

max - the maximum expected value

Returns:

copy of the feature vector with each value normalised to 0..1

normaliseFV

public DoubleFV normaliseFV()

Description copied from interface: FeatureVector

Normalise the FV to unit length

Specified by:

normaliseFV in interface FeatureVector

Returns:

a copy of the feature vector as a DoubleFV, normalised to unit length

normaliseFV

public DoubleFV normaliseFV(double p)

Description copied from interface: FeatureVector

Lp Norm of the FV.

Specified by:

normaliseFV in interface FeatureVector

Parameters:

p - the norm to compute

Returns:

feature vector normalised using the Lp norm

asDoubleFV

public DoubleFV asDoubleFV()

Description copied from interface: FeatureVector

Convert the FV to a DoubleFV representation

Specified by:

asDoubleFV in interface FeatureVector

Returns:

a copy of the feature vector as a DoubleFV

asDoubleVector

public double[] asDoubleVector()

Description copied from interface: FeatureVector

Convert the FV to a 1-dimensional double array representation

Specified by:

asDoubleVector in interface FeatureVector

Returns:

a copy of the feature vector as a double array

concatenate

public SparseLongFV concatenate(SparseLongFV... ins)

Description copied from interface: Concatenatable

Concatenate all the inputs with this, returning a new object that is the result of the concatenation.

Specified by:

concatenate in interface Concatenatable<SparseLongFV,SparseLongFV>

Parameters:

ins - the inputs

Returns:

the concatenated object

concatenate

public SparseLongFV concatenate(List<SparseLongFV> ins)

Description copied from interface: Concatenatable

Concatenate all the inputs with this, returning a new object that is the result of the concatenation.

Specified by:

concatenate in interface Concatenatable<SparseLongFV,SparseLongFV>

Parameters:

ins - the inputs

Returns:

the concatenated object