org.openimaj.feature

Class IntFV

java.lang.Object

org.openimaj.feature.ArrayFeatureVector<int[]>

org.openimaj.feature.IntFV

All Implemented Interfaces:

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

Direct Known Subclasses:

MultidimensionalIntFV

public class IntFV
extends ArrayFeatureVector<int[]>
implements Concatenatable<IntFV,IntFV>, Cloneable

Basic int single-dimensional feature vector implementation

Author:

Jonathon Hare

See Also:

Serialized Form

Field Summary

Fields inherited from class org.openimaj.feature.ArrayFeatureVector

values

Constructor Summary

Constructors

Constructor and Description
IntFV() Construct an empty feature vector
IntFV(int nbins) Construct empty FV with given number of bins
IntFV(int[] values) Construct from flattened values array and dimensions

Method Summary

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.
IntFV	clone()
double	compare(IntFV h, IntFVComparison method) Compare this FV to another with the given method.
IntFV	concatenate(IntFV... ins) Concatenate all the inputs with this, returning a new object that is the result of the concatenation.
IntFV	concatenate(List<IntFV> ins) Concatenate all the inputs with this, returning a new object that is the result of the concatenation.
boolean	equals(Object obj)
int	get(int x) Get the element at the given flat index
double	getAsDouble(int i) Get an element of the feature as a double value
int	hashCode()
int	length() Get the length of this vector
IntFV	newInstance() Construct a new instance of this featurevector.
DoubleFV	normaliseFV() Normalise the FV to unit area.
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	setFromDouble(int i, double v) Set an element of the feature from a double value
IntFV	subvector(int beginIndex) Returns a new featurevector that is a subsequence of this vector.
IntFV	subvector(int beginIndex, int endIndex) Returns a new string that is a subvector of this vector.
String	toString()
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 org.openimaj.feature.ArrayFeatureVector

getVector

Methods inherited from class java.lang.Object

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

Constructor Detail

IntFV

public IntFV()

Construct an empty feature vector

IntFV

public IntFV(int nbins)

Construct empty FV with given number of bins

Parameters:

nbins - the number of bins in each dimension

IntFV

public IntFV(int[] values)

Construct from flattened values array and dimensions

Parameters:

values - the flat array of values

Method Detail

get

public int get(int x)

Get the element at the given flat index

Parameters:

x - the flattened element index

Returns:

the value corresponding to x

normaliseFV

public 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.

Specified by:

normaliseFV in interface FeatureVector

Parameters:

min - an array containing the minimum expected values

max - an array containing the maximum expected values

Returns:

feature vector with each value normalised to 0..1

normaliseFV

public DoubleFV normaliseFV(double min,
                            double max)

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:

feature vector with each value normalised to 0..1

normaliseFV

public DoubleFV normaliseFV()

Normalise the FV to unit area.

Specified by:

normaliseFV in interface FeatureVector

Returns:

feature vector with all elements summing to 1.

normaliseFV

public DoubleFV normaliseFV(double p)

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

clone

public IntFV clone()

Overrides:

clone in class Object

toString

public String toString()

Overrides:

toString in class Object

asDoubleFV

public DoubleFV asDoubleFV()

Convert the FV to a DoubleFV representation

Specified by:

asDoubleFV in interface FeatureVector

Returns:

the DoubleFV representation

asDoubleVector

public double[] asDoubleVector()

Convert the FV to a 1-dimensional double array representation

Specified by:

asDoubleVector in interface FeatureVector

Returns:

the double[] representation

compare

public double compare(IntFV h,
                      IntFVComparison method)

Compare this FV to another with the given method.

Parameters:

h - the feature to compare against.

method - the method to compare with.

Returns:

a score determined by the comparison method.

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

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

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

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

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

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

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

concatenate

public IntFV concatenate(IntFV... 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<IntFV,IntFV>

Parameters:

ins - the inputs

Returns:

the concatenated object

concatenate

public IntFV concatenate(List<IntFV> 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<IntFV,IntFV>

Parameters:

ins - the inputs

Returns:

the concatenated object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

subvector

public IntFV subvector(int beginIndex)

Description copied from class: ArrayFeatureVector

Returns a new featurevector that is a subsequence of this vector. The subsequence begins with the element at the specified index and extends to the end of this vector.

Specified by:

subvector in class ArrayFeatureVector<int[]>

Parameters:

beginIndex - the beginning index, inclusive.

Returns:

the specified subvector.

subvector

public IntFV subvector(int beginIndex,
                       int endIndex)

Description copied from class: ArrayFeatureVector

Returns a new string that is a subvector of this vector. The subvector begins at the specified beginIndex and extends to the element at index endIndex - 1. Thus the length of the subvector is endIndex-beginIndex.

Specified by:

subvector in class ArrayFeatureVector<int[]>

Parameters:

beginIndex - the beginning index, inclusive.

endIndex - the ending index, exclusive.

Returns:

the specified subvector.

getAsDouble

public double getAsDouble(int i)

Description copied from interface: FeatureVector

Get an element of the feature as a double value

Specified by:

getAsDouble in interface FeatureVector

Parameters:

i - the element index

Returns:

the value as a double

setFromDouble

public void setFromDouble(int i,
                          double v)

Description copied from interface: FeatureVector

Set an element of the feature from a double value

Specified by:

setFromDouble in interface FeatureVector

Parameters:

i - the element index

v - the value

newInstance

public IntFV newInstance()

Description copied from interface: FeatureVector

Construct a new instance of this featurevector. Implementors must return an instance of themselves (rather than a different type of feature).

Specified by:

newInstance in interface FeatureVector

Returns:

a new instance.