SparseIntFV (OpenIMAJ master project 1.3.10 API)

java.lang.Object
- org.openimaj.feature.SparseIntFV

All Implemented Interfaces:

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

Direct Known Subclasses:

Document
```
public class SparseIntFV
extends Object
implements FeatureVector, Concatenatable<SparseIntFV,SparseIntFV>
```
A sparse one-dimensional feature vector of int-valued elements.

Author:

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

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

SparseIntArray values
The underlying data backing the feature vector

Fields
Modifier and Type	Field and Description
`SparseIntArray`	`values` The underlying data backing the feature vector

Constructor Summary

Constructors
Modifier	Constructor and Description
`protected`	`SparseIntFV()` Construct an empty FV with zero length
	`SparseIntFV(int nbins)` Construct empty FV with given number of bins
	`SparseIntFV(int[] values)` Construct from native array
	`SparseIntFV(SparseIntArray values)` Construct from sparse array

Method Summary

All Methods Instance Methods Concrete 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.
`SparseIntFV`	`concatenate(List<SparseIntFV> ins)` Concatenate all the inputs with this, returning a new object that is the result of the concatenation.
`SparseIntFV`	`concatenate(SparseIntFV... ins)` Concatenate all the inputs with this, returning a new object that is the result of the concatenation.
`double`	`getAsDouble(int i)` Get an element of the feature as a double value
`SparseIntArray`	`getVector()` Get the underlying data array.
`int`	`length()` Get the length of this vector
`SparseIntFV`	`newInstance()` Construct a new instance of this featurevector.
`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`	`setFromDouble(int i, double v)` Set an element of the feature from a double value
`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 SparseIntArray values
```
    The underlying data backing the feature vector
- Constructor Detail
  - SparseIntFV
```
protected SparseIntFV()
```
    Construct an empty FV with zero length
  - SparseIntFV
```
public SparseIntFV(int nbins)
```
    Construct empty FV with given number of bins
    
    Parameters:
    
    nbins - the number of bins in each dimension
  - SparseIntFV
```
public SparseIntFV(SparseIntArray values)
```
    Construct from sparse array
    
    Parameters:
    
    values - the array of values
  - SparseIntFV
```
public SparseIntFV(int[] 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 SparseIntArray 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 SparseIntFV concatenate(SparseIntFV... 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<SparseIntFV,SparseIntFV>
    
    Parameters:
    
    ins - the inputs
    
    Returns:
    
    the concatenated object
  - concatenate
```
public SparseIntFV concatenate(List<SparseIntFV> 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<SparseIntFV,SparseIntFV>
    
    Parameters:
    
    ins - the inputs
    
    Returns:
    
    the concatenated object
  - 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 SparseIntFV 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.

Class SparseIntFV

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

values

Constructor Detail

SparseIntFV

SparseIntFV

SparseIntFV

SparseIntFV

Method Detail

readASCII

asciiHeader

readBinary

binaryHeader

writeASCII

writeBinary

getVector

length

normaliseFV

normaliseFV

normaliseFV

normaliseFV

asDoubleFV

asDoubleVector

concatenate

concatenate

getAsDouble

setFromDouble

newInstance