net.librec.math.structure

Class DenseVector

java.lang.Object

net.librec.math.structure.DenseVector

All Implemented Interfaces:

java.io.Serializable

public class DenseVector
extends java.lang.Object
implements java.io.Serializable

Data Structure: dense vector

Author:

guoguibing

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected double[]	data
protected int	size

Constructor Summary

Constructors

Constructor and Description
DenseVector(DenseVector vec) Construct a dense vector by deeply copying data from a given vector
DenseVector(double[] array) Construct a dense vector by deeply copying data from a given array
DenseVector(double[] array, boolean deep) Construct a dense vector by copying data from a given array
DenseVector(int size) Construct a dense vector with a specific size

Method Summary

Methods

Modifier and Type	Method and Description
DenseVector	add(DenseVector vec) Do vector operation: a + b
DenseVector	add(double val) Return a new dense vector by adding a value to all entries of current vector a[i] = b[i] + c
void	add(int idx, double val) Add a value to entry [index]
DenseVector	addEqual(DenseVector vec) Do vector operation: a + b
DenseVector	addEqual(double val) Return this dense vector by adding a value to all entries of current vector b[i] = b[i] + c
DenseVector	clone() Make a deep copy of current vector
double	get(int idx) Get a value at entry [index]
double[]	getData()
void	init() Initialize a dense vector with uniform values in (0, 1)
void	init(double range) Initialize a dense vector with uniform values in (0, range)
void	init(double mean, double sigma) Initialize a dense vector with Gaussian values
double	inner(DenseVector vec) Do vector operation: a^t * b
double	inner(SparseVector vec) Do vector operation: a^t * b
static DenseVector	kroneckerProduct(DenseVector M, DenseVector N) Return the Kronecker product of two vectors
double	mean()
DenseVector	minus(DenseVector vec) Do vector operation: a - b
DenseVector	minus(double val) Return a new dense vector by substructing a value from all entries of current vector a[i] = b[i] - c
void	minus(int idx, double val) Substract a value from entry [index]
DenseVector	minusEqual(DenseVector vec) Do vector operation: a - b
DenseVector	minusEqual(double val) Return this dense vector by substructing a value from all entries of current vector b[i] = b[i] - c
DenseMatrix	outer(DenseVector vec) Do vector operation: a * b^t
DenseVector	scale(double val) Return a new dense vector by scaling a value to all entries of current vector a = b.scale(c)
DenseVector	scaleEqual(double val) Return this dense vector by scaling a value to all entries of current vector b = b.scale(c).
void	set(int idx, double val) Set a value to entry [index]
void	setAll(double val) Set a value to all entries
void	setData(double[] data)
double	sum()
java.lang.String	toString()

Methods inherited from class java.lang.Object

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

Field Detail

size

protected int size

data

protected double[] data

Constructor Detail

DenseVector

public DenseVector(int size)

Construct a dense vector with a specific size

Parameters:

size - the size of vector

DenseVector

public DenseVector(double[] array)

Construct a dense vector by deeply copying data from a given array

Parameters:

array - a given array

DenseVector

public DenseVector(double[] array,
           boolean deep)

Construct a dense vector by copying data from a given array

Parameters:

array - a given data array

deep - whether to deep copy array data

DenseVector

public DenseVector(DenseVector vec)

Construct a dense vector by deeply copying data from a given vector

Parameters:

vec - a given vector

Method Detail

clone

public DenseVector clone()

Make a deep copy of current vector

Overrides:

clone in class java.lang.Object

init

public void init(double mean,
        double sigma)

Initialize a dense vector with Gaussian values

Parameters:

mean - mean of the gaussian

sigma - sigma of the gaussian

init

public void init()

Initialize a dense vector with uniform values in (0, 1)

init

public void init(double range)

Initialize a dense vector with uniform values in (0, range)

Parameters:

range - max of the range

get

public double get(int idx)

Get a value at entry [index]

Parameters:

idx - index of the data

Returns:

value at entry [index]

getData

public double[] getData()

Returns:

vector's data

mean

public double mean()

Returns:

mean of current vector

sum

public double sum()

Returns:

summation of entries

set

public void set(int idx,
       double val)

Set a value to entry [index]

Parameters:

idx - index to set

val - value to set

setAll

public void setAll(double val)

Set a value to all entries

Parameters:

val - value to set

add

public void add(int idx,
       double val)

Add a value to entry [index]

Parameters:

idx - index to add

val - value to add

minus

public void minus(int idx,
         double val)

Substract a value from entry [index]

Parameters:

idx - index to minus

val - value to minus

add

public DenseVector add(double val)

Return a new dense vector by adding a value to all entries of current vector a[i] = b[i] + c

Parameters:

val - value to add

Returns:

a new dense vector by adding a value to all entries of current vector a[i] = b[i] + c

addEqual

public DenseVector addEqual(double val)

Return this dense vector by adding a value to all entries of current vector b[i] = b[i] + c

Parameters:

val - value to add

Returns:

this dense vector by adding a value to all entries of current vector b[i] = b[i] + c

add

public DenseVector add(DenseVector vec)

Do vector operation: a + b

Parameters:

vec - vector to add

Returns:

a new dense vector with results of c = a + b

addEqual

public DenseVector addEqual(DenseVector vec)

Do vector operation: a + b

Parameters:

vec - vector to add

Returns:

this dense vector with results of a = a + b

minus

public DenseVector minus(double val)

Return a new dense vector by substructing a value from all entries of current vector a[i] = b[i] - c

Parameters:

val - value to minus

Returns:

a new dense vector by substructing a value from all entries of current vector a[i] = b[i] - c

minusEqual

public DenseVector minusEqual(double val)

Return this dense vector by substructing a value from all entries of current vector b[i] = b[i] - c

Parameters:

val - value to

Returns:

this dense vector by substructing a value from all entries of current vector b[i] = b[i] - c

minus

public DenseVector minus(DenseVector vec)

Do vector operation: a - b

Parameters:

vec - a given vector

Returns:

a new dense vector with results of c = a - b

minusEqual

public DenseVector minusEqual(DenseVector vec)

Do vector operation: a - b

Parameters:

vec - a given vector

Returns:

this dense vector with results of a = a - b

scale

public DenseVector scale(double val)

Return a new dense vector by scaling a value to all entries of current vector a = b.scale(c)

Parameters:

val - a given value for scaling

Returns:

a new dense vector by scaling a value to all entries of current vector a = b.scale(c)

scaleEqual

public DenseVector scaleEqual(double val)

Return this dense vector by scaling a value to all entries of current vector b = b.scale(c).

Parameters:

val - a given value for scaling

Returns:

this dense vector by scaling a value to all entries of current vector b = b.scale(c)

inner

public double inner(DenseVector vec)

Do vector operation: a^t * b

Parameters:

vec - a given vector

Returns:

the inner product of two vectors

inner

public double inner(SparseVector vec)

Do vector operation: a^t * b

Parameters:

vec - a given vector

Returns:

the inner product of two vectors

outer

public DenseMatrix outer(DenseVector vec)

Do vector operation: a * b^t

Parameters:

vec - a given vector

Returns:

the outer product of two vectors

kroneckerProduct

public static DenseVector kroneckerProduct(DenseVector M,
                           DenseVector N)

Return the Kronecker product of two vectors

Parameters:

M - a dense matrix

N - another dense matrix

Returns:

the Kronecker product of two vectors

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

setData

public void setData(double[] data)

Parameters:

data - the data to set