DenseVector (Java Statistical Analysis Tool 0.0.8 API)

java.lang.Object
- jsat.linear.Vec
- - jsat.linear.DenseVector

All Implemented Interfaces:

Serializable, Cloneable, Iterable<IndexValue>
```
public class DenseVector
extends Vec
```
A vector implementation that is dense, meaning all values are allocated - even if their values will be implicitly zero.

Author:

Edward Raff

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

protected double[] array

Fields
Modifier and Type	Field and Description
`protected double[]`	`array`

Constructor Summary

Constructors
Constructor and Description
`DenseVector(double[] array)` Creates a new Dense Vector that uses the given array as its values.
`DenseVector(double[] array, int start, int end)` Creates a new Dense Vector that uses the given array as its values.
`DenseVector(int length)` Creates a new Dense Vector of zeros
`DenseVector(List<Double> list)` Creates a new vector of the length of the given list, and values copied over in order.
`DenseVector(Vec toCopy)` Creates a new Dense Vector that contains a copy of the values in the given vector

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`double[]`	`arrayCopy()` Creates a new array that contains all the values of this vector in the appropriate indices
`Vec`	`clone()`
`DenseVector`	`deepCopy()`
`double`	`dot(Vec v)` Computes the dot product between two vectors, which is equivalent to Σ this_i*v_i This method should be overloaded for a serious implementation.
`boolean`	`equals(Object obj)`
`boolean`	`equals(Object obj, double range)`
`double`	`get(int index)` Gets the value stored at a specific index in the vector
`boolean`	`isSparse()` Indicates whether or not this vector is optimized for sparce computation, meaning that most values in the vector are zero - and considered implicit.
`double`	`kurtosis()` Computes the kurtosis of this vector, which is the 4th moment.
`int`	`length()` Returns the length of this vector
`double`	`max()` Returns the maximum value stored in this vector
`double`	`median()` Returns the median value in this vector
`double`	`min()` Returns the minimum value stored in this vector
`void`	`multiply(double c, Matrix A, Vec b)` If this is vector `a`, this this computes b = b + c `a`^T*`A`
`void`	`mutableAdd(double c)` Alters this vector such that `this` = `this` + `c` This method should be overloaded for a serious implementation.
`void`	`mutableAdd(double c, Vec b)` Alters this vector such that `this` = `this` + `c` * `b` This method should be overloaded for a serious implementation.
`void`	`mutableDivide(double c)` Mutates `this /= c` This method should be overloaded for a serious implementation.
`void`	`mutableMultiply(double c)` Mutates `this *= c` This method should be overloaded for a serious implementation.
`void`	`mutablePairwiseDivide(Vec b)` Mutates `this` by dividing each value by the value in `b` that has the same index This method should be overloaded for a serious implementation.
`void`	`mutablePairwiseMultiply(Vec b)` Mutates `this` by multiplying each value by the value in `b` that has the same index.
`void`	`mutableSubtract(double c)` Alters this vector such that `this` = `this` - `c`
`void`	`normalize()` Mutates this vector to be normalized by the L₂ norm
`double`	`pNorm(double p)` Returns the p-norm of this vector.
`double`	`pNormDist(double p, Vec y)` Returns the p-norm distance between this and another vector y.
`void`	`set(int index, double val)` Sets the value stored at a specified index in the vector
`double`	`skewness()` Computes the skewness of this vector, which is the 3rd moment.
`DenseVector`	`sortedCopy()` Returns a copy of this array with the values moved around so that they are in sorted order
`double`	`sum()` Computes the sum of the values in this vector
`static DenseVector`	`toDenseVec(double... array)` Returns a new dense vector backed by the given array.
`double`	`variance()` Computes the variance of the values in this vector, which is `Vec.standardDeviation()`²

Methods inherited from class jsat.linear.Vec
add, add, applyFunction, applyIndexFunction, canBeMutated, copyTo, copyToCol, copyToRow, countNaNs, divide, getNonZeroIterator, getNonZeroIterator, hashCode, increment, iterator, mean, multiply, multiply, multiply, mutableAdd, mutableSubtract, mutableSubtract, nnz, normalized, pairwiseDivide, pairwiseMultiply, random, random, standardDeviation, subtract, subtract, toString, zeroOut, zeros

Methods inherited from class java.lang.Object
finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.lang.Iterable
forEach, spliterator

- Field Detail
  - array
```
protected double[] array
```
- Constructor Detail
  - DenseVector
```
public DenseVector(int length)
```
    Creates a new Dense Vector of zeros
    
    Parameters:
    
    length - the length of the vector
  - DenseVector
```
public DenseVector(List<Double> list)
```
    Creates a new vector of the length of the given list, and values copied over in order.
    
    Parameters:
    
    list - the list of values to copy into a new vector
  - DenseVector
```
public DenseVector(double[] array)
```
    Creates a new Dense Vector that uses the given array as its values. Its values will not be copied, and raw access and mutations tot he given array may occur.
    
    Parameters:
    
    array - the backing array to use for a new vector of the same length
  - DenseVector
```
public DenseVector(double[] array,
                   int start,
                   int end)
```
    Creates a new Dense Vector that uses the given array as its values. Its values will not be copied, and raw access and mutations tot he given array may occur.
    
    Parameters:
    
    array - the backing array to use for a new vector
    
    start - the first index in the array, inclusive, to mark the start of the vector.
    
    end - the last index in the array, exclusive, to mark the end of the vector.
  - DenseVector
```
public DenseVector(Vec toCopy)
```
    Creates a new Dense Vector that contains a copy of the values in the given vector
    
    Parameters:
    
    toCopy - the vector to copy
- Method Detail
  - length
```
public int length()
```
    Description copied from class: Vec
    
    Returns the length of this vector
    
    Specified by:
    
    length in class Vec
    
    Returns:
    
    the length of this vector
  - get
```
public double get(int index)
```
    Description copied from class: Vec
    
    Gets the value stored at a specific index in the vector
    
    Specified by:
    
    get in class Vec
    
    Parameters:
    
    index - the index to access
    
    Returns:
    
    the double value in the vector
  - set
```
public void set(int index,
                double val)
```
    Description copied from class: Vec
    
    Sets the value stored at a specified index in the vector
    
    Specified by:
    
    set in class Vec
    
    Parameters:
    
    index - the index to access
    
    val - the value to store in the index
  - min
```
public double min()
```
    Description copied from class: Vec
    
    Returns the minimum value stored in this vector
    
    Overrides:
    
    min in class Vec
    
    Returns:
    
    the minimum value in this vector
  - max
```
public double max()
```
    Description copied from class: Vec
    
    Returns the maximum value stored in this vector
    
    Overrides:
    
    max in class Vec
    
    Returns:
    
    the maximum value in this vector
  - sum
```
public double sum()
```
    Description copied from class: Vec
    
    Computes the sum of the values in this vector
    
    Overrides:
    
    sum in class Vec
    
    Returns:
    
    the sum of this vector's values
  - median
```
public double median()
```
    Description copied from class: Vec
    
    Returns the median value in this vector
    
    Overrides:
    
    median in class Vec
    
    Returns:
    
    the median
  - skewness
```
public double skewness()
```
    Description copied from class: Vec
    
    Computes the skewness of this vector, which is the 3rd moment.
    
    Overrides:
    
    skewness in class Vec
    
    Returns:
    
    the skewness
  - kurtosis
```
public double kurtosis()
```
    Description copied from class: Vec
    
    Computes the kurtosis of this vector, which is the 4th moment.
    
    Overrides:
    
    kurtosis in class Vec
    
    Returns:
    
    the kurtosis
  - sortedCopy
```
public DenseVector sortedCopy()
```
    Description copied from class: Vec
    
    Returns a copy of this array with the values moved around so that they are in sorted order
    
    Overrides:
    
    sortedCopy in class Vec
    
    Returns:
    
    a new array in sorted order
  - variance
```
public double variance()
```
    Description copied from class: Vec
    
    Computes the variance of the values in this vector, which is Vec.standardDeviation()²
    
    Overrides:
    
    variance in class Vec
    
    Returns:
    
    the variance
  - dot
```
public double dot(Vec v)
```
    Description copied from class: Vec
    
    Computes the dot product between two vectors, which is equivalent to
    Σ this_i*v_i
    
    This method should be overloaded for a serious implementation.
    
    Overrides:
    
    dot in class Vec
    
    Parameters:
    
    v - the other vector
    
    Returns:
    
    the dot product of this vector and another
  - deepCopy
```
public DenseVector deepCopy()
```
  - multiply
```
public void multiply(double c,
                     Matrix A,
                     Vec b)
```
    Description copied from class: Vec
    
    If this is vector a, this this computes b = b + c a^T*A
    
    Overrides:
    
    multiply in class Vec
    
    Parameters:
    
    c - the constant factor to multiply by
    
    A - the matrix to multiple by
    
    b - the vector to mutate by adding the result to
  - mutableAdd
```
public void mutableAdd(double c)
```
    Description copied from class: Vec
    
    Alters this vector such that this = this + c
    
    This method should be overloaded for a serious implementation.
    
    Overrides:
    
    mutableAdd in class Vec
    
    Parameters:
    
    c - a scalar constant to add to each value in this vector
  - mutableAdd
```
public void mutableAdd(double c,
                       Vec b)
```
    Description copied from class: Vec
    
    Alters this vector such that this = this + c * b
    
    This method should be overloaded for a serious implementation.
    
    Overrides:
    
    mutableAdd in class Vec
    
    Parameters:
    
    c - a scalar constant
    
    b - the vector to add to this
  - mutableSubtract
```
public void mutableSubtract(double c)
```
    Description copied from class: Vec
    
    Alters this vector such that this = this - c
    
    Overrides:
    
    mutableSubtract in class Vec
    
    Parameters:
    
    c - the scalar constant to subtract from all values in this vector
  - mutableMultiply
```
public void mutableMultiply(double c)
```
    Description copied from class: Vec
    
    Mutates this *= c
    
    This method should be overloaded for a serious implementation.
    
    Overrides:
    
    mutableMultiply in class Vec
    
    Parameters:
    
    c - the constant to multiply by
  - mutableDivide
```
public void mutableDivide(double c)
```
    Description copied from class: Vec
    
    Mutates this /= c
    
    This method should be overloaded for a serious implementation.
    
    Overrides:
    
    mutableDivide in class Vec
    
    Parameters:
    
    c - the constant to divide by
  - pNormDist
```
public double pNormDist(double p,
                        Vec y)
```
    Description copied from class: Vec
    
    Returns the p-norm distance between this and another vector y.
    
    Overrides:
    
    pNormDist in class Vec
    
    Parameters:
    
    p - the distance type. 2 is the common value
    
    y - the other vector to compare against
    
    Returns:
    
    the p-norm distance
  - pNorm
```
public double pNorm(double p)
```
    Description copied from class: Vec
    
    Returns the p-norm of this vector.
    
    Overrides:
    
    pNorm in class Vec
    
    Parameters:
    
    p - the norm type. 2 is a common value
    
    Returns:
    
    the p-norm of this vector
  - clone
```
public Vec clone()
```
    Specified by:
    
    clone in class Vec
  - normalize
```
public void normalize()
```
    Description copied from class: Vec
    
    Mutates this vector to be normalized by the L₂ norm
    
    Overrides:
    
    normalize in class Vec
  - mutablePairwiseMultiply
```
public void mutablePairwiseMultiply(Vec b)
```
    Description copied from class: Vec
    
    Mutates this by multiplying each value by the value in b that has the same index.
    
    This method should be overloaded for a serious implementation.
    
    Overrides:
    
    mutablePairwiseMultiply in class Vec
    
    Parameters:
    
    b - the vector to pairwise multiply by
  - mutablePairwiseDivide
```
public void mutablePairwiseDivide(Vec b)
```
    Description copied from class: Vec
    
    Mutates this by dividing each value by the value in b that has the same index
    
    This method should be overloaded for a serious implementation.
    
    Overrides:
    
    mutablePairwiseDivide in class Vec
    
    Parameters:
    
    b - the vector to pairwise divide by
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Vec
  - equals
```
public boolean equals(Object obj,
                      double range)
```
    Overrides:
    
    equals in class Vec
  - toDenseVec
```
public static DenseVector toDenseVec(double... array)
```
    Returns a new dense vector backed by the given array. This is a weak reference, the given array should no longer be altered - as it will effect the values of the dense vector.
    
    Parameters:
    
    array - the array to use as the backing of a dense vector
    
    Returns:
    
    a Dense Vector that is backed using the given array
  - arrayCopy
```
public double[] arrayCopy()
```
    Description copied from class: Vec
    
    Creates a new array that contains all the values of this vector in the appropriate indices
    
    Overrides:
    
    arrayCopy in class Vec
    
    Returns:
    
    a new array that is a copy of this vector
  - isSparse
```
public boolean isSparse()
```
    Description copied from class: Vec
    
    Indicates whether or not this vector is optimized for sparce computation, meaning that most values in the vector are zero - and considered implicit. Only non-zero values are stored.
    
    Specified by:
    
    isSparse in class Vec
    
    Returns:
    
    true if the vector is sparce, false otherwise.

Class DenseVector

Field Summary

Constructor Summary

Method Summary

Methods inherited from class jsat.linear.Vec

Methods inherited from class java.lang.Object

Methods inherited from interface java.lang.Iterable

Field Detail

array

Constructor Detail

DenseVector

DenseVector

DenseVector

DenseVector

DenseVector

Method Detail

length

get

set

min

max

sum

median

skewness

kurtosis

sortedCopy

variance

dot

deepCopy

multiply

mutableAdd

mutableAdd

mutableSubtract

mutableMultiply

mutableDivide

pNormDist

pNorm

clone

normalize

mutablePairwiseMultiply

mutablePairwiseDivide

equals

equals

toDenseVec

arrayCopy

isSparse