DenseVector (Tribuo 4.1.1 API)

java.lang.Object
- org.tribuo.math.la.DenseVector

All Implemented Interfaces:

Serializable, Iterable<VectorTuple>, SGDVector, Tensor

Direct Known Subclasses:

ShrinkingVector
```
public class DenseVector
extends Object
implements SGDVector
```
A dense vector, backed by a double array.

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

protected double[] elements

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

Constructor Summary

Constructors
Modifier	Constructor and Description
`protected`	`DenseVector(DenseVector other)` Copy constructor.
`protected`	`DenseVector(double[] values)` Does not defensively copy the input, used internally.
	`DenseVector(int size)`
	`DenseVector(int size, double value)`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`add(int index, double value)` Adds `value` to the element at `index`.
`DenseVector`	`add(SGDVector other)` Adds `other` to this vector, producing a new `DenseVector`.
`DenseVector`	`copy()` Returns a deep copy of this vector.
`static DenseVector`	`createDenseVector(double[] values)` Defensively copies the values before construction.
`static <T extends Output<T>> DenseVector`	`createDenseVector(Example<T> example, ImmutableFeatureMap featureInfo, boolean addBias)` Builds a `DenseVector` from an `Example`.
`double`	`dot(SGDVector other)` Calculates the dot product between this vector and `other`.
`boolean`	`equals(Object other)` Equals is defined mathematically, that is two SGDVectors are equal iff they have the same indices and the same values at those indices.
`double`	`euclideanDistance(SGDVector other)` The l2 or euclidean distance between this vector and the other vector.
`void`	`expNormalize(double total)` An optimisation for the exponential normalizer when you already know the normalization constant.
`void`	`fill(double value)` Fills this `DenseVector` with `value`.
`void`	`foreachInPlace(DoubleUnaryOperator f)` Applies a `DoubleUnaryOperator` elementwise to this `Tensor`.
`double`	`get(int index)` Gets an element from this vector.
`int[]`	`getShape()` Returns an int array specifying the shape of this `Tensor`.
`void`	`hadamardProductInPlace(Tensor other, DoubleUnaryOperator f)` Updates this `Tensor` with the Hadamard product (i.e., a term by term multiply) of this and `other`.
`int`	`hashCode()`
`int`	`indexOfMax()` Returns the index of the maximum value.
`void`	`intersectAndAddInPlace(Tensor other, DoubleUnaryOperator f)` Updates this `Tensor` by adding all the values from the intersection with `other`.
`VectorIterator`	`iterator()`
`double`	`l1Distance(SGDVector other)` The l1 or Manhattan distance between this vector and the other vector.
`double`	`maxValue()` Returns the maximum value.
`double`	`minValue()` Returns the minimum value.
`void`	`normalize(VectorNormalizer normalizer)` Normalizes the vector using the supplied vector normalizer.
`int`	`numActiveElements()` Returns the number of non-zero elements (on construction, an element could be set to zero and it would still remain active).
`double`	`oneNorm()` Calculates the Manhattan norm for this vector.
`Matrix`	`outer(SGDVector other)` Generates the matrix representing the outer product between the two vectors.
`double`	`reduce(double initialValue, DoubleUnaryOperator op, DoubleBinaryOperator reduction)` Performs a reduction from left to right of this vector.
`Tensor`	`reshape(int[] newShape)` Reshapes the Tensor to the supplied shape.
`DenseVector`	`scale(double coefficient)` Generates a new vector with each element scaled by `coefficient`.
`void`	`set(int index, double value)` Sets the `index` to the `value`.
`void`	`setElements(DenseVector other)` Sets all the elements of this vector to be the same as `other`.
`int`	`size()` Returns the dimensionality of this vector.
`SparseVector`	`sparsify()` Generates a `SparseVector` representation from this dense vector, removing all values with absolute value below `VectorTuple.DELTA`.
`SparseVector`	`sparsify(double tolerance)` Generates a `SparseVector` representation from this dense vector, removing all values with absolute value below the supplied tolerance.
`DenseVector`	`subtract(SGDVector other)` Subtracts `other` from this vector, producing a new `DenseVector`.
`double`	`sum()` Calculates the sum of this vector.
`double`	`sum(DoubleUnaryOperator f)`
`double[]`	`toArray()` Generates a copy of the values in this DenseVector.
`String`	`toString()`
`double`	`twoNorm()` Calculates the euclidean norm for this vector.
`double`	`variance(double mean)` Calculates the variance of this vector based on the supplied mean.

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

Methods inherited from interface org.tribuo.math.la.SGDVector
cosineDistance, cosineSimilarity, l2Distance, variance

Methods inherited from interface org.tribuo.math.la.Tensor
hadamardProductInPlace, intersectAndAddInPlace, scalarAddInPlace, scaleInPlace, shapeCheck, shapeSum

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

- Field Detail
  - elements
```
protected final double[] elements
```
- Constructor Detail
  - DenseVector
```
public DenseVector(int size)
```
  - DenseVector
```
public DenseVector(int size,
                   double value)
```
  - DenseVector
```
protected DenseVector(double[] values)
```
    Does not defensively copy the input, used internally.
    
    Parameters:
    
    values - The values of this dense vector.
  - DenseVector
```
protected DenseVector(DenseVector other)
```
    Copy constructor.
    
    Parameters:
    
    other - The vector to copy.
- Method Detail
  - createDenseVector
```
public static DenseVector createDenseVector(double[] values)
```
    Defensively copies the values before construction.
    
    Parameters:
    
    values - The values of this dense vector.
    
    Returns:
    
    A new dense vector.
  - createDenseVector
```
public static <T extends Output<T>> DenseVector createDenseVector(Example<T> example,
                                                                  ImmutableFeatureMap featureInfo,
                                                                  boolean addBias)
```
    Builds a DenseVector from an Example.
    Used in training and inference.
    Throws IllegalArgumentException if the Example contains NaN-valued features or if no features in this Example are present in the feature map..
    Unspecified features are set to zero.
    
    Type Parameters:
    
    T - The type parameter of the example.
    
    Parameters:
    
    example - The example to convert.
    
    featureInfo - The feature information, used to calculate the dimension of this DenseVector.
    
    addBias - Add a bias feature.
    
    Returns:
    
    A DenseVector representing the example's features.
  - toArray
```
public double[] toArray()
```
    Generates a copy of the values in this DenseVector.
    This implementation uses Arrays.copyOf, and should be overridden if the get function has been modified.
    
    Specified by:
    
    toArray in interface SGDVector
    
    Returns:
    
    A copy of the values in this DenseVector.
  - getShape
```
public int[] getShape()
```
    Description copied from interface: Tensor
    
    Returns an int array specifying the shape of this Tensor.
    
    Specified by:
    
    getShape in interface Tensor
    
    Returns:
    
    An int array.
  - reshape
```
public Tensor reshape(int[] newShape)
```
    Description copied from interface: Tensor
    
    Reshapes the Tensor to the supplied shape. Throws IllegalArgumentException if the shape isn't compatible.
    
    Specified by:
    
    reshape in interface Tensor
    
    Parameters:
    
    newShape - The desired shape.
    
    Returns:
    
    A Tensor of the desired shape.
  - copy
```
public DenseVector copy()
```
    Description copied from interface: SGDVector
    
    Returns a deep copy of this vector.
    
    Specified by:
    
    copy in interface SGDVector
    
    Returns:
    
    A copy of this vector.
  - size
```
public int size()
```
    Description copied from interface: SGDVector
    
    Returns the dimensionality of this vector.
    
    Specified by:
    
    size in interface SGDVector
    
    Returns:
    
    The dimensionality of the vector.
  - numActiveElements
```
public int numActiveElements()
```
    Description copied from interface: SGDVector
    
    Returns the number of non-zero elements (on construction, an element could be set to zero and it would still remain active).
    
    Specified by:
    
    numActiveElements in interface SGDVector
    
    Returns:
    
    The number of non-zero elements.
  - reduce
```
public double reduce(double initialValue,
                     DoubleUnaryOperator op,
                     DoubleBinaryOperator reduction)
```
    Performs a reduction from left to right of this vector.
    
    Specified by:
    
    reduce in interface SGDVector
    
    Parameters:
    
    initialValue - The initial value.
    
    op - The element wise operation to apply before reducing.
    
    reduction - The reduction operation (should be commutative).
    
    Returns:
    
    The reduced value.
  - equals
```
public boolean equals(Object other)
```
    Equals is defined mathematically, that is two SGDVectors are equal iff they have the same indices and the same values at those indices.
    
    Overrides:
    
    equals in class Object
    
    Parameters:
    
    other - Object to compare against.
    
    Returns:
    
    True if this vector and the other vector contain the same values in the same order.
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - add
```
public DenseVector add(SGDVector other)
```
    Adds other to this vector, producing a new DenseVector.
    
    Specified by:
    
    add in interface SGDVector
    
    Parameters:
    
    other - The vector to add.
    
    Returns:
    
    A new DenseVector where each element value = this.get(i) + other.get(i).
  - subtract
```
public DenseVector subtract(SGDVector other)
```
    Subtracts other from this vector, producing a new DenseVector.
    
    Specified by:
    
    subtract in interface SGDVector
    
    Parameters:
    
    other - The vector to subtract.
    
    Returns:
    
    A new DenseVector where each element value = this.get(i) - other.get(i).
  - intersectAndAddInPlace
```
public void intersectAndAddInPlace(Tensor other,
                                   DoubleUnaryOperator f)
```
    Description copied from interface: Tensor
    
    Updates this Tensor by adding all the values from the intersection with other.
    The function f is applied to all values from other before the addition.
    Each value is updated as value += f(otherValue).
    
    Specified by:
    
    intersectAndAddInPlace in interface Tensor
    
    Parameters:
    
    other - The other Tensor.
    
    f - A function to apply.
  - hadamardProductInPlace
```
public void hadamardProductInPlace(Tensor other,
                                   DoubleUnaryOperator f)
```
    Description copied from interface: Tensor
    
    Updates this Tensor with the Hadamard product (i.e., a term by term multiply) of this and other.
    The function f is applied to all values from other before the addition.
    Each value is updated as value *= f(otherValue).
    
    Specified by:
    
    hadamardProductInPlace in interface Tensor
    
    Parameters:
    
    other - The other Tensor.
    
    f - A function to apply.
  - foreachInPlace
```
public void foreachInPlace(DoubleUnaryOperator f)
```
    Description copied from interface: Tensor
    
    Applies a DoubleUnaryOperator elementwise to this Tensor.
    
    Specified by:
    
    foreachInPlace in interface Tensor
    
    Parameters:
    
    f - The function to apply.
  - scale
```
public DenseVector scale(double coefficient)
```
    Description copied from interface: SGDVector
    
    Generates a new vector with each element scaled by coefficient.
    
    Specified by:
    
    scale in interface SGDVector
    
    Parameters:
    
    coefficient - The coefficient to scale the elements by.
    
    Returns:
    
    A new SGDVector.
  - add
```
public void add(int index,
                double value)
```
    Description copied from interface: SGDVector
    
    Adds value to the element at index.
    
    Specified by:
    
    add in interface SGDVector
    
    Parameters:
    
    index - The index to update.
    
    value - The value to add.
  - dot
```
public double dot(SGDVector other)
```
    Description copied from interface: SGDVector
    
    Calculates the dot product between this vector and other.
    
    Specified by:
    
    dot in interface SGDVector
    
    Parameters:
    
    other - The other vector.
    
    Returns:
    
    The dot product.
  - outer
```
public Matrix outer(SGDVector other)
```
    Description copied from interface: SGDVector
    
    Generates the matrix representing the outer product between the two vectors.
    
    Specified by:
    
    outer in interface SGDVector
    
    Parameters:
    
    other - Another SGDVector
    
    Returns:
    
    The outer product Matrix.
  - sum
```
public double sum()
```
    Description copied from interface: SGDVector
    
    Calculates the sum of this vector.
    
    Specified by:
    
    sum in interface SGDVector
    
    Returns:
    
    The sum.
  - sum
```
public double sum(DoubleUnaryOperator f)
```
  - twoNorm
```
public double twoNorm()
```
    Description copied from interface: SGDVector
    
    Calculates the euclidean norm for this vector.
    
    Specified by:
    
    twoNorm in interface SGDVector
    
    Specified by:
    
    twoNorm in interface Tensor
    
    Returns:
    
    The euclidean norm.
  - oneNorm
```
public double oneNorm()
```
    Description copied from interface: SGDVector
    
    Calculates the Manhattan norm for this vector.
    
    Specified by:
    
    oneNorm in interface SGDVector
    
    Returns:
    
    The Manhattan norm.
  - get
```
public double get(int index)
```
    Description copied from interface: SGDVector
    
    Gets an element from this vector.
    
    Specified by:
    
    get in interface SGDVector
    
    Parameters:
    
    index - The index of the element.
    
    Returns:
    
    The value at that index.
  - set
```
public void set(int index,
                double value)
```
    Description copied from interface: SGDVector
    
    Sets the index to the value.
    
    Specified by:
    
    set in interface SGDVector
    
    Parameters:
    
    index - The index to set.
    
    value - The value to set it to.
  - setElements
```
public void setElements(DenseVector other)
```
    Sets all the elements of this vector to be the same as other.
    
    Parameters:
    
    other - The DenseVector to copy.
  - fill
```
public void fill(double value)
```
    Fills this DenseVector with value.
    
    Parameters:
    
    value - The value to store in this vector.
  - indexOfMax
```
public int indexOfMax()
```
    Description copied from interface: SGDVector
    
    Returns the index of the maximum value. Requires probing the array.
    
    Specified by:
    
    indexOfMax in interface SGDVector
    
    Returns:
    
    The index of the maximum value.
  - maxValue
```
public double maxValue()
```
    Description copied from interface: SGDVector
    
    Returns the maximum value. Requires probing the array.
    
    Specified by:
    
    maxValue in interface SGDVector
    
    Returns:
    
    The maximum value.
  - minValue
```
public double minValue()
```
    Description copied from interface: SGDVector
    
    Returns the minimum value. Requires probing the array.
    
    Specified by:
    
    minValue in interface SGDVector
    
    Returns:
    
    The minimum value.
  - normalize
```
public void normalize(VectorNormalizer normalizer)
```
    Description copied from interface: SGDVector
    
    Normalizes the vector using the supplied vector normalizer.
    
    Specified by:
    
    normalize in interface SGDVector
    
    Parameters:
    
    normalizer - The kind of normalization to apply.
  - expNormalize
```
public void expNormalize(double total)
```
    An optimisation for the exponential normalizer when you already know the normalization constant. Used in the CRF.
    
    Parameters:
    
    total - The normalization constant.
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - variance
```
public double variance(double mean)
```
    Description copied from interface: SGDVector
    
    Calculates the variance of this vector based on the supplied mean.
    
    Specified by:
    
    variance in interface SGDVector
    
    Parameters:
    
    mean - The mean of the vector.
    
    Returns:
    
    The variance of the vector.
  - iterator
```
public VectorIterator iterator()
```
    Specified by:
    
    iterator in interface Iterable<VectorTuple>
  - sparsify
```
public SparseVector sparsify()
```
    Generates a SparseVector representation from this dense vector, removing all values with absolute value below VectorTuple.DELTA.
    
    Returns:
    
    A SparseVector.
  - sparsify
```
public SparseVector sparsify(double tolerance)
```
    Generates a SparseVector representation from this dense vector, removing all values with absolute value below the supplied tolerance.
    
    Parameters:
    
    tolerance - The threshold below which to set a value to zero.
    
    Returns:
    
    A SparseVector.
  - euclideanDistance
```
public double euclideanDistance(SGDVector other)
```
    The l2 or euclidean distance between this vector and the other vector.
    
    Specified by:
    
    euclideanDistance in interface SGDVector
    
    Parameters:
    
    other - The other vector.
    
    Returns:
    
    The euclidean distance between them.
  - l1Distance
```
public double l1Distance(SGDVector other)
```
    The l1 or Manhattan distance between this vector and the other vector.
    
    Specified by:
    
    l1Distance in interface SGDVector
    
    Parameters:
    
    other - The other vector.
    
    Returns:
    
    The l1 distance.

Class DenseVector

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface org.tribuo.math.la.SGDVector

Methods inherited from interface org.tribuo.math.la.Tensor

Methods inherited from interface java.lang.Iterable

Field Detail

elements

Constructor Detail

DenseVector

DenseVector

DenseVector

DenseVector

Method Detail

createDenseVector

createDenseVector

toArray

getShape

reshape

copy

size

numActiveElements

reduce

equals

hashCode

add

subtract

intersectAndAddInPlace

hadamardProductInPlace

foreachInPlace

scale

add

dot

outer

sum

sum

twoNorm

oneNorm

get

set

setElements

fill

indexOfMax

maxValue

minValue

normalize

expNormalize

toString

variance

iterator

sparsify

sparsify

euclideanDistance

l1Distance