VectorFactory (Cognitive Foundry)

java.lang.Object
- gov.sandia.cognition.math.matrix.VectorFactory<VectorType>

Type Parameters:

VectorType - Type of Vector created by this factory.

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

CustomDenseVectorFactory, CustomSparseVectorFactory, DenseVectorFactoryMTJ, SparseVectorFactory
```
public abstract class VectorFactory<VectorType extends Vector>
extends java.lang.Object
implements java.io.Serializable
```
Abstract factory for creating Vector objects.

Since:

1.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type	Field and Description
`protected static VectorFactory<? extends Vector>`	`DEFAULT_DENSE_INSTANCE` The default `VectorFactory` instance.
`protected static SparseVectorFactory<? extends Vector>`	`DEFAULT_SPARSE_INSTANCE` The default SparseVectorFactory instance.

Constructor Summary

Constructors
Modifier Constructor and Description

protected VectorFactory()
Creates a new VectorFactory.

Constructors
Modifier	Constructor and Description
`protected`	`VectorFactory()` Creates a new `VectorFactory`.

Method Summary

All Methods Static Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method and Description
`VectorType`	`copyArray(double[] values)` Copies the values from the array into the Vector
`VectorType`	`copyArray(int dimensionality, int[] indices, double[] values)` Creates a new vector of the given dimensionality by setting the values at the given indices.
`VectorType`	`copyMap(int dimensionality, java.util.Map<java.lang.Integer,? extends java.lang.Number> map)` Creates a vector from the given map of indices to values.
`VectorType`	`copyValues(java.util.Collection<? extends java.lang.Number> values)` Copies the values from the given Collection.
`VectorType`	`copyValues(double... values)` Copies the values from the given doubles into a Vector
`abstract VectorType`	`copyVector(Vector m)` Creates a deep copy new Vector given another, argument is unchanged
`VectorType`	`createGaussianRandom(int dimensionality, java.util.Random random)` Creates a vector with random values sampled from a Gaussian distribution with mean 0 and variance 1.
`VectorType`	`createUniformRandom(int dim, double min, double max, java.util.Random random)` Creates a Vector with random values for the entries, uniformly distributed between "min" and "max"
`VectorType`	`createUniformRandom(int dimensionality, java.util.Random random)` Creates a vector with random values for the entries uniformly sampled between 0 and 1.
`abstract VectorType`	`createVector(int dim)` Creates an empty Vector of the specified dimension, all elements must be all zeros!
`VectorType`	`createVector(int dimensionality, double initialValue)` Creates a Vector with the given initial value for all elements.
`Vector1D`	`createVector1D()` Creates a one-dimensional zero vector: (0.0).
`abstract Vector1D`	`createVector1D(double x)` Creates a one-dimensional vector with the given x coordinate: (x).
`Vector2D`	`createVector2D()` Creates a two-dimensional zero vector: (0.0, 0.0).
`abstract Vector2D`	`createVector2D(double x, double y)` Creates a two-dimensional vector with the given x and y coordinates: (x, y).
`Vector3D`	`createVector3D()` Creates a three-dimensional zero vector: (0.0, 0.0, 0.0).
`abstract Vector3D`	`createVector3D(double x, double y, double z)` Creates a three-dimensional vector with the given x, y, and z coordinates: (x, y, z).
`abstract VectorType`	`createVectorCapacity(int dimensionality, int initialCapacity)` Creates a new, empty vector with the given dimensionality and expected number of nonzero elements.
`abstract MatrixFactory<?>`	`getAssociatedMatrixFactory()` Gets the matrix factory implementation associated with this vector factory.
`static VectorFactory<? extends Vector>`	`getDefault()` Gets the default implementation of the `VectorFactory`.
`static VectorFactory<? extends Vector>`	`getDenseDefault()` Gets the default implementation of `VectorFactory` for dense vectors.
`static SparseVectorFactory<? extends Vector>`	`getSparseDefault()` Gets the default implementation of the `SparseVectorFactory`.

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

- Field Detail
  - DEFAULT_DENSE_INSTANCE
```
protected static final VectorFactory<? extends Vector> DEFAULT_DENSE_INSTANCE
```
    The default VectorFactory instance.
  - DEFAULT_SPARSE_INSTANCE
```
protected static final SparseVectorFactory<? extends Vector> DEFAULT_SPARSE_INSTANCE
```
    The default SparseVectorFactory instance.
- Constructor Detail
  - VectorFactory
```
protected VectorFactory()
```
    Creates a new VectorFactory.
- Method Detail
  - getDefault
```
public static VectorFactory<? extends Vector> getDefault()
```
    Gets the default implementation of the VectorFactory.
    
    Returns:
    
    The default VectorFactory implementation.
  - getDenseDefault
```
public static VectorFactory<? extends Vector> getDenseDefault()
```
    Gets the default implementation of VectorFactory for dense vectors.
    
    Returns:
    
    The default dense vector factory;
  - getSparseDefault
```
public static SparseVectorFactory<? extends Vector> getSparseDefault()
```
    Gets the default implementation of the SparseVectorFactory.
    
    Returns:
    
    The default SparseVectorFactory implementation.
  - copyVector
```
public abstract VectorType copyVector(Vector m)
```
    Creates a deep copy new Vector given another, argument is unchanged
    
    Parameters:
    
    m - Vector to copy
    
    Returns:
    
    Deep copy of the given Vector
  - copyArray
```
public VectorType copyArray(double[] values)
```
    Copies the values from the array into the Vector
    
    Parameters:
    
    values - Values to copy
    
    Returns:
    
    Vector with same dimension and values as "values"
  - copyValues
```
public VectorType copyValues(double... values)
```
    Copies the values from the given doubles into a Vector
    
    Parameters:
    
    values - Values to copy
    
    Returns:
    
    Vector with same dimension and values as "values"
  - copyValues
```
public VectorType copyValues(java.util.Collection<? extends java.lang.Number> values)
```
    Copies the values from the given Collection. It does this by iterating through collection and initializing by iterating through them in the order specified by the collection. Thus, this should probably not be used with collections that do not have a very well determined iteration order, like a HashSet (as such, LinkedHashSet may be a better option to preserve insertion order).
    
    Parameters:
    
    values - Values to create a vector from. Cannot be null and cannot contain null values.
    
    Returns:
    
    A vector of dimensionality equal to the size of the given collection and whose values are initialized to the values in the collection in order of iteration.
  - createVector
```
public abstract VectorType createVector(int dim)
```
    Creates an empty Vector of the specified dimension, all elements must be all zeros!
    
    Parameters:
    
    dim - number of elements in the Vector
    
    Returns:
    
    A new Vector or the given dimensionality with all zero elements.
  - createVector1D
```
public Vector1D createVector1D()
```
    Creates a one-dimensional zero vector: (0.0).
    
    Returns:
    
    A one-dimensional zero vector.
  - createVector1D
```
public abstract Vector1D createVector1D(double x)
```
    Creates a one-dimensional vector with the given x coordinate: (x). This is useful mainly for creating a vector wrapper for the double.
    
    Parameters:
    
    x - The x coordinate.
    
    Returns:
    
    A new one-dimensional vector with the given coordinate.
  - createVector2D
```
public Vector2D createVector2D()
```
    Creates a two-dimensional zero vector: (0.0, 0.0).
    
    Returns:
    
    A two-dimensional zero vector.
  - createVector2D
```
public abstract Vector2D createVector2D(double x,
                                        double y)
```
    Creates a two-dimensional vector with the given x and y coordinates: (x, y).
    
    Parameters:
    
    x - The x coordinate.
    
    y - The y coordinate.
    
    Returns:
    
    A new two-dimensional vector with the given coordinates.
  - createVector3D
```
public Vector3D createVector3D()
```
    Creates a three-dimensional zero vector: (0.0, 0.0, 0.0).
    
    Returns:
    
    A three-dimensional zero vector.
  - createVector3D
```
public abstract Vector3D createVector3D(double x,
                                        double y,
                                        double z)
```
    Creates a three-dimensional vector with the given x, y, and z coordinates: (x, y, z).
    
    Parameters:
    
    x - The x coordinate.
    
    y - The y coordinate.
    
    z - The z coordinate.
    
    Returns:
    
    A new three-dimensional vector with the given coordinates.
  - createVectorCapacity
```
public abstract VectorType createVectorCapacity(int dimensionality,
                                                int initialCapacity)
```
    Creates a new, empty vector with the given dimensionality and expected number of nonzero elements.
    
    Parameters:
    
    dimensionality - The dimensionality for the vector to create.
    
    initialCapacity - The expected initial number of nonzero elements of the vector to create.
    
    Returns:
    
    A new vector with the given dimensionality and capacity for at least the given number of nonzeros.
  - createUniformRandom
```
public VectorType createUniformRandom(int dimensionality,
                                      java.util.Random random)
```
    Creates a vector with random values for the entries uniformly sampled between 0 and 1.
    
    Parameters:
    
    dimensionality - The number of dimensions in the vector.
    
    random - The random number generator to use.
    
    Returns:
    
    A new Vector with uniform random values of the given dimension.
  - createUniformRandom
```
public VectorType createUniformRandom(int dim,
                                      double min,
                                      double max,
                                      java.util.Random random)
```
    Creates a Vector with random values for the entries, uniformly distributed between "min" and "max"
    
    Parameters:
    
    dim - number of elements in the Vector
    
    min - minimum range of the uniform distribution
    
    max - maximum range of the uniform distribution
    
    random - The random number generator.
    
    Returns:
    
    Vector with random values for the entries, uniformly distributed between "min" and "max"
  - createGaussianRandom
```
public VectorType createGaussianRandom(int dimensionality,
                                       java.util.Random random)
```
    Creates a vector with random values sampled from a Gaussian distribution with mean 0 and variance 1.
    
    Parameters:
    
    dimensionality - The number of dimensions in the vector.
    
    random - The random number generator to use.
    
    Returns:
    
    A new Vector of the given dimension with values sampled from a standard Gaussian distribution.
  - createVector
```
public VectorType createVector(int dimensionality,
                               double initialValue)
```
    Creates a Vector with the given initial value for all elements.
    
    Parameters:
    
    dimensionality - The number of elements for the vector.
    
    initialValue - Initial value to set all elements to
    
    Returns:
    
    Vector of the given dimensions, with all value equal to initialValue
  - copyArray
```
public VectorType copyArray(int dimensionality,
                            int[] indices,
                            double[] values)
```
    Creates a new vector of the given dimensionality by setting the values at the given indices.
    
    Parameters:
    
    dimensionality - The dimensionality of the vector to create.
    
    indices - The array of indices of values to set. Must be the same length as the values array. The indices must be between 0 and the dimensionality - 1.
    
    values - The array of values to set. Must be the same length as the indices array.
    
    Returns:
    
    A new vector with the given indices set to their corresponding values.
  - copyMap
```
public VectorType copyMap(int dimensionality,
                          java.util.Map<java.lang.Integer,? extends java.lang.Number> map)
```
    Creates a vector from the given map of indices to values.
    
    Parameters:
    
    dimensionality - The dimensionality of the vector. Cannot be negative.
    
    map - The map of indices to values to fill in the vector. All indices must be 0-based and between 0 (inclusive) and dimensionality (exclusive). Cannot be null.
    
    Returns:
    
    A new vector with elements initialized to the ones in the map.
  - getAssociatedMatrixFactory
```
public abstract MatrixFactory<?> getAssociatedMatrixFactory()
```
    Gets the matrix factory implementation associated with this vector factory.
    
    Returns:
    
    The associated matrix factory.

Class VectorFactory<VectorType extends Vector>

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

DEFAULT_DENSE_INSTANCE

DEFAULT_SPARSE_INSTANCE

Constructor Detail

VectorFactory

Method Detail

getDefault

getDenseDefault

getSparseDefault

copyVector

copyArray

copyValues

copyValues

createVector

createVector1D

createVector1D

createVector2D

createVector2D

createVector3D

createVector3D

createVectorCapacity

createUniformRandom

createUniformRandom

createGaussianRandom

createVector

copyArray

copyMap

getAssociatedMatrixFactory