Package org.flag4j.rng

Class RandomTensor

java.lang.Object

org.flag4j.rng.RandomTensor

public class RandomTensor
extends Object

An instance of this class is used for generating streams of pseudorandom tensors, matrices, and vectors.

Field Summary

Fields

Modifier and Type	Field	Description
private final RandomCNumber	COMPLEX_RNG	Complex pseudorandom number generator.
private final RandomArray	RAND_ARRAY

Constructor Summary

Constructors

Constructor	Description
RandomTensor()	Constructs a new pseudorandom tensor generator with a seed which is unlikely to be the same as other from any other invocation of this constructor.
RandomTensor(long seed)	Constructs a pseudorandom tensor generator with a specified seed.

Method Summary

Modifier and Type	Method	Description
Matrix	geRandomTrilMatrix(int size, int min, int max)	Gets a pseudorandom lower triangular matrix of the specified size.
CMatrix	randnCMatrix(int rows, int cols)	Generates a matrix filled with pseudorandom complex values with magnitudes sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.
CMatrix	randnCMatrix(int rows, int cols, double mean, double std)	Generates a matrix filled with pseudorandom complex values with magnitudes sampled from a normal distribution with a specified mean and standard deviation.
CMatrix	randnCMatrix(Shape shape)	Generates a matrix filled with pseudorandom complex values with magnitudes sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.
CMatrix	randnCMatrix(Shape shape, double mean, double std)	Generates a matrix filled with pseudorandom values sampled from a normal distribution with a specified mean and standard deviation.
CTensor	randnCTensor(Shape shape)	Generates a tensor filled with pseudorandom values sampled from a normal distribution with mean of 0.0 and standard deviation of 1.0.
CTensor	randnCTensor(Shape shape, double mean, double std)	Generates a tensor filled with pseudorandom values sampled from a normal distribution with specified mean and standard deviation.
CVector	randnCVector(int size)	Generates a vector filled with pseudorandom values with magnitudes sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.
CVector	randnCVector(int size, double mean, double std)	Generates a vector filled with pseudorandom values with magnitudes sampled from a normal distribution with specified mean and standard deviation.
Matrix	randnMatrix(int rows, int cols)	Generates a matrix filled with pseudorandom values sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.
Matrix	randnMatrix(int rows, int cols, double mean, double std)	Generates a matrix filled with pseudorandom values sampled from a normal distribution with a specified mean and standard deviation.
Matrix	randnMatrix(Shape shape)	Generates a matrix filled with pseudorandom values sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.
Matrix	randnMatrix(Shape shape, double mean, double std)	Generates a matrix filled with pseudorandom values sampled from a normal distribution with a specified mean and standard deviation.
Tensor	randnTensor(Shape shape)	Generates a tensor filled with pseudorandom values sampled from a normal distribution with mean of 0.0 and standard deviation of 1.0.
Tensor	randnTensor(Shape shape, double mean, double std)	Generates a tensor filled with pseudorandom values sampled from a normal distribution with specified mean and standard deviation.
Vector	randnVector(int size)	Generates a vector filled with pseudorandom values sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.
Vector	randnVector(int size, double mean, double std)	Generates a vector filled with pseudorandom values sampled from a normal distribution with specified mean and standard deviation.
CMatrix	randomCMatrix(int rows, int cols)	Generates a matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).
CMatrix	randomCMatrix(int rows, int cols, double min, double max)	Generates a matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [min, max).
CMatrix	randomCMatrix(Shape shape)	Generates a matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).
CMatrix	randomCMatrix(Shape shape, double min, double max)	Generates a matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [min, max).
CooMatrix	randomCooMatrix(int rows, int cols, double min, double max, double sparsity)	Generates a random sparse matrix with the specified sparsity.
CooMatrix	randomCooMatrix(int rows, int cols, double min, double max, int numNonZeroEntries)	Generates a random sparse matrix with the specified number of non-zero entries.
CooMatrix	randomCooMatrix(Shape shape, double min, double max, double sparsity)	Generates a random sparse matrix with the specified sparsity.
CooMatrix	randomCooMatrix(Shape shape, double min, double max, int numNonZeroEntries)	Generates a random sparse matrix with the specified number of non-zero entries.
CsrMatrix	randomCsrMatrix(int rows, int cols, double min, double max, double sparsity)	Generates a random sparse matrix with the specified sparsity.
CsrMatrix	randomCsrMatrix(int rows, int cols, double min, double max, int numNonZeroEntries)	Generates a random sparse matrix with the specified number of non-zero entries.
CsrMatrix	randomCsrMatrix(Shape shape, double min, double max, double sparsity)	Generates a random sparse matrix with the specified sparsity.
CsrMatrix	randomCsrMatrix(Shape shape, double min, double max, int numNonZeroEntries)	Generates a random sparse matrix with the specified number of non-zero entries.
CTensor	randomCTensor(Shape shape)	Generates a tensor filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).
CTensor	randomCTensor(Shape shape, double min, double max)	Generates a tensor filled with pseudorandom values with magnitudes uniformly distributed in [min, max).
CVector	randomCVector(int size)	Generates a vector filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).
CVector	randomCVector(int size, double min, double max)	Generates a vector filled with pseudorandom values with magnitudes uniformly distributed in [min, max).
Matrix	randomMatrix(int rows, int cols)	Generates a matrix filled with pseudorandom values uniformly distributed in [0, 1).
Matrix	randomMatrix(int rows, int cols, double min, double max)	Generates a matrix filled with pseudorandom values uniformly distributed in [min, max).
Matrix	randomMatrix(Shape shape)	Generates a matrix filled with pseudorandom values uniformly distributed in [0, 1).
Matrix	randomMatrix(Shape shape, double min, double max)	Generates a matrix filled with pseudorandom values uniformly distributed in [min, max).
Matrix	randomOrthogonalMatrix(int size)	Gets a pseudorandom orthogonal matrix.
CooCMatrix	randomSparseCMatrix(int rows, int cols, double min, double max, double sparsity)	Generates a random sparse matrix with the specified sparsity.
CooCMatrix	randomSparseCMatrix(int rows, int cols, double min, double max, int numNonZeroEntries)	Generates a random sparse matrix with the specified number of non-zero entries.
CooCMatrix	randomSparseCMatrix(Shape shape, double min, double max, double sparsity)	Generates a random sparse matrix with the specified sparsity.
CooCMatrix	randomSparseCMatrix(Shape shape, double min, double max, int numNonZeroEntries)	Generates a random sparse matrix with the specified number of non-zero entries.
CooMatrix	randomSymmetricCooMatrix(int size, int min, int max, double sparsity)	Generates a symmetric COO matrix filled with pseudorandom values uniformly distributed in [min, max).
CsrMatrix	randomSymmetricCsrMatrix(int size, int min, int max, double sparsity)	Generates a symmetric CSR matrix filled with pseudorandom values uniformly distributed in [min, max).
Matrix	randomSymmetricMatrix(int size)	Generates a symmetric matrix filled with pseudorandom values uniformly distributed in [0, 1).
Tensor	randomTensor(Shape shape)	Generates a tensor filled with pseudorandom values uniformly distributed in [0, 1).
Tensor	randomTensor(Shape shape, double min, double max)	Generates a tensor filled with pseudorandom values uniformly distributed in [min, max).
Matrix	randomTriuMatrix(int size, int min, int max)	Gets a pseudorandom upper triangular matrix of the specified size.
CMatrix	randomUnitaryMatrix(int size)	Gets a pseudorandom unitary matrix.
Vector	randomVector(int size)	Generates a vector filled with pseudorandom values uniformly distributed in [0, 1).
Vector	randomVector(int size, double min, double max)	Generates a vector filled with pseudorandom values uniformly distributed in [min, max).

Methods inherited from class java.lang.Object

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

Field Details

COMPLEX_RNG

private final RandomCNumber COMPLEX_RNG

Complex pseudorandom number generator.

RAND_ARRAY

private final RandomArray RAND_ARRAY

Constructor Details

RandomTensor

public RandomTensor()

Constructs a new pseudorandom tensor generator with a seed which is unlikely to be the same as other from any other invocation of this constructor.

RandomTensor

public RandomTensor(long seed)

Constructs a pseudorandom tensor generator with a specified seed. Use this constructor for reproducible results.

Parameters:

seed - Seed of the pseudorandom tensor generator.

Method Details

randomTensor

public Tensor randomTensor(Shape shape)

Generates a tensor filled with pseudorandom values uniformly distributed in [0, 1).

Parameters:

shape - Shape of the tensor.

Returns:

A tensor filled with pseudorandom values uniformly distributed in [0, 1).

randomTensor

public Tensor randomTensor(Shape shape,
 double min,
 double max)

Generates a tensor filled with pseudorandom values uniformly distributed in [min, max).

Parameters:

shape - Shape of the tensor.

min - Minimum value for the uniform distribution.

max - Maximum value for the uniform distribution.

Returns:

A tensor filled with pseudorandom values uniformly distributed in [min, max).

Throws:

IllegalArgumentException - If max is less than min.

randnTensor

public Tensor randnTensor(Shape shape)

Generates a tensor filled with pseudorandom values sampled from a normal distribution with mean of 0.0 and standard deviation of 1.0.

Parameters:

shape - Shape of the tensor.

Returns:

A tensor filled with pseudorandom values sampled from a normal distribution with mean of 0.0 and standard deviation of 1.0.

randnTensor

public Tensor randnTensor(Shape shape,
 double mean,
 double std)

Generates a tensor filled with pseudorandom values sampled from a normal distribution with specified mean and standard deviation.

Parameters:

shape - Shape of the tensor.

mean - Mean of the normal distribution to sample from.

std - Standard deviation of normal distribution to sample from.

Returns:

A tensor filled with pseudorandom values sampled from a normal distribution with specified mean and standard deviation.

Throws:

IllegalArgumentException - If standard deviation is negative.

randomCTensor

public CTensor randomCTensor(Shape shape)

Generates a tensor filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).

Parameters:

shape - Shape of the tensor.

Returns:

A tensor filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).

randomCTensor

public CTensor randomCTensor(Shape shape,
 double min,
 double max)

Generates a tensor filled with pseudorandom values with magnitudes uniformly distributed in [min, max).

Parameters:

shape - Shape of the tensor.

min - Minimum value for the uniform distribution from which to sample magnitude.

max - Maximum value for the uniform distribution from which to sample magnitude.

Returns:

A tensor filled with pseudorandom values with magnitudes uniformly distributed in [min, max)

Throws:

IllegalArgumentException - If min is negative or if max is less than min.

randnCTensor

public CTensor randnCTensor(Shape shape)

Generates a tensor filled with pseudorandom values sampled from a normal distribution with mean of 0.0 and standard deviation of 1.0.

Parameters:

shape - Shape of the tensor.

Returns:

A tensor filled with pseudorandom values sampled from a normal distribution with mean of 0.0 and standard deviation of 1.0.

randnCTensor

public CTensor randnCTensor(Shape shape,
 double mean,
 double std)

Generates a tensor filled with pseudorandom values sampled from a normal distribution with specified mean and standard deviation.

Parameters:

shape - Shape of the tensor.

mean - Mean of the normal distribution to sample from.

std - Standard deviation of normal distribution to sample from.

Returns:

A tensor filled with pseudorandom values sampled from a normal distribution with specified mean and standard deviation.

Throws:

IllegalArgumentException - If standard deviation is negative.

randomVector

public Vector randomVector(int size)

Generates a vector filled with pseudorandom values uniformly distributed in [0, 1).

Parameters:

size - Size of the vector to generate.

Returns:

A vector filled with pseudorandom values uniformly distributed in [0, 1).

randomVector

public Vector randomVector(int size,
 double min,
 double max)

Generates a vector filled with pseudorandom values uniformly distributed in [min, max).

Parameters:

size - Size of the vector to generate.

Returns:

A vector filled with pseudorandom values uniformly distributed in [min, max).

Throws:

IllegalArgumentException - If max is less than min.

randnVector

public Vector randnVector(int size)

Generates a vector filled with pseudorandom values sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

Parameters:

size - Size of the vector to generate.

Returns:

A vector filled with pseudorandom values sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

randnVector

public Vector randnVector(int size,
 double mean,
 double std)

Generates a vector filled with pseudorandom values sampled from a normal distribution with specified mean and standard deviation.

Parameters:

size - Size of the vector to generate.

Returns:

A vector filled with pseudorandom values sampled from a normal distribution with specified mean and standard deviation.

Throws:

IllegalArgumentException - If the standard deviation is negative.

randomCVector

public CVector randomCVector(int size)

Generates a vector filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).

Parameters:

size - Size of the vector to generate.

Returns:

A vector filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).

randomCVector

public CVector randomCVector(int size,
 double min,
 double max)

Generates a vector filled with pseudorandom values with magnitudes uniformly distributed in [min, max).

Parameters:

size - Size of the vector to generate.

Returns:

A vector filled with pseudorandom values with magnitudes uniformly distributed in [min, max).

Throws:

IllegalArgumentException - If min is negative or if max is less than min.

randnCVector

public CVector randnCVector(int size)

Generates a vector filled with pseudorandom values with magnitudes sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

Parameters:

size - Size of the vector to generate.

Returns:

A vector filled with pseudorandom values with magnitudes sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

randnCVector

public CVector randnCVector(int size,
 double mean,
 double std)

Generates a vector filled with pseudorandom values with magnitudes sampled from a normal distribution with specified mean and standard deviation.

Parameters:

size - Size of the vector to generate.

Returns:

A vector filled with pseudorandom values with magnitudes sampled from a normal distribution with specified mean * and standard deviation.

Throws:

IllegalArgumentException - If the standard deviation is negative.

randomMatrix

public Matrix randomMatrix(int rows,
 int cols)

Generates a matrix filled with pseudorandom values uniformly distributed in [0, 1).

Parameters:

rows - Number of rows in the resulting matrix.

cols - Number of columns in the resulting matrix.

Returns:

A matrix filled with pseudorandom values uniformly distributed in [0, 1).

randomMatrix

public Matrix randomMatrix(Shape shape)

Generates a matrix filled with pseudorandom values uniformly distributed in [0, 1).

Parameters:

shape - Shape of the resulting matrix. Must be of rank 2.

Returns:

A matrix filled with pseudorandom values uniformly distributed in [0, 1).

Throws:

IllegalArgumentException - If the shape is not of rank 2.

randomMatrix

public Matrix randomMatrix(int rows,
 int cols,
 double min,
 double max)

Generates a matrix filled with pseudorandom values uniformly distributed in [min, max).

Parameters:

rows - Number of rows in the resulting matrix.

cols - Number of columns in the resulting matrix.

min - Minimum value of uniform distribution to sample from (inclusive).

max - Maximum value of uniform distribution to sample from (exclusive).

Returns:

A matrix filled with pseudorandom values uniformly distributed in [min, max).

Throws:

IllegalArgumentException - If max is less than min.

randomMatrix

public Matrix randomMatrix(Shape shape,
 double min,
 double max)

Generates a matrix filled with pseudorandom values uniformly distributed in [min, max).

Parameters:

shape - Shape of the resulting matrix. Must be of rank 2.

min - Minimum value of uniform distribution to sample from (inclusive).

max - Maximum value of uniform distribution to sample from (exclusive).

Returns:

A matrix filled with pseudorandom values uniformly distributed in [min, max).

Throws:

IllegalArgumentException - If max is less than min.

IllegalArgumentException - If shape is not of rank 2.

randomCooMatrix

public CooMatrix randomCooMatrix(int rows,
 int cols,
 double min,
 double max,
 double sparsity)

Generates a random sparse matrix with the specified sparsity. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

rows - Number of rows in the sparse matrix.

cols - Number of columns in the sparse matrix.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

sparsity - Desired sparsity of the resulting matrix. i.e. the percent of values which are zero. Must be a value in [0.0, 1.0].

Returns:

A sparse matrix with sparsity approximately equal to sparsity filled with random values uniformly distributed in [min, max).

randomCooMatrix

public CooMatrix randomCooMatrix(Shape shape,
 double min,
 double max,
 double sparsity)

Generates a random sparse matrix with the specified sparsity. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

shape - Shape of the sparse matrix to generate.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

sparsity - Desired sparsity of the resulting matrix. i.e. the percent of values which are zero. Must be a value in [0.0, 1.0].

Returns:

A sparse matrix with sparsity approximately equal to sparsity filled with random values uniformly distributed in [min, max).

randomCooMatrix

public CooMatrix randomCooMatrix(int rows,
 int cols,
 double min,
 double max,
 int numNonZeroEntries)

Generates a random sparse matrix with the specified number of non-zero entries. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

rows - Number of rows in the random sparse matrix.

cols - Number of columns in the random sparse matrix.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

numNonZeroEntries - Desired number of non-zero entries int the random sparse matrix.

Returns:

A sparse matrix filled with the specified number of non-zero entries uniformly distributed in [min, max).

randomCooMatrix

public CooMatrix randomCooMatrix(Shape shape,
 double min,
 double max,
 int numNonZeroEntries)

Generates a random sparse matrix with the specified number of non-zero entries. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

shape - Shape of the sparse matrix to generate.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

numNonZeroEntries - Desired number of non-zero entries int the random sparse matrix.

Returns:

A sparse matrix filled with the specified number of non-zero entries uniformly distributed in [min, max).

randomCsrMatrix

public CsrMatrix randomCsrMatrix(int rows,
 int cols,
 double min,
 double max,
 double sparsity)

Generates a random sparse matrix with the specified sparsity. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

rows - Number of rows in the sparse matrix.

cols - Number of columns in the sparse matrix.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

sparsity - Desired sparsity of the resulting matrix. i.e. the percent of values which are zero. Must be a value in [0.0, 1.0].

Returns:

A sparse matrix with sparsity approximately equal to sparsity filled with random values uniformly distributed in [min, max).

randomCsrMatrix

public CsrMatrix randomCsrMatrix(Shape shape,
 double min,
 double max,
 double sparsity)

Generates a random sparse matrix with the specified sparsity. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

shape - Shape of the sparse matrix to generate.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

sparsity - Desired sparsity of the resulting matrix. i.e. the percent of values which are zero. Must be a value in [0.0, 1.0].

Returns:

A sparse matrix with sparsity approximately equal to sparsity filled with random values uniformly distributed in [min, max).

randomCsrMatrix

public CsrMatrix randomCsrMatrix(int rows,
 int cols,
 double min,
 double max,
 int numNonZeroEntries)

Generates a random sparse matrix with the specified number of non-zero entries. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

rows - Number of rows in the random sparse matrix.

cols - Number of columns in the random sparse matrix.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

numNonZeroEntries - Desired number of non-zero entries int the random sparse matrix.

Returns:

A sparse matrix filled with the specified number of non-zero entries uniformly distributed in [min, max).

randomCsrMatrix

public CsrMatrix randomCsrMatrix(Shape shape,
 double min,
 double max,
 int numNonZeroEntries)

Generates a random sparse matrix with the specified number of non-zero entries. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

shape - Shape of the sparse matrix to generate.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

numNonZeroEntries - Desired number of non-zero entries int the random sparse matrix.

Returns:

A sparse matrix filled with the specified number of non-zero entries uniformly distributed in [min, max).

randnMatrix

public Matrix randnMatrix(int rows,
 int cols)

Generates a matrix filled with pseudorandom values sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

Parameters:

rows - The number of rows in the resulting matrix.

cols - The number of columns in the resulting matrix.

Returns:

A matrix filled with pseudorandom values sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

randnMatrix

public Matrix randnMatrix(Shape shape)

Generates a matrix filled with pseudorandom values sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

Parameters:

shape - Shape of the resulting matrix.

Returns:

A matrix filled with pseudorandom values sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

randnMatrix

public Matrix randnMatrix(int rows,
 int cols,
 double mean,
 double std)

Generates a matrix filled with pseudorandom values sampled from a normal distribution with a specified mean and standard deviation.

Parameters:

rows - The number of rows in the resulting matrix.

cols - The number of columns in the resulting matrix.

mean - Mean of the normal distribution from which values are sampled.

std - Standard deviation of the normal distribution from which values are sampled.

Returns:

A matrix filled with pseudorandom values sampled from a normal distribution with a specified mean and standard deviation.

Throws:

IllegalArgumentException - If the standard deviation is negative.

randnMatrix

public Matrix randnMatrix(Shape shape,
 double mean,
 double std)

Generates a matrix filled with pseudorandom values sampled from a normal distribution with a specified mean and standard deviation.

Parameters:

shape - Shape of the resulting matrix.

mean - Mean of the normal distribution from which values are sampled.

std - Standard deviation of the normal distribution from which values are sampled.

Returns:

A matrix filled with pseudorandom values sampled from a normal distribution with a specified mean and standard deviation.

Throws:

IllegalArgumentException - If the standard deviation is negative.

randomSymmetricMatrix

public Matrix randomSymmetricMatrix(int size)

Generates a symmetric matrix filled with pseudorandom values uniformly distributed in [0, 1).

Parameters:

size - Number of rows and columns in the resulting matrix (the result will be a square matrix).

Returns:

A symmetric matrix filled with pseudorandom values uniformly distributed in [0, 1).

randomSymmetricCooMatrix

public CooMatrix randomSymmetricCooMatrix(int size,
 int min,
 int max,
 double sparsity)

Generates a symmetric COO matrix filled with pseudorandom values uniformly distributed in [min, max).

Parameters:

size - Number of rows and columns in the resulting matrix (the result will be a square matrix).

min - Minimum value in uniform distribution.

max - Maximum value in uniform distribution.

sparsity - Desired sparsity of the resulting matrix. i.e. the percent of values which are zero. Must be a value in [0.0, 1.0]. The true sparsity may slightly differ to ensure the matrix is symmetric.

Returns:

A symmetric matrix filled with pseudorandom values uniformly distributed in [min, max).

Throws:

IllegalArgumentException - If sparsity is not in the range [0.0, 1.0].

randomSymmetricCsrMatrix

public CsrMatrix randomSymmetricCsrMatrix(int size,
 int min,
 int max,
 double sparsity)

Generates a symmetric CSR matrix filled with pseudorandom values uniformly distributed in [min, max).

Parameters:

size - Number of rows and columns in the resulting matrix (the result will be a square matrix).

min - Minimum value in uniform distribution.

max - Maximum value in uniform distribution.

sparsity - Desired sparsity of the resulting matrix. i.e. the percent of values which are zero. Must be a value in [0.0, 1.0]. The true sparsity may slightly differ to ensure the matrix is symmetric.

Returns:

A symmetric matrix filled with pseudorandom values uniformly distributed in [min, max).

Throws:

IllegalArgumentException - If sparsity is not in the range [0.0, 1.0].

randomOrthogonalMatrix

public Matrix randomOrthogonalMatrix(int size)

Gets a pseudorandom orthogonal matrix. From an implementation point of view, a pseudorandom matrix is generated as if by randomMatrix(size, size). Then, a QR decomposition is computed on this pseudorandom matrix and the Q matrix from this decomposition is returned.

Parameters:

size - Size of the orthogonal matrix (i.e. the number rows and columns for the square matrix).

Returns:

A pseudorandom orthogonal matrix.

randomCMatrix

public CMatrix randomCMatrix(int rows,
 int cols)

Generates a matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).

Parameters:

rows - Number of rows in the resulting matrix.

cols - Number of columns in the resulting matrix.

Returns:

A matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).

randomCMatrix

public CMatrix randomCMatrix(Shape shape)

Generates a matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).

Parameters:

shape - Shape of the resulting matrix. Must be of rank 2.

Returns:

A matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [0, 1).

Throws:

IllegalArgumentException - If the shape is not of rank 2.

randomCMatrix

public CMatrix randomCMatrix(int rows,
 int cols,
 double min,
 double max)

Generates a matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [min, max).

Parameters:

rows - Number of rows in the resulting matrix.

cols - Number of columns in the resulting matrix.

min - Minimum value of uniform distribution to sample from (inclusive).

max - Maximum value of uniform distribution to sample from (exclusive).

Returns:

A matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [min, max).

Throws:

IllegalArgumentException - If max is less than min.

randomCMatrix

public CMatrix randomCMatrix(Shape shape,
 double min,
 double max)

Generates a matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [min, max).

Parameters:

shape - Shape of the resulting matrix. Must be of rank 2.

min - Minimum value of uniform distribution to sample from (inclusive).

max - Maximum value of uniform distribution to sample from (exclusive).

Returns:

A matrix filled with pseudorandom complex values with magnitudes uniformly distributed in [min, max).

Throws:

IllegalArgumentException - If max is less than min.

IllegalArgumentException - If shape is not of rank 2.

randnCMatrix

public CMatrix randnCMatrix(int rows,
 int cols)

Generates a matrix filled with pseudorandom complex values with magnitudes sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

Parameters:

rows - The number of rows in the resulting matrix.

cols - The number of columns in the resulting matrix.

Returns:

A matrix filled with pseudorandom complex values with magnitudes sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

randnCMatrix

public CMatrix randnCMatrix(Shape shape)

Generates a matrix filled with pseudorandom complex values with magnitudes sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

Parameters:

shape - Shape of the resulting matrix.

Returns:

A matrix filled with pseudorandom complex values with magnitudes sampled from a normal distribution with a mean of 0.0 and a standard deviation of 1.0.

randnCMatrix

public CMatrix randnCMatrix(int rows,
 int cols,
 double mean,
 double std)

Generates a matrix filled with pseudorandom complex values with magnitudes sampled from a normal distribution with a specified mean and standard deviation.

Parameters:

rows - The number of rows in the resulting matrix.

cols - The number of columns in the resulting matrix.

mean - Mean of the normal distribution from which values are sampled.

std - Standard deviation of the normal distribution from which values are sampled.

Returns:

A matrix filled with pseudorandom complex values with magnitudes sampled from a normal distribution with a specified mean and standard deviation.

Throws:

IllegalArgumentException - If the standard deviation is negative.

randnCMatrix

public CMatrix randnCMatrix(Shape shape,
 double mean,
 double std)

Generates a matrix filled with pseudorandom values sampled from a normal distribution with a specified mean and standard deviation.

Parameters:

shape - Shape of the resulting matrix.

mean - Mean of the normal distribution from which values are sampled.

std - Standard deviation of the normal distribution from which values are sampled.

Returns:

A matrix filled with pseudorandom values sampled from a normal distribution with a specified mean and standard deviation.

Throws:

IllegalArgumentException - If the standard deviation is negative.

randomSparseCMatrix

public CooCMatrix randomSparseCMatrix(int rows,
 int cols,
 double min,
 double max,
 double sparsity)

Generates a random sparse matrix with the specified sparsity. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

rows - Number of rows in the sparse matrix.

cols - Number of columns in the sparse matrix.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

sparsity - Desired sparsity of the resulting matrix. i.e. the percent of values which are zero. Must be a value in [0.0, 1.0].

Returns:

A sparse matrix with sparsity approximately equal to sparsity filled with random values uniformly distributed in [min, max).

randomSparseCMatrix

public CooCMatrix randomSparseCMatrix(Shape shape,
 double min,
 double max,
 double sparsity)

Generates a random sparse matrix with the specified sparsity. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

shape - Shape of the sparse matrix to generate.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

sparsity - Desired sparsity of the resulting matrix. i.e. the percent of values which are zero. Must be a value in [0.0, 1.0].

Returns:

A sparse matrix with sparsity approximately equal to sparsity filled with random values uniformly distributed in [min, max).

randomSparseCMatrix

public CooCMatrix randomSparseCMatrix(int rows,
 int cols,
 double min,
 double max,
 int numNonZeroEntries)

Generates a random sparse matrix with the specified number of non-zero entries. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

rows - Number of rows in the random sparse matrix.

cols - Number of columns in the random sparse matrix.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

numNonZeroEntries - Desired number of non-zero entries int the random sparse matrix.

Returns:

A sparse matrix filled with the specified number of non-zero entries uniformly distributed in [min, max).

randomSparseCMatrix

public CooCMatrix randomSparseCMatrix(Shape shape,
 double min,
 double max,
 int numNonZeroEntries)

Generates a random sparse matrix with the specified number of non-zero entries. The non-zero values will have a uniform distribution in [min, max). Values will be uniformly distributed throughout the matrix.

Parameters:

shape - Shape of the sparse matrix to generate.

min - Minimum value for random non-zero values in the sparse matrix.

max - Maximum value for random non-zero values

numNonZeroEntries - Desired number of non-zero entries int the random sparse matrix.

Returns:

A sparse matrix filled with the specified number of non-zero entries uniformly distributed in [min, max).

randomUnitaryMatrix

public CMatrix randomUnitaryMatrix(int size)

Gets a pseudorandom unitary matrix. From an implementation point of view, a pseudorandom complex matrix is generated as if by randomCMatrix(size, size). Then, a QR decomposition is computed on this pseudorandom matrix and the Q matrix from this decomposition is returned.

Parameters:

size - Size of the unitary matrix (i.e. the number rows and columns for the square matrix).

Returns:

A pseudorandom unitary matrix.

randomTriuMatrix

public Matrix randomTriuMatrix(int size,
 int min,
 int max)

Gets a pseudorandom upper triangular matrix of the specified size. The entries will be distributed according to a standard normal distribution with a mean of 0 and standard deviation of 1.

Parameters:

size - Size if the upper triangular matrix.

Returns:

A pseudorandom upper triangular matrix of the specified size.

geRandomTrilMatrix

public Matrix geRandomTrilMatrix(int size,
 int min,
 int max)

Gets a pseudorandom lower triangular matrix of the specified size. The entries will be distributed according to a standard normal distribution with a mean of 0 and standard deviation of 1.

Parameters:

size - Size if the lower triangular matrix.

Returns:

A pseudorandom lower triangular matrix of the specified size.