All Classes and Interfaces

Class
Description
A sparse matrix stored in coordinate list (COO) format.
Base class for all sparse Field tensors stored in coordinate list (COO) format.
A sparse vector stored in coordinate list (COO) format.
A sparse matrix stored in coordinate list (COO) format.
Base class for all sparse Ring tensors stored in coordinate list (COO) format.
A sparse vector stored in coordinate list (COO) format.
A sparse matrix stored in coordinate list (COO) format.
Base class for all sparse tensors stored in coordinate list (COO) format.
A sparse vector stored in coordinate list (COO) format.
 
A sparse matrix stored in compressed sparse row (CSR) format.
A sparse matrix stored in compressed sparse row (CSR) format.
This is the base class of all real primitive double tensors.
 
The base class for all dense Field tensors.
The base class for all dense vectors whose data are Field elements.
The base class for all dense matrices whose elements are members of a Ring.
The base class for all dense Ring tensors.
The base class for all dense vectors whose data are Ring elements.
The base class for all dense matrices whose elements are members of a Semiring.
The base class for all dense Semiring tensors.
The base class for all dense vectors whose data are Semiring elements.
This is the base class of all real primitive double tensors, matrices, or vectors.
The base abstract class for all tensors, including matrices and vectors.
 
This class contains several low-level methods useful for computing aggregation ops on dense tensors.
This utility class contains several low-level methods useful for computing aggregation ops on dense/sparse tensors.
This utility class contains methods useful for aggregating arrays of Semiring's.
The ArrayBuilder class provides a collection of static utility methods to construct, initialize, and manipulate arrays in various ways.
The ArrayConversions class provides utility methods for converting between various array types and formats.
The ArrayJoiner class provides utility methods for combining and repeating arrays.
The ArrayUtils class provides a set of utility methods for performing operations on arrays.
Base class for solvers which solve a linear system of equations U*x=b or U*X=B where U is an upper triangular matrix.
Base class for all decompositions which implement matrix balancing.
Represents an immutable boolean value within a semiring structure.
This abstract class specifies methods for computing the Cholesky decomposition of a positive-definite matrix.
Instances of this class represents a complex dense matrix backed by a Complex128 array.
This utility class provides methods useful for comparing elements of a Ring.
This utility class provides methods useful for comparing elements of a Semiring.
Represents an immutable complex number with double-precision floating point components.
A 2D bivariateGaussian distribution on the complex plane.
This class provides low level methods for computing operations on complex tensors.
A uniform distribution on an annulus (e.g. washer) in the complex plane.
A rectangular uniform distribution on the complex plane.
Represents an immutable complex number with single-precision floating point components.
This class provides low level methods for computing ops on complex tensors.
This solver solves linear systems of equations where the coefficient matrix in an upper triangular complex dense matrix and the constant vector is a complex dense vector.
Instances of this class may be used to balance complex dense matrices.
An instance of this class allows for the computation of a Cholesky decomposition of a complex Hermitian positive-definite matrix.
This class contains methods for computing the determinant of a complex dense matrix.
Solver for solving a well determined system of linear equations in an exact sense using the LU decomposition.
Solver for solving a complex well determined linear tensor equation A*X=B in an exact sense.
This solver solves linear systems of equations where the coefficient matrix in a lower triangular complex dense matrix and the constant vector/matrix is complex and dense.
Computes the Hessenburg decomposition of a complex dense square matrix.
This class solves a linear system of equations Ax=b in a least-squares sense.
Complex128his class provides methods for computing the LU decomposition of a complex dense matrix.
A parser for parsing complex numbers represented as a string.
Instances of this class compute the QR decomposition of a complex dense matrix.
This class computes the Schur decomposition of a complex dense square matrix.
Instances of this class can be used to compute the singular value decomposition (SVD) of a complex dense matrix.
This class is the base class for complex matrix decompositions which proceed by using unitary transformations (specifically Householder reflectors) to bring a matrix into an upper triangular/Hessenburg matrix.
Utility class for computing the condition number of a matrix.
Configurations for standard and concurrent ops.
A complex sparse matrix stored in coordinate list (COO) format.
This utility class contains methods for combining or joining sparse COO tensors, matrices, and vectors.
Utility class for converting COO tensor to another type of tensor.
Sparse complex tensor stored in coordinate list (COO) format.
A complex sparse vector stored in coordinate list (COO) format.
A class which can be used to sort the indices, along with data values, in lexicographical order.
Instances of this class represent a sparse matrix whose non-zero elements are stored in Coordinate List (COO) format, with all data elements belonging to a specified Field type.
Represents a sparse tensor whose non-zero elements are stored in Coordinate List (COO) format, with all data elements belonging to a specified Field type.
Represents a sparse vector whose non-zero elements are stored in Coordinate List (COO) format, with all data elements belonging to a specified Field type.
A utility class that aids in getting or setting specified elements of a sparse COO tensor, matrix, or vector.
Utility class containing methods for manipulating a sparse COO tensor, matrix, or vector.
A real sparse matrix stored in coordinate list (COO) format.
Utility class for computing certain properties of COO matrices.
Utility class for computing the Hermitian transpose of a COO ring matrix or tensor.
Represents a sparse matrix whose non-zero elements are stored in Coordinate List (COO) format, with all data elements belonging to a specified Ring type.
Utility class for computing ops on sparse COO Ring matrices.
This utility class contains low level implementations of norms for sparse COO ring tensors, matrices and vectors.
Represents a sparse tensor whose non-zero elements are stored in Coordinate List (COO) format, with all data elements belonging to a specified Ring type.
Utility class for computing ops on sparse COO Ring tensors.
Represents a sparse vector whose non-zero elements are stored in Coordinate List (COO) format, with all data elements belonging to a specified Ring type.
Utility class for computing ops on sparse COO Ring vectors.
A utility class for checking equality between COO Semiring tensors.
This utility class contains methods useful for computing the matrix multiplication between two sparse COO Semiring tensors.
Represents a sparse matrix whose non-zero elements are stored in Coordinate List (COO) format, with all data elements belonging to a specified Semiring type.
Utility class for computing various ops on and between sparse COO Semiring matrices.
This class contains low level implementations for methods to evaluate certain properties of a sparse COO Semiring matrix.
Represents a sparse tensor whose non-zero elements are stored in Coordinate List (COO) format, with all data elements belonging to a specified Semiring type.
This utility class contains methods for computing ops on two Semiring tensors.
Represents a sparse vector whose non-zero elements are stored in Coordinate List (COO) format, with all data elements belonging to a specified Semiring type.
Utility class for computing ops between sparse COO Semiring vectors.
A real sparse tensor stored in coordinate list (COO) format.
Instances of this class can be used to compute the tensor dot product between two sparse COO tensors.
Utility class for computing the transpose of a sparse COO tensor or matrix.
A real sparse vector stored in coordinate list (COO) format.
A complex sparse matrix stored in compressed sparse row (CSR) format.
Utility class for converting CSR matrices to flat matrices, dense matrices, etc.
Instances of this class represent a sparse matrix using the compressed sparse row (CSR) format where all data elements belonging to a specified Field type.
Instances of this class represent a real sparse matrix using the compressed sparse row (CSR) format.
Utility class for computing ops on sparse CSR matrices.
Utility class containing methods useful for determining certain properties of general CSR matrices.
 
This class contains methods to check properties of sparse CSR Ring matrices.
Instances of this class represent a sparse matrix using the compressed sparse row (CSR) format where all data elements belonging to a specified Semiring type.
A dense complex tensor backed by an array of Complex128's.
 
This interface specifies methods which should be implemented in all decompositions.
This utility class provides implementations for the concatenation of dense tensors.
This class provides methods for checking the equality of a dense field tensor with a sparse field tensor.
This utility class provides low level methods for computing the matrix multiplication between a sparse/dense matrix and dense/sparse matrix/vector.
This class contains low level implementations for ops between a dense and a sparse field matrix.
This class contains methods to apply common ops to a dense/sparse field matrix and to a sparse/dense field matrix.
This class provides low level methods for computing ops between dense/sparse and sparse/dense field vectors.
This class contains low-level ops which act on a dense and a sparse CSR field matrix.
This class contains low-level implementations of semiring sparse-dense matrix multiplication where the sparse matrices are in CSR format.
This class provides methods for checking the equality of dense tensors.
This utility class contains methods for computing the determinant of a dense matrix whose data are elements of a Field.
This class contains low-level implementations of element-wise tensor division between two Field tensors.
This class provides low level methods for computing ops on dense field tensors.
This class provides low level implementations for vector ops with two dense Field vectors.
 
Utility class for computing the Hermitian transpose of a dense Ring tensor or matrix.
Utility class for computing ops between two dense Ring tensors.
This utility class contains methods for computing norms of dense Ring Vectors.
This utility class contains methods for computing ops on dense Ring Vectors.
Utility class for converting dense Semiring tensors to another type of tensor.
Utility class useful for computing element-wise products between two Semiring tensors.
This utility class provides methods for computing dense matrix multiplication between matrices whose data are members of a Semiring.
Singleton class which stores a map of all viable dense Semiring matrix multiply algorithms and uses that map to dispatch a dense Semiring matrix multiply problem to the appropriate algorithm.
Simple enum class containing all possible choices of real dense matrix multiply algorithms.
This utility class contains methods for computing the dense matrix multiplication between a matrix and the transpose of a matrix.
This class provides low level methods for computing ops on dense semiring tensors.
This interface specifies a binary operation on two dense Semiring tensors.
Instances of this class can be used to compute the tensor dot product between two dense tensors.
This utility class contains methods for computing ops on dense Semiring Vectors.
This utility class provides methods for computing the transpose of a dense tensor.
 
Base class for all statistical distributions.
 
This class provides several methods useful for computing eigenvalues and eigenvectors.
 
Contains error messages for common errors which may occur.
Solves a well determined system of equations Ax=b in an exact sense by using a LU decomposition.
Solves a well determined system of equations AX=B in an exact sense where A, X, and B are tensors.
Defines a mathematical field structure and specifies the operations that field elements must support.
This class provides methods for computing the LU decomposition of a dense matrix whose elements are members of a Field.
Instances of this class represents a dense matrix backed by a Field array.
This utility class contains ops for tensors whose elements are members of a Field.
Instances of this class represent a dense tensor backed by a Field array.
This interface provides default functionality for all tensors whose data are elements of a Field.
Instances of this class represents a dense vector backed by a Field array.
A simple utility class containing useful constants.
An exception which is thrown when an unexpected error occurs while trying to parse a string representing some algebraic structure (e.g. matrix, complex number, etc.).
This solver solves linear systems of equations where the coefficient matrix in a lower triangular real dense matrix and the constant vector is a real dense vector.
This class contains methods for computing real or complex Givens' rotation matrices.
Computes the Hessenburg decomposition of a complex dense Hermitian matrix.
This class contains methods for computing real or complex Householder reflectors (also known as elementary reflectors).
Data record to store an ordered list of integers (i.e., an n-tuple).
This class provides methods for computing the inverse of a matrix.
 
An exception which is thrown when a linear algebra related error occurs at runtime.
Interface representing a solver for linear systems involving matrices and vectors.
Interface representing a linear system solver for tensor equations.
This class solves a linear system of equations Ax=b in a least-squares sense.
This abstract class specifies methods for computing the LU decomposition of a matrix.
Simple enum containing pivoting options for pivoting in LU decomposition.
 
Instances of this class represents a complex dense matrix backed by a double[] array.
A data record for storing the tokens of a Matrix Market Exchange Format file header.
Enum containing valid field types in a Matrix Market file.
Enum containing valid formats in a Matrix Market file.
Enum containing valid object types in a Matrix Market file.
Enum containing valid symmetry in a Matrix Market file.
Instances of this class may be used to parse a file containing matrix or vector data in Matrix Market Exchange Format.
The MatrixMixin interface defines methods that any matrix implementation must support.
Dispatches matrix multiplication to the appropriate algorithm based on the size of the matrices to be multiplied.
A utility class providing a range of matrix norm computations for both real and complex matrices.
 
Data record to store a pair of values (i.e., a 2-tuple).
Represents a square permutation matrix with rows and columns equal to PermutationMatrix.size, where each row and column contains exactly one entry of 1, and all other entries are 0.
This class contains several methods for determining the positive definiteness of a matrix.
Utility class for formatting arrays as ★★pretty★★ human-readable strings.
Printing and formating options for tensors, matrices, and vectors.
A utility class for generating projection matrices used in 3D graphics transformations.
 
The RandomComplex class provides methods to generate pseudorandom complex numbers under a variety of distributions and constraints.
A utility class for generating random dense tensors, matrices, and vectors with customizable distributions.
A utility class for generating random sparse tensors and matrices with customizable sparsity and distributions.
This solver solves linear systems of equations where the coefficient matrix in an upper triangular real dense matrix and the constant vector is a real dense vector or matrix.
Instances of this class may be used to balance real dense matrices.
An instance of this class allows for the computation of a Cholesky decomposition for a real dense matrix.
This utility class contains implementations for ops which concatenate sparse COO matrices and vectors.
Utility class for computing ops between a complex sparse COO tensor and a real coo tensor.
This class contains low-level ops which act on a real/complex dense and a complex/real sparse CSR matrix.
This class provides low-level implementation of matrix multiplication between a real CSR matrix and a complex CSR matrix.
This class contains low-level implementations for element-wise ops on real/complex CSR matrices.
This class contains low level implementations of ops between real/complex and dense/sparse matrices.
This class contains methods to apply common binary ops to a real/complex dense matrix and to a complex/real sparse matrix.
This class contains methods for checking the equality of real dense/sparse and complex dense/sparse tensors.
This class provides low level methods for computing ops between a real/complex dense/sparse vector and a complex/real sparse/dense vector.
This class contains methods for checking the equality of real/complex sparse tensors.
This class has low level implementations for ops between a real sparse matrix and a complex sparse matrix.
This class contains low level methods for computing the multiplication between a real/complex matrix and a complex/real matrix/vector.
This class contains low level implementations of ops on a real sparse tensor and a complex sparse tensor.
This class provides methods for getting and setting elements and slices from/to a real sparse matrix.
Utility class for computing tensor dot products between two real sparse COO tensors.
Utility class for computing ops between two real sparse COO tensors backed by a primitive double array.
This class contains low level implementations for ops on a real sparse COO vector.
This class contains low-level implementations of real sparse-dense matrix multiplication where the sparse matrix is in CSR format.
This class contains low-level ops which act on a real dense and a real sparse CSR matrix.
This class contains methods to check equality or approximate equality between two sparse CSR matrices.
Utility class for manipulating real sparse CSR matrices (e.g. row swaps, column swaps, etc.).
This class provides low-level implementation of matrix multiplication between two real CSR matrices.
This utility class provides implementations for tensor dot products on two real sparse CSR matrices.
This utility class contains low-level implementations for operations on real CSR matrices.
This class contains low-level implementations for evaluating properties of real sparse CSR matrices.
This class contains methods to apply common binary ops to a real dense matrix and to a real sparse matrix.
This class contains methods for computing the determinant of a real dense matrix.
This class contains low level implementations of element-wise division algorithms for real dense tensors.
This class contains low level implementations of element-wise multiplications algorithms for real dense tensors.
This class provides methods for checking the equality of real dense tensors.
This class contains several low level methods for computing matrix-matrix multiplications.
This class contains several low level methods for computing matrix-matrix multiplications with a transpose for two real dense matrices.
Singleton class which stores a map of all viable real dense matrix multiply algorithms and uses that map to dispatch a real dense matrix multiply problem to the appropriate algorithm.
Simple enum class containing all possible choices of real dense matrix multiply algorithms.
This class provides low level methods for computing ops on real dense tensors.
This class contains low-level implementations for ops which check if a tensor satisfies some property.
This class contains low-level implementations of setting ops for real dense tensors.
This class contains methods for checking the equality of a real dense and real sparse tensors.
This class contains low level methods for computing the matrix multiplication (and matrix vector multiplication) between a real dense/sparse matrix and a real sparse/dense matrix or vector.
This class contains several low level methods for computing matrix-matrix multiplications with a transpose for a real dense matrix and a real sparse matrix.
This class contains low-level ops between a real dense and real sparse matrix.
This class provides low level methods for computing ops between a real dense/sparse vector and a real sparse/dense vector.
Functional interface for creating a lambda which implements an operation acting on two real dense tensors.
Instances of this class can be used to compute the tensor dot product between two real dense primitive double tensors.
This class contains several low-level algorithms for computing the transpose of real dense tensors.
This class provides low level implementations for several vector operation.
Solver for solving a well determined system of linear equations in an exact sense using the LU decomposition.
Solver for solving a real well determined linear tensor equation A*X=B in an exact sense.
This class contains low level methods for computing the matrix multiplication (and matrix vector multiplication) between a real dense/sparse matrix and a sparse/dense field matrix/vector.
This class contains several low level methods for computing matrix-matrix multiplications with a transpose for a real/field and sparse/dense matrix.
This class contains low level implementations of ops between real/field and dense/sparse matrices.
This class contains methods to apply common binary ops to a real/field dense matrix and to a field/real sparse matrix.
This class provides low level methods for computing ops between a real/field dense/sparse vector and a field/real sparse/dense vector.
This class contains low-level implementations of real-complex sparse-dense matrix multiplication where the sparse matrix is in CSR format.
This class contains low-level ops which act on a real/complex dense and a complex/real sparse CSR matrix.
This class contains low-level implementations of element-wise tensor division for a dense real and dense field tensor.
This class contains low-level implementations of element-wise tensor multiplication for a dense real and dense field tensor.
This class provides methods for checking the equality of one dense real and one dense field tensors.
This class contains several low level methods for computing dense matrix-matrix multiplications between one field matrix and one real matrix.
This class contains several low level methods for computing matrix-matrix multiplications with a transpose for a real dense matrix and a dense field matrix.
This class provides low level methods for computing ops with at least one real tensor and at least one field tensor.
This class provides low level implementations for vector ops with one dense real vector and one dense field vector.
Represents an immutable real number backed by a 32-bit floating-point value.
Represents an immutable real number backed by a 64-bit floating-point value.
This solver solves linear systems of equations where the coefficient matrix in a lower triangular real dense matrix and the constant vector is a real dense vector.
A real Gaussian (e.g. normal) distribution.
Computes the Hessenburg decomposition of a real dense square matrix.
A real number backed by a 16-bit integer number.
A real number backed by a 32-bit integer number.
This class solves a linear system of equations Ax=b in a least-squares sense.
This class provides methods for computing the LU decomposition of a real dense matrix.
This class provides low level methods for computing ops on real tensors.
This class provides low level methods for checking tensor properties.
Instances of this class compute the QR decomposition of a real dense matrix.
This class computes the Schur decomposition of a real dense square matrix.
This class contains methods for checking the equality of real sparse tensors.
This utility class provides methods for inserting/removing values in a real sparse vector.
This class contains low level implementations of matrix multiplication for real sparse matrices.
This utility class contains implementations for real sparse COO matrix manipulations.
This class has low level implementations for ops between two real sparse matrices.
This class contains low level implementations for methods to evaluate certain properties of a real sparse matrix.
This class contains low level implementations of norms for tensors, matrices and vector.
Instances of this class can be used to compute the singular value decomposition (SVD) of a real dense matrix.
A uniform real distribution.
This class is the base class for real matrix decompositions which proceed by using unitary/orthogonal transformations (specifically HouseholderOld reflectors) to bring a matrix into an upper triangular/Hessenburg matrix.
Defines a mathematical ring structure and specifies the operations that ring elements must support.
Instances of this class represents a dense matrix backed by a Ring array.
Utility class useful for computing ops on Ring tensors.
Utility class for checking properties of Ring's
Instances of this class represent a dense tensor backed by a Ring array.
This interface provides default functionality for all tensors whose data are elements of a Ring.
Instances of this class represents a dense vector backed by a Ring array.
The Rotation class provides utility methods to compute rotation matrices for 2D and 3D rotations.
This class contains static methods for computing row echelon, reduced row echelon, and extended reduced row echelon forms of a matrix.
The base class for Schur decompositions.
Defines a mathematical semiring structure and specifies the operations that semiring elements must support.
Utility class for computing matrix multiplication of a sparse CSR Semiring matrix.
Utility class for computing ops on sparse CSR Semiring tensors.
Utility class containing methods useful for determining certain properties of a sparse CSR Semiring matrix.
Instances of this class represents a dense matrix backed by a Semiring array.
This utility class contains ops for tensors whose elements are members of a Field.
This utility class provides methods useful for determining properties of semiring tensors.
Instances of this class represent a dense tensor backed by a Semiring array.
This interface provides default functionality for all tensors whose data are elements of a Semiring.
Instances of this class represents a dense vector backed by a Semiring array.
Represents the shape of a multidimensional array (e.g. tensor, matrix, vector, etc.), specifying its dimensions and providing utilities for shape-related ops.
An exception which is thrown when some operation not defined for singular matrices is attempted to be performed on a singular matrix.
The SmartMatrix class provides a unified interface for performing operations on matrices of various types without requiring users to know the specific underlying implementation.
This class provides methods for efficiently finding if a sparse vector, matrix, or tensor contains a non-zero item at a specified index.
Data class for storing information for a sparse (CSR or COO) matrix.
Data class for storing information for a sparse COO tensor.
Contains common utility functions for working with sparse matrices.
Data class for storing information for a sparse COO vector.
A class which provides simple utility methods for strings.
This class contains several methods for computing the subspace of a matrix.
 
This abstract class specifies methods for computing the singular value decomposition (SVD) of a matrix.
Computes the Hessenburg decomposition of a real dense symmetric matrix.
A real symmetric tri-diagonal matrix.
A real dense tensor backed by a primitive double array.
The base class for all classes whose instances may be used to compute a tensor dot product.
This utility class provides static methods for computing the 'inverse' of a tensor with respect to some tensor dot product operation.
Functional interface for general tensor operation.
This interface specifies methods which any tensor whose data are elements of a field should implement.
This interface specifies methods which any tensor whose data are elements of a ring should implement.
This interface specifies methods which any tensor whose data are elements of a semiring should implement.
The TensorReader class provides several static methods for reading serialized tensors, matrices, and vectors from a file.
An exception to be thrown when there is an error related to tensor shapes.
The TensorWriter class provides static methods for serializing and saving tensors, matrices, and vectors to files.
This class contains the base thread pool for all concurrent ops and methods for managing the pool.
A utility class for computing transformations on Semiring arrays.
Provides a dispatch method for dynamically choosing the best matrix transpose algorithm.
Data record to store a triplet of values (i.e., a 3-tuple).
Data record to store an ordered list of values (i.e., an n-tuple).
This class is the base class for all decompositions which proceed by using unitary transformations (specifically HouseholderOld reflectors) to bring a matrix into an upper triangular matrix (QR decomposition) or an upper Hessenburg matrix (Hessenburg decomposition).
This utility class contains several methods for ensuring parameters satisfy some condition.
A dense vector backed by a primitive double array.
This interface specifies methods which all vectors should implement.
A utility class for computing vector norms, including various types of ℓp norms, with support for both dense and sparse vectors.
Utility class containing static for generating view matrices.