All Classes and Interfaces
Class
Description
Computes a matrix decomposition such that:
A = U*B*VT
where A is m by n, U is orthogonal and m by m, B is an m by n bidiagonal matrix, V is orthogonal and n by n.
A = U*B*VT
where A is m by n, U is orthogonal and m by m, B is an m by n bidiagonal matrix, V is orthogonal and n by n.
Implementation of
BidiagonalDecomposition for 32-bit floatsImplementation of
BidiagonalDecomposition for 64-bit floatsDense matrix composed of boolean values
Cholesky decomposition.
Implementation of
CholeskyDecomposition for 32-bit floats.
Implementation of
CholeskyDecomposition for 64-bit floats.
Cholesky LDLT decomposition.
Implementation of
CholeskyDecomposition for 32-bit floats.
Implementation of
CholeskyDecomposition for 64-bit floats.
Implementation of
CholeskySparseDecomposition for 32-bit floats.
Implementation of
CholeskySparseDecomposition for 64-bit floats.Interface for all complex 64 bit floating point rectangular matrices.
A generic abstract class for matrices whose data is stored in a single 1D array of floats.
Dense matrix for complex numbers.
Represents a complex number using 32-bit floating point numbers.
Represents a complex number using 64-bit floating point numbers.
Basic math operations on complex numbers.
Basic math operations on complex numbers.
Complex_F32 number in polar notation.z = r*(cos(θ) + i*sin(θ))
where r and θ are polar coordinate parameters
Complex_F64 number in polar notation.z = r*(cos(θ) + i*sin(θ))
where r and θ are polar coordinate parameters
Location of controls for turning on and off concurrent (i.e.
Convert between matrices with the same structure but different element data types
Contains a function to convert from one matrix type into another
Converts 1D and 2D arrays to and from EJML data types
Functions for converting between matrix types.
An interface for performing matrix decompositions.
Decomposition for sparse matrices.
An eigenpair is a set composed of an eigenvalue and an eigenvector.
Computes a boolean result when given a row, col, and element value
A double array which can have its size changed
Utility class to get the corresponding mask builder based on a matrix or primitive array
Mask implementation backed by a primitive array
Utility class to build
DMaskPrimitiveMask implementation backed by a matrix in CSC format
Utility class to build
DMaskSparseMask implementation which checks if the entry is assigned in the sparse matrix.
Utility class to build
DMaskSparseStructuralInterface for all 64F real matrices.
Interface for a row-major matrix that uses a single array internally.
Fixed sized vector with 2 elements.
Fixed sized 2 by DMatrix2x2 matrix.
Fixed sized vector with 3 elements.
Fixed sized 3 by DMatrix3x3 matrix.
Fixed sized vector with 4 elements.
Fixed sized 4 by DMatrix4x4 matrix.
Fixed sized vector with 5 elements.
Fixed sized 5 by DMatrix5x5 matrix.
Fixed sized vector with 6 elements.
Fixed sized 6 by DMatrix6x6 matrix.
A generic abstract class for matrices whose data is stored in a single 1D array of doubles.
Interface which all fixed sized matrices must implement
This is a matrix iterator for traversing through a submatrix.
A row-major block matrix declared on to one continuous array.
DMatrixRMaj is a row matrix with real elements that are 64-bit floats.
High level interface for sparse matrices double types.
Value of an element in a sparse matrix
Compressed Column (CC) sparse matrix format.
A sparse matrix format that is designed to act as an intermediate step for other matrix types.
An algebraic structure with a single associative binary operation and an identity element
as defined in the graphblas c-api (https://people.eecs.berkeley.edu/~aydin/GraphBLAS_API_C_v13.pdf)
p.
Functional Interface used in reduce methods to specify arbitrary binary functions accepting doubles
Functional Interface used in applyRow/Col-Wise method to specify arbitrary binary functions accepting a row index and a double value
Functional Interface used in apply method to specify arbitrary unary functions accepting a double
Scalar value.
An algebraic structure, defined over the `doubles` by two monoids + and *, called addition and multiplication.
as defined in the graphblas c-api (https://people.eecs.berkeley.edu/~aydin/GraphBLAS_API_C_v13.pdf)
p.
Describes a rectangular submatrix inside of a
DMatrixD1.
This is a generic interface for computing the eigenvalues and eigenvectors of a matrix.
Implementation of
EigenDecomposition for 32-bit floats
Implementation of
EigenDecomposition for 64-bit floatsCentral class for controlling concurrency in EJML.
This is a list of parameters that are used across the code.
Contains various functions related to unit testing matrix operations.
Automatically generated file containing build version information.
The row and column of an element in a Matrix
Convenience class for fancy print designed to make it less verbose
Converts 1D and 2D arrays to and from EJML data types
Functions for converting between matrix types.
An eigenpair is a set composed of an eigenvalue and an eigenvector.
A float array which can have its size changed
Different types of fill in reducing techniques that can be selected
Utility class to get the corresponding mask builder based on a matrix or primitive array
Mask implementation backed by a primitive array
Utility class to build
FMaskPrimitiveMask implementation backed by a matrix in CSC format
Utility class to build
FMaskSparseMask implementation which checks if the entry is assigned in the sparse matrix.
Utility class to build
FMaskSparseStructuralInterface for all 64F real matrices.
Interface for a row-major matrix that uses a single array internally.
Fixed sized vector with 2 elements.
Fixed sized 2 by FMatrix2x2 matrix.
Fixed sized vector with 3 elements.
Fixed sized 3 by FMatrix3x3 matrix.
Fixed sized vector with 4 elements.
Fixed sized 4 by FMatrix4x4 matrix.
Fixed sized vector with 5 elements.
Fixed sized 5 by FMatrix5x5 matrix.
Fixed sized vector with 6 elements.
Fixed sized 6 by FMatrix6x6 matrix.
A generic abstract class for matrices whose data is stored in a single 1D array of floats.
Interface which all fixed sized matrices must implement
This is a matrix iterator for traversing through a submatrix.
A row-major block matrix declared on to one continuous array.
FMatrixRMaj is a row matrix with real elements that are 32-bit floats.
High level interface for sparse matrices float types.
Value of an element in a sparse matrix
Compressed Column (CC) sparse matrix format.
A sparse matrix format that is designed to act as an intermediate step for other matrix types.
An algebraic structure with a single associative binary operation and an identity element
as defined in the graphblas c-api (https://people.eecs.berkeley.edu/~aydin/GraphBLAS_API_C_v13.pdf)
p.
Functional Interface used in reduce methods to specify arbitrary binary functions accepting floats
Functional Interface used in applyRow/Col-Wise method to specify arbitrary binary functions accepting a row index and a float value
Functional Interface used in apply method to specify arbitrary unary functions accepting a float
Scalar value.
An algebraic structure, defined over the `floats` by two monoids + and *, called addition and multiplication.
as defined in the graphblas c-api (https://people.eecs.berkeley.edu/~aydin/GraphBLAS_API_C_v13.pdf)
p.
Describes a rectangular submatrix inside of a
FMatrixD1.An array of objects which grows and recycles its elements automatically.
An integer array which can have its size changed
Processes a value and is provided workspace
Performs a parallel for loop with the specified step increment and a workspace for each thread.
Processes an integer and returns a number
Processes a range of integer numbers
Processes a range of integer numbers
Functional Interface used in matrix select methods to specify arbitrary binary predicates accepting element coordinates
Inspired by the predefined SelectOps in GraphBLAS (spec extension)
Scalar value.
Base class for Linear Solvers.
An implementation of LinearSolverDense solves a linear system or inverts a matrix.
Ensures that any linear solver it is wrapped around will never modify
the input matrices.
Ensures that any linear solver it is wrapped around will never modify
the input matrices.
Wrapper which allows a regular linear solver to act like a sparse solver
LU Decomposition refactors the original matrix such that:
PT*L*U = A where P is a pivot matrix, L is a lower triangular matrix, U is an upper triangular matrix and A is the original matrix.
PT*L*U = A where P is a pivot matrix, L is a lower triangular matrix, U is an upper triangular matrix and A is the original matrix.
Implementation of
LUDecomposition for 32-bit numbersImplementation of
LUDecomposition for 64-bit numbersImplementation of
LUSparseDecomposition for 32-bit numbersImplementation of
LUSparseDecomposition for 64-bit numbersMask used for specifying which matrix entries should be computed
Helper class to build
Mask and specify specific parameterBase interface for all rectangular matrices
If two matrices did not have compatible dimensions for the operation this exception
is thrown.
Determines which features a matrix has that do not rely on inner data type
Generic (slow) matrix features for real matrices
Generic (slow) matrix features for real matrices
Provides simple to use routines for reading and writing matrices to and from files.
High level interface for all sparse matrices
Specifies that type of data structure a matrix is encoded with.
QR decompositions decompose a rectangular matrix 'A' such that 'A=QR'.
Similar to
QRDecomposition but it can handle the rank deficient case by
performing column pivots during the decomposition.
Implementation of
QRPDecomposition for 32-bit floats
Implementation of
QRPDecomposition for 64-bit floatsSparse
QRDecompositionAn implementation of the quick sort algorithm from Numerical Recipes Third Edition
that is specified for arrays of doubles.
Base class for reading CSV formatted files.
Reads in a matrix that is in a column-space-value (CSV) format.
An augmented system matrix is said to be in reduced row echelon form (RREF) if the following are true:
Implementation of
ReducedRowEchelonForm for 32-bit floatsImplementation of
ReducedRowEchelonForm for 64-bit floatsMatrix which can be reshaped
This exception is thrown if an operation can not be finished because the matrix is singular.
This is an abstract class for computing the singular value decomposition (SVD) of a matrix, which is defined
as:
A = U * W * V T where A is m by n, and U and V are orthogonal matrices, and W is a diagonal matrix.
A = U * W * V T where A is m by n, and U and V are orthogonal matrices, and W is a diagonal matrix.
Implementation of
SingularValueDecomposition for 32-bit floats.Implementation of
SingularValueDecomposition for 64-bit floats.Finds the nullspace for a matrix given the number of singular values
Describes a rectangular submatrix.
Finds the decomposition of a matrix in the form of:
A = O*T*OT
where A is a symmetric m by m matrix, O is an orthogonal matrix, and T is a tridiagonal matrix.
A = O*T*OT
where A is a symmetric m by m matrix, O is an orthogonal matrix, and T is a tridiagonal matrix.
Implementation of
TridiagonalSimilarDecomposition for 32-bit floatsImplementation of
TridiagonalSimilarDecomposition for 64-bit floatsVarious functions that are useful but don't have a clear location that they belong in.
Interface for all complex 64 bit floating point rectangular matrices.
A generic abstract class for matrices whose data is stored in a single 1D array of doubles.
Dense matrix for complex numbers.