Uses of Interface
org.ojalgo.matrix.decomposition.MatrixDecomposition.Solver

Packages that use MatrixDecomposition.Solver

Package	Description
org.ojalgo.matrix.decomposition
org.ojalgo.optimisation.convex
org.ojalgo.random.process

Uses of MatrixDecomposition.Solver in org.ojalgo.matrix.decomposition

Subinterfaces of MatrixDecomposition.Solver in org.ojalgo.matrix.decomposition

Modifier and Type	Interface	Description
interface	Cholesky<N extends Comparable<N>>	Cholesky: [A] = [L][L]H (or [R]H[R])
static interface	Eigenvalue.Spectral<N extends Comparable<N>>	“Spectral decomposition” refers specifically to the orthogonal/unitary eigen-decomposition of a normal matrix (most commonly Hermitian / symmetric).
interface	LDL<N extends Comparable<N>>	LDL: [A] = [L][D][L]H (or [R]H[D][R])
interface	LDU<N extends Comparable<N>>	LDU: [A] = [L][D][U] ( [PL][L][D][U][PU] )
interface	LU<N extends Comparable<N>>	LU: [A] = [L][U]
interface	QR<N extends Comparable<N>>	QR: [A] = [Q][R] Decomposes [this] into [Q] and [R] where: [Q] is an orthogonal matrix (orthonormal columns).
interface	SingularValue<N extends Comparable<N>>	Singular Value: [A] = [U][S][V]T Decomposes [this] into [U], [S] and [V] where: [U] is an orthogonal matrix.

Classes in org.ojalgo.matrix.decomposition that implement MatrixDecomposition.Solver

Modifier and Type	Class	Description
(package private) class	DenseCholesky<N extends Comparable<N>>
(package private) static final class	DenseCholesky.C128
(package private) static final class	DenseCholesky.H256
(package private) static final class	DenseCholesky.Q128
(package private) static final class	DenseCholesky.R064
(package private) static final class	DenseCholesky.R128
(package private) class	DenseLDL<N extends Comparable<N>>
(package private) static final class	DenseLDL.C128
(package private) static final class	DenseLDL.H256
(package private) static final class	DenseLDL.Q128
(package private) static final class	DenseLDL.R064
(package private) static final class	DenseLDL.R128
(package private) class	DenseLU<N extends Comparable<N>>
(package private) static final class	DenseLU.C128
(package private) static final class	DenseLU.H256
(package private) static final class	DenseLU.Q128
(package private) static final class	DenseLU.R064
(package private) static final class	DenseLU.R128
(package private) class	DenseQR<N extends Comparable<N>>
(package private) static final class	DenseQR.C128
(package private) static final class	DenseQR.H256
(package private) static final class	DenseQR.Q128
(package private) static final class	DenseQR.R064
(package private) static final class	DenseQR.R128
(package private) class	DenseSingularValue<N extends Comparable<N>>
(package private) static final class	DenseSingularValue.C128
(package private) static final class	DenseSingularValue.H256
(package private) static final class	DenseSingularValue.Q128
(package private) static final class	DenseSingularValue.R064
(package private) static final class	DenseSingularValue.R128
(package private) class	HermitianEvD<N extends Comparable<N>>	Eigenvalues and eigenvectors of a real matrix.
(package private) static final class	HermitianEvD.C128
(package private) static final class	HermitianEvD.H256
(package private) static final class	HermitianEvD.Q128
(package private) static final class	HermitianEvD.R064
(package private) static final class	HermitianEvD.R128
(package private) final class	RawCholesky
(package private) static final class	RawEigenvalue.Symmetric
(package private) final class	RawLU
(package private) final class	RawQR	For an m-by-n matrix A with m >= n, the QR decomposition is an m-by-n orthogonal matrix Q and an n-by-n upper triangular matrix R so that A = Q*R.
(package private) final class	RawSingularValue	Singular Value Decomposition.
(package private) final class	SparseLU	A sparse, primitive double based, LU decomposition with support for incremental Forrest-Tomlin updates.
final class	SparseQDLDL	Quasi-Definite LDL (QDLDL) sparse decomposition.

Uses of MatrixDecomposition.Solver in org.ojalgo.optimisation.convex

Fields in org.ojalgo.optimisation.convex declared as MatrixDecomposition.Solver

Modifier and Type	Field	Description
private final MatrixDecomposition.Solver<Double>	BasePrimitiveSolver.mySolverGeneral
private final MatrixDecomposition.Solver<Double>	BasePrimitiveSolver.mySolverQ

Fields in org.ojalgo.optimisation.convex with type parameters of type MatrixDecomposition.Solver

Modifier and Type	Field	Description
private Function<Structure2D, MatrixDecomposition.Solver<Double>>	ConvexSolver.Configuration.mySolverGeneral
private Function<Structure2D, MatrixDecomposition.Solver<Double>>	ConvexSolver.Configuration.mySolverSPD

Methods in org.ojalgo.optimisation.convex that return MatrixDecomposition.Solver

Modifier and Type	Method	Description
MatrixDecomposition.Solver<Double>	ConvexSolver.Configuration.newSolverGeneral(Structure2D structure)
MatrixDecomposition.Solver<Double>	ConvexSolver.Configuration.newSolverSPD(Structure2D structure)

Method parameters in org.ojalgo.optimisation.convex with type arguments of type MatrixDecomposition.Solver

Modifier and Type	Method	Description
ConvexSolver.Configuration	ConvexSolver.Configuration.solverGeneral(Function<Structure2D, MatrixDecomposition.Solver<Double>> factory)	This matrix decomposition should be able to "invert" the full KKT systsem body matrix (which is symmetric) and/or its Schur complement with regards to the [Q] matrix (of quadratic terms).
ConvexSolver.Configuration	ConvexSolver.Configuration.solverSPD(Function<Structure2D, MatrixDecomposition.Solver<Double>> factory)	The [Q] matrix (of quadratic terms) is supposed to be symmetric positive definite (or at least semidefinite), but in reality there are usually many deficiencies.

Uses of MatrixDecomposition.Solver in org.ojalgo.random.process

Methods in org.ojalgo.random.process that return MatrixDecomposition.Solver

Modifier and Type	Method	Description
(package private) MatrixDecomposition.Solver<Double>	GaussianField.getC22()