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 java.lang.Comparable<N>>	Cholesky: [A] = [L][L]H (or [R]H[R])
static interface	Eigenvalue.Spectral<N extends java.lang.Comparable<N>>	“Spectral decomposition” refers specifically to the orthogonal/unitary eigen-decomposition of a normal matrix (most commonly Hermitian / symmetric).
interface	LDL<N extends java.lang.Comparable<N>>	LDL: [A] = [L][D][L]H (or [R]H[D][R])
interface	LDU<N extends java.lang.Comparable<N>>	LDU: [A] = [L][D][U] ( [PL][L][D][U][PU] )
interface	LU<N extends java.lang.Comparable<N>>	LU: [A] = [L][U]
interface	QR<N extends java.lang.Comparable<N>>	QR: [A] = [Q][R] Decomposes [this] into [Q] and [R] where: [Q] is an orthogonal matrix (orthonormal columns).
interface	SingularValue<N extends java.lang.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 java.lang.Comparable<N>>
(package private) static class	DenseCholesky.C128
(package private) static class	DenseCholesky.H256
(package private) static class	DenseCholesky.Q128
(package private) static class	DenseCholesky.R064
(package private) static class	DenseCholesky.R128
(package private) class	DenseLDL<N extends java.lang.Comparable<N>>
(package private) static class	DenseLDL.C128
(package private) static class	DenseLDL.H256
(package private) static class	DenseLDL.Q128
(package private) static class	DenseLDL.R064
(package private) static class	DenseLDL.R128
(package private) class	DenseLU<N extends java.lang.Comparable<N>>
(package private) static class	DenseLU.C128
(package private) static class	DenseLU.H256
(package private) static class	DenseLU.Q128
(package private) static class	DenseLU.R064
(package private) static class	DenseLU.R128
(package private) class	DenseQR<N extends java.lang.Comparable<N>>
(package private) static class	DenseQR.C128
(package private) static class	DenseQR.H256
(package private) static class	DenseQR.Q128
(package private) static class	DenseQR.R064
(package private) static class	DenseQR.R128
(package private) class	DenseSingularValue<N extends java.lang.Comparable<N>>
(package private) static class	DenseSingularValue.C128
(package private) static class	DenseSingularValue.H256
(package private) static class	DenseSingularValue.Q128
(package private) static class	DenseSingularValue.R064
(package private) static class	DenseSingularValue.R128
(package private) class	HermitianEvD<N extends java.lang.Comparable<N>>	Eigenvalues and eigenvectors of a real matrix.
(package private) static class	HermitianEvD.C128
(package private) static class	HermitianEvD.H256
(package private) static class	HermitianEvD.Q128
(package private) static class	HermitianEvD.R064
(package private) static class	HermitianEvD.R128
(package private) class	RawCholesky
(package private) static class	RawEigenvalue.Symmetric
(package private) class	RawLU
(package private) 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) class	RawSingularValue	Singular Value Decomposition.
(package private) class	SparseLU	A sparse, primitive double based, LU decomposition with support for incremental Forrest-Tomlin updates.

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 MatrixDecomposition.Solver<java.lang.Double>	BasePrimitiveSolver.mySolverGeneral
private MatrixDecomposition.Solver<java.lang.Double>	BasePrimitiveSolver.mySolverQ

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

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

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

Modifier and Type	Method	Description
MatrixDecomposition.Solver<java.lang.Double>	ConvexSolver.Configuration.newSolverGeneral(Structure2D structure)
MatrixDecomposition.Solver<java.lang.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(java.util.function.Function<Structure2D,MatrixDecomposition.Solver<java.lang.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(java.util.function.Function<Structure2D,MatrixDecomposition.Solver<java.lang.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<java.lang.Double>	GaussianField.getC22()