Uses of Class
org.ojalgo.matrix.store.R064CSC

Packages that use R064CSC

Package	Description
org.ojalgo.matrix.decomposition
org.ojalgo.matrix.store

Uses of R064CSC in org.ojalgo.matrix.decomposition

Fields in org.ojalgo.matrix.decomposition declared as R064CSC

Modifier and Type	Field	Description
private R064CSC	SparseQDLDL.myL

Methods in org.ojalgo.matrix.decomposition that return R064CSC

Modifier and Type	Method	Description
R064CSC	MinimumDegree.permute(R064CSC original, int[] recording)	Permutes a symmetric R064CSC matrix according to the computed ordering.

Methods in org.ojalgo.matrix.decomposition with parameters of type R064CSC

Modifier and Type	Method	Description
void	MinimumDegree.approximate(R064CSC matrix)	Approximates a minimum degree ordering for a symmetric R064CSC matrix.
SparseQDLDL.EliminationTree	SparseQDLDL.computeEliminationTree(R064CSC matrix)
private boolean	SparseQDLDL.decompose(R064CSC matrix, SparseQDLDL.EliminationTree eTree, R064CSC decomp, double[] D, double[] Dinv, SparseQDLDL.WorkerCache workers)	In this method, variable names are deliberately kept close to what they are in the original c-code.
boolean	SparseQDLDL.factor(R064CSC matrix)	Requirements on the input matrix and summary of the factorisation semantics: Square. Symmetric, with only the upper/right triangle stored.
boolean	SparseQDLDL.factor(R064CSC matrix, SparseQDLDL.EliminationTree eTree)	Convenience for callers that have already computed the symbolic structure for a given sparsity pattern.
R064CSC	MinimumDegree.permute(R064CSC original, int[] recording)	Permutes a symmetric R064CSC matrix according to the computed ordering.

Uses of R064CSC in org.ojalgo.matrix.store

Fields in org.ojalgo.matrix.store declared as R064CSC

Modifier and Type	Field	Description
private R064CSC	R064CSC.NonZeroView.myMatrix

Methods in org.ojalgo.matrix.store that return R064CSC

Modifier and Type	Method	Description
R064CSC	R064CSC.Builder.build()
R064CSC	R064CSC.copyCSC()	Creates a deep copy of this CSC matrix store.
R064CSC	ColumnsSupplier.toCSC()
(package private) R064CSC	ColumnsSupplier.toCSC(int nbRows, int nbCols, int nbNz)
R064CSC	R064CSC.toCSC()
R064CSC	R064CSR.toCSC()
R064CSC	RowsSupplier.toCSC()
R064CSC	SparseStore.toCSC()
R064CSC	SparseStructure2D.toCSC()
R064CSC	R064CSR.transpose()

Methods in org.ojalgo.matrix.store with parameters of type R064CSC

Modifier and Type	Method	Description
static void	R064CSC.btran(R064CSC mtrxL, int r, PhysicalStore<java.lang.Double> arg)	Assumes mtrxL is unit lower/left triangular, with the unit diagonal not stored.
static void	R064CSC.calculateInfinityColumnNorms(R064CSC matrix, double[] norms)
static void	R064CSC.calculateInfinityRowNorms(R064CSC matrix, double[] norms)
static void	R064CSC.calculateInfinitySymmetricNorms(R064CSC matrix, double[] norms)	Algorithm assumes that the matrix is symmetric, and only a triangular part is stored.
static void	R064CSC.ftran(R064CSC mtrxL, int r, PhysicalStore<java.lang.Double> arg)	Assumes mtrxL is unit lower/left triangular, with the unit diagonal not stored.
static void	R064CSC.multiply(double[] data, double[] left, R064CSC right)	Transposed matrix-vector multiplication: data' = left' * right (A'x = y <-> x'A = y')
static void	R064CSC.multiply(double[] data, R064CSC left, double[] right)	General matrix-vector multiplication: data = left * right
static void	R064CSC.multiplySymmetric(double[] data, R064CSC matrix, double[] vector)	For a symmetric matrix A, the matrix-vector products A * x and x * A are equal.
static void	R064CSC.scale(R064CSC matrix, double scalar)	Scales all non-zero entries of a sparse matrix by a scalar.
static void	R064CSC.scaleColumns(R064CSC matrix, double[] scalars)
static void	R064CSC.scaleRows(R064CSC matrix, double[] scalars)

Constructors in org.ojalgo.matrix.store with parameters of type R064CSC

Constructor	Description
NonZeroView(R064CSC matrix)
NonZeroView(R064CSC matrix, int cursor)