Uses of Class
org.ojalgo.matrix.store.R064CSC
Packages that use R064CSC
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Uses of R064CSC in org.ojalgo.matrix.decomposition
Fields in org.ojalgo.matrix.decomposition declared as R064CSCMethods in org.ojalgo.matrix.decomposition that return R064CSCModifier and TypeMethodDescriptionPermutes a symmetricR064CSCmatrix according to the computed ordering.Methods in org.ojalgo.matrix.decomposition with parameters of type R064CSCModifier and TypeMethodDescriptionvoidMinimumDegree.approximate(R064CSC matrix) Approximates a minimum degree ordering for a symmetricR064CSCmatrix.SparseQDLDL.computeEliminationTree(R064CSC matrix) private booleanSparseQDLDL.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.booleanRequirements on the input matrix and summary of the factorisation semantics: Square. Symmetric, with only the upper/right triangle stored.booleanSparseQDLDL.factor(R064CSC matrix, SparseQDLDL.EliminationTree eTree) Convenience for callers that have already computed the symbolic structure for a given sparsity pattern.Permutes a symmetricR064CSCmatrix according to the computed ordering. -
Uses of R064CSC in org.ojalgo.matrix.store
Subclasses with type arguments of type R064CSC in org.ojalgo.matrix.storeModifier and TypeClassDescriptionstatic final classA builder for constructingR064CSRinstances.Fields in org.ojalgo.matrix.store declared as R064CSCMethods in org.ojalgo.matrix.store that return R064CSCModifier and TypeMethodDescriptionR064CSC.Builder.build()R064CSC.copyCSC()Creates a deep copy of this CSC matrix store.ColumnsSupplier.toCSC()(package private) R064CSCColumnsSupplier.toCSC(int nbRows, int nbCols, int nbNz) R064CSC.toCSC()R064CSR.toCSC()RowsSupplier.toCSC()SparseStore.toCSC()SparseStructure2D.toCSC()R064CSR.transpose()Methods in org.ojalgo.matrix.store with parameters of type R064CSCModifier and TypeMethodDescriptionstatic voidR064CSC.btran(R064CSC mtrxL, int r, PhysicalStore<Double> arg) Assumes mtrxL is unit lower/left triangular, with the unit diagonal not stored.static voidR064CSC.calculateInfinityColumnNorms(R064CSC matrix, double[] norms) static voidR064CSC.calculateInfinityRowNorms(R064CSC matrix, double[] norms) static voidR064CSC.calculateInfinitySymmetricNorms(R064CSC matrix, double[] norms) Algorithm assumes that the matrix is symmetric, and only a triangular part is stored.static voidR064CSC.ftran(R064CSC mtrxL, int r, PhysicalStore<Double> arg) Assumes mtrxL is unit lower/left triangular, with the unit diagonal not stored.static voidTransposed matrix-vector multiplication: data' = left' * right (A'x = y invalid input: '<'-> x'A = y')static voidGeneral matrix-vector multiplication: data = left * rightstatic voidR064CSC.multiplySymmetric(double[] data, R064CSC matrix, double[] vector) For a symmetric matrix A, the matrix-vector products A * x and x * A are equal.static voidScales all non-zero entries of a sparse matrix by a scalar.static voidR064CSC.scaleColumns(R064CSC matrix, double[] scalars) static voidConstructors in org.ojalgo.matrix.store with parameters of type R064CSCModifierConstructorDescription(package private)NonZeroView(R064CSC matrix) (package private)NonZeroView(R064CSC matrix, int cursor)