SparseLinearAlgebraTraits_d Concept Reference Definition The concept SparseLinearAlgebraTraits_d is used to solve sparse linear systems A \( \times \) X = B. Has models CGAL::Eigen_solver_traits<T> Concepts class Vector SparseLinearAlgebraTraits_d::Vector is a concept of a vector that can be multiplied by a sparse matrix. More... class Matrix SparseLinearAlgebraTraits_d::Matrix is a concept of a sparse matrix class. More... Types typedef unspecified_type Matrix typedef unspecified_type Vector typedef unspecified_type NT Creation SparseLinearAlgebraTraits_d () Default constructor. Operations bool linear_solver (const Matrix &A, const Vector &B, Vector &X, NT &D) Solve the sparse linear system \(A \times X = B\). Member Function Documentation linear_solver() bool SparseLinearAlgebraTraits_d::linear_solver ( const Matrix & A, const Vector & B, Vector & X, NT & D ) Solve the sparse linear system \(A \times X = B\). Return true on success. The solution is then \((1/D) \times X \). PreconditionA.row_dimension() == B.dimension() A.column_dimension() == X.dimension() SparseLinearAlgebraTraits_d Generated by 1.17.0

Definition

The concept SparseLinearAlgebraTraits_d is used to solve sparse linear systems A \( \times \) X = B.

Has models

CGAL::Eigen_solver_traits<T>

Concepts
class	Vector
	SparseLinearAlgebraTraits_d::Vector is a concept of a vector that can be multiplied by a sparse matrix. More...
class	Matrix
	SparseLinearAlgebraTraits_d::Matrix is a concept of a sparse matrix class. More...

Types
typedef unspecified_type	Matrix
typedef unspecified_type	Vector
typedef unspecified_type	NT

Creation
	SparseLinearAlgebraTraits_d ()
	Default constructor.

Operations
bool	linear_solver (const Matrix &A, const Vector &B, Vector &X, NT &D)
	Solve the sparse linear system \(A \times X = B\).

Member Function Documentation

linear_solver()

bool SparseLinearAlgebraTraits_d::linear_solver	(	const Matrix &	A,
		const Vector &	B,
		Vector &	X,
		NT &	D )

Solve the sparse linear system \(A \times X = B\).

Return true on success. The solution is then \((1/D) \times X \).

Precondition

A.row_dimension() == B.dimension()

A.column_dimension() == X.dimension()