 CGAL 5.3 - CGAL and Solvers
SparseLinearAlgebraTraits_d::Matrix Concept Reference

## Definition

SparseLinearAlgebraTraits_d::Matrix is a concept of a sparse matrix class.

Refines:
DefaultConstructible
Has Models:

CGAL::Eigen_sparse_matrix<T>

CGAL::Eigen_sparse_symmetric_matrix<T>

SparseLinearAlgebraTraits_d
SparseLinearAlgebraTraits_d::Vector

## Types

typedef unspecified_type Index
Index type.

typedef unspecified_type NT

## Creation

Matrix (Index dimension)
Create a square matrix initialized with zeros.

Matrix (Index rows, Index columns)
Create a rectangular matrix initialized with zeros.

## Operations

Index row_dimension () const
Return the matrix number of rows.

Index column_dimension () const
Return the matrix number of columns.

NT get_coef (Index row, Index column) const

void add_coef (Index row, Index column, NT value)
Write access to a matrix coefficient: a_ij = a_ij + val. More...

void set_coef (Index row, Index column, NT value, bool new_coef=false)
Write access to a matrix coefficient: a_ij = val. More...

void swap (Matrix &m)
Swaps the content of *this and m.

Matrix operator* (const NT &c, const Matrix &M)
Multiplication with a scalar.

Matrix operator+ (const Matrix &M0, const Matrix &M1)
Sum of two matrices.

## Member Function Documentation

 void SparseLinearAlgebraTraits_d::Matrix::add_coef ( Index row, Index column, NT value )

Write access to a matrix coefficient: a_ij = a_ij + val.

Precondition
0 <= row < row_dimension()
0 <= column < column_dimension()

## ◆ get_coef()

 NT SparseLinearAlgebraTraits_d::Matrix::get_coef ( Index row, Index column ) const

Precondition
0 <= row < row_dimension()
0 <= column < column_dimension()

## ◆ set_coef()

 void SparseLinearAlgebraTraits_d::Matrix::set_coef ( Index row, Index column, NT value, bool new_coef = false )

Write access to a matrix coefficient: a_ij = val.

Optimization: Users can indicate that the coefficient does not already exist in the matrix by setting new_coef to true.

Precondition
0 <= i < row_dimension()
0 <= j < column_dimension()