CGAL 4.7 - Planar Parameterization of Triangulated Surface Meshes: SparseLinearAlgebraTraits_d::Matrix Concept Reference

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CGAL 4.7 - Planar Parameterization of Triangulated Surface Meshes

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SparseLinearAlgebraTraits_d::Matrix Concept Reference
Concepts

## Definition

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

Refines:
  `LinearAlgebraTraits_d::Matrix`

Has Models:

  `CGAL::Eigen_sparse_matrix<T>`

  `CGAL::Eigen_sparse_symmetric_matrix<T>`

  `OpenNL::SparseMatrix<T>` in `OpenNL` package

See Also
  `SparseLinearAlgebraTraits_d`
  `SparseLinearAlgebraTraits_d::Vector`

## Types

typedef unspecified_type | NT

## Creation

| Matrix (int dimension)
| Create a square matrix initialized with zeros.
| Matrix (int rows, int columns)
| Create a rectangular matrix initialized with zeros.

## Operations

int | row_dimension () const
| Return the matrix number of rows.
int | column_dimension () const
| Return the matrix number of columns.
NT | get_coef (int row, int column) const
| Read access to a matrix coefficient. More...
void | add_coef (int row, int column, NT value)
| Write access to a matrix coefficient: `a_ij = a_ij + val`. More...
void | set_coef (int row, int column, NT value, bool new_coef=false)
| Write access to a matrix coefficient: `a_ij = val`. More...

## Member Function Documentation

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

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

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

NT SparseLinearAlgebraTraits_d::Matrix::get_coef | ( | int | row,
|  | int | column
| ) |  | const

Read access to a matrix coefficient.

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

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

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

Optimization: Caller can optimize this call by setting `new_coef` to true if the coefficient does not already exist in the matrix.

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