SvdTraits

Navigation: Up Table of Contents Package Overview Bibliography Index Title Acknowledging CGAL

SvdTraits

Definition

The concept SvdTraits describes the set of requirements to be fulfilled by any class used to instantiate the third template parameter of the class Monge_via_jet_fitting<DataKernel,LocalKernel,SvdTraits>.

It describes the linear algebra types and algorithms needed by the class Monge_via_jet_fitting.

Requirements

The scalar type, SvdTraits::FT, must be the same as that of the LocalKernel concept : LocalKernel::FT.

Types

SvdTraits::FT
	The scalar type.
SvdTraits::Vector
	The vector type.
SvdTraits::Matrix
	The matrix type.

Operations

SvdTraits vector ( size_t n);
	initialize all the elements of the vector to zero.

The type Vector has the access methods

size_t	vector.size ()
FT	vector ( size_t i )	return the i^th entry, i from 0 to size()-1.
void	vector.set ( size_t i, const FT value)
		set the i^th entry to value.

The type Matrix has the access methods

SvdTraits matrix ( size_t n1, size_t n2);
	initialize all the entries of the matrix to zero.

size_t	matrix.number_of_rows ()
size_t	matrix.number_of_columns ()
FT	matrix ( size_t i , size_t j )	return the entry at row i and column j, i from 0 to number_of_rows - 1, j from 0 to number_of_columns - 1.
void	matrix.set ( size_t i, size_t j, const FT value)
		set the entry at row i and column j to value.

The concept SvdTraits has a linear solver using a singular value decomposition algorithm.

FT	traits.solve ( Matrix& M, Vector& B)
		Solves the system MX=B (in the least square sense if M is not square) using a singular value decomposition and returns the condition number of M. The solution is stored in B.

Has Models

Lapack_svd.

SvdTraits

Definition

Requirements

Types

Operations

Has Models

See Also