Please, help us to better know about our user community by answering the following short survey:
Eigen  3.3.9
Eigen::LeastSquaresConjugateGradient< _MatrixType, _Preconditioner > Class Template Reference

Detailed Description

template<typename _MatrixType, typename _Preconditioner>
class Eigen::LeastSquaresConjugateGradient< _MatrixType, _Preconditioner >

A conjugate gradient solver for sparse (or dense) least-square problems.

This class allows to solve for A x = b linear problems using an iterative conjugate gradient algorithm. The matrix A can be non symmetric and rectangular, but the matrix A' A should be positive-definite to guaranty stability. Otherwise, the SparseLU or SparseQR classes might be preferable. The matrix A and the vectors x and b can be either dense or sparse.

Template Parameters
_MatrixTypethe type of the matrix A, can be a dense or a sparse matrix.
_Preconditionerthe type of the preconditioner. Default is LeastSquareDiagonalPreconditioner

This class follows the sparse solver concept .

The maximal number of iterations and tolerance value can be controlled via the setMaxIterations() and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations and NumTraits<Scalar>::epsilon() for the tolerance.

This class can be used as the direct solver classes. Here is a typical usage example:

int m=1000000, n = 10000;
VectorXd x(n), b(m);
SparseMatrix<double> A(m,n);
// fill A and b
LeastSquaresConjugateGradient<SparseMatrix<double> > lscg;
x = lscg.solve(b);
std::cout << "#iterations: " << lscg.iterations() << std::endl;
std::cout << "estimated error: " << lscg.error() << std::endl;
// update b, and solve again
x = lscg.solve(b);

By default the iterations start with x=0 as an initial guess of the solution. One can control the start using the solveWithGuess() method.

See also
class ConjugateGradient, SparseLU, SparseQR

Public Member Functions

 LeastSquaresConjugateGradient ()
template<typename MatrixDerived >
 LeastSquaresConjugateGradient (const EigenBase< MatrixDerived > &A)

Constructor & Destructor Documentation

◆ LeastSquaresConjugateGradient() [1/2]

template<typename _MatrixType , typename _Preconditioner >
Eigen::LeastSquaresConjugateGradient< _MatrixType, _Preconditioner >::LeastSquaresConjugateGradient ( )

Default constructor.

◆ LeastSquaresConjugateGradient() [2/2]

template<typename _MatrixType , typename _Preconditioner >
template<typename MatrixDerived >
Eigen::LeastSquaresConjugateGradient< _MatrixType, _Preconditioner >::LeastSquaresConjugateGradient ( const EigenBase< MatrixDerived > &  A)

Initialize the solver with matrix A for further Ax=b solving.

This constructor is a shortcut for the default constructor followed by a call to compute().

this class stores a reference to the matrix A as well as some precomputed values that depend on it. Therefore, if A is changed this class becomes invalid. Call compute() to update it with the new matrix A, or modify a copy of A.

The documentation for this class was generated from the following file: