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| LeastSquaresConjugateGradient () |
| Default constructor. More...
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template<typename MatrixDerived > |
| LeastSquaresConjugateGradient (const EigenBase< MatrixDerived > &A) |
| Initialize the solver with matrix A for further Ax=b solving. More...
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| ~LeastSquaresConjugateGradient () |
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template<typename Rhs , typename Dest > |
void | _solve_vector_with_guess_impl (const Rhs &b, Dest &x) const |
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| IterativeSolverBase () |
| Default constructor. More...
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| IterativeSolverBase (const EigenBase< MatrixDerived > &A) |
| Initialize the solver with matrix A for further Ax=b solving. More...
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| ~IterativeSolverBase () |
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LeastSquaresConjugateGradient< _MatrixType, _Preconditioner > & | analyzePattern (const EigenBase< MatrixDerived > &A) |
| Initializes the iterative solver for the sparsity pattern of the matrix A for further solving Ax=b problems. More...
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LeastSquaresConjugateGradient< _MatrixType, _Preconditioner > & | factorize (const EigenBase< MatrixDerived > &A) |
| Initializes the iterative solver with the numerical values of the matrix A for further solving Ax=b problems. More...
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LeastSquaresConjugateGradient< _MatrixType, _Preconditioner > & | compute (const EigenBase< MatrixDerived > &A) |
| Initializes the iterative solver with the matrix A for further solving Ax=b problems. More...
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EIGEN_CONSTEXPR Index | rows () const EIGEN_NOEXCEPT |
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EIGEN_CONSTEXPR Index | cols () const EIGEN_NOEXCEPT |
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RealScalar | tolerance () const |
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LeastSquaresConjugateGradient< _MatrixType, _Preconditioner > & | setTolerance (const RealScalar &tolerance) |
| Sets the tolerance threshold used by the stopping criteria. More...
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Preconditioner & | preconditioner () |
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const Preconditioner & | preconditioner () const |
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Index | maxIterations () const |
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LeastSquaresConjugateGradient< _MatrixType, _Preconditioner > & | setMaxIterations (Index maxIters) |
| Sets the max number of iterations. More...
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Index | iterations () const |
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RealScalar | error () const |
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const SolveWithGuess< LeastSquaresConjugateGradient< _MatrixType, _Preconditioner >, Rhs, Guess > | solveWithGuess (const MatrixBase< Rhs > &b, const Guess &x0) const |
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ComputationInfo | info () const |
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void | _solve_with_guess_impl (const Rhs &b, SparseMatrixBase< DestDerived > &aDest) const |
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internal::enable_if< Rhs::ColsAtCompileTime!=1 &&DestDerived::ColsAtCompileTime!=1 >::type | _solve_with_guess_impl (const Rhs &b, MatrixBase< DestDerived > &aDest) const |
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internal::enable_if< Rhs::ColsAtCompileTime==1||DestDerived::ColsAtCompileTime==1 >::type | _solve_with_guess_impl (const Rhs &b, MatrixBase< DestDerived > &dest) const |
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void | _solve_impl (const Rhs &b, Dest &x) const |
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LeastSquaresConjugateGradient< _MatrixType, _Preconditioner > & | derived () |
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const LeastSquaresConjugateGradient< _MatrixType, _Preconditioner > & | derived () const |
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| SparseSolverBase () |
| Default constructor. More...
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| ~SparseSolverBase () |
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LeastSquaresConjugateGradient< _MatrixType, _Preconditioner > & | derived () |
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const LeastSquaresConjugateGradient< _MatrixType, _Preconditioner > & | derived () const |
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const Solve< LeastSquaresConjugateGradient< _MatrixType, _Preconditioner >, Rhs > | solve (const MatrixBase< Rhs > &b) const |
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const Solve< LeastSquaresConjugateGradient< _MatrixType, _Preconditioner >, Rhs > | solve (const SparseMatrixBase< Rhs > &b) const |
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void | _solve_impl (const SparseMatrixBase< Rhs > &b, SparseMatrixBase< Dest > &dest) const |
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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
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\implsparsesolverconcept
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;
std::cout <<
"#iterations: " << lscg.
iterations() << std::endl;
std::cout <<
"estimated error: " << lscg.
error() << std::endl;
RealScalar error() const
Definition: IterativeSolverBase.h:305
Derived & compute(const EigenBase< MatrixDerived > &A)
Initializes the iterative solver with the matrix A for further solving Ax=b problems.
Definition: IterativeSolverBase.h:238
Index iterations() const
Definition: IterativeSolverBase.h:296
A conjugate gradient solver for sparse (or dense) least-square problems.
Definition: LeastSquareConjugateGradient.h:150
A versatible sparse matrix representation.
Definition: SparseMatrix.h:98
const Solve< Derived, Rhs > solve(const MatrixBase< Rhs > &b) const
Definition: SparseSolverBase.h:88
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