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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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| LeastSquaresConjugateGradient () |
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template<typename MatrixDerived > |
| LeastSquaresConjugateGradient (const EigenBase< MatrixDerived > &A) |
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| ~LeastSquaresConjugateGradient () |
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void | _solve_impl (const Rhs &b, Dest &x) const |
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std::enable_if_t< Rhs::ColsAtCompileTime!=1 &&DestDerived::ColsAtCompileTime!=1 > | _solve_with_guess_impl (const Rhs &b, MatrixBase< DestDerived > &aDest) const |
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std::enable_if_t< Rhs::ColsAtCompileTime==1||DestDerived::ColsAtCompileTime==1 > | _solve_with_guess_impl (const Rhs &b, MatrixBase< DestDerived > &dest) const |
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void | _solve_with_guess_impl (const Rhs &b, SparseMatrixBase< DestDerived > &aDest) const |
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LeastSquaresConjugateGradient< MatrixType_, Preconditioner_ > & | analyzePattern (const EigenBase< MatrixDerived > &A) |
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EIGEN_CONSTEXPR Index | cols () const EIGEN_NOEXCEPT |
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LeastSquaresConjugateGradient< MatrixType_, Preconditioner_ > & | compute (const EigenBase< MatrixDerived > &A) |
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LeastSquaresConjugateGradient< MatrixType_, Preconditioner_ > & | derived () |
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const LeastSquaresConjugateGradient< MatrixType_, Preconditioner_ > & | derived () const |
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RealScalar | error () const |
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LeastSquaresConjugateGradient< MatrixType_, Preconditioner_ > & | factorize (const EigenBase< MatrixDerived > &A) |
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ComputationInfo | info () const |
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Index | iterations () const |
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| IterativeSolverBase () |
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| IterativeSolverBase (const EigenBase< MatrixDerived > &A) |
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| IterativeSolverBase (IterativeSolverBase &&)=default |
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Index | maxIterations () const |
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Preconditioner & | preconditioner () |
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const Preconditioner & | preconditioner () const |
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EIGEN_CONSTEXPR Index | rows () const EIGEN_NOEXCEPT |
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LeastSquaresConjugateGradient< MatrixType_, Preconditioner_ > & | setMaxIterations (Index maxIters) |
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LeastSquaresConjugateGradient< MatrixType_, Preconditioner_ > & | setTolerance (const RealScalar &tolerance) |
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const SolveWithGuess< LeastSquaresConjugateGradient< MatrixType_, Preconditioner_ >, Rhs, Guess > | solveWithGuess (const MatrixBase< Rhs > &b, const Guess &x0) const |
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RealScalar | tolerance () const |
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| ~IterativeSolverBase () |
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Derived & | derived () |
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const Derived & | derived () const |
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template<typename Rhs > |
const Solve< Derived, Rhs > | solve (const MatrixBase< Rhs > &b) const |
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template<typename Rhs > |
const Solve< Derived, Rhs > | solve (const SparseMatrixBase< Rhs > &b) const |
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| SparseSolverBase () |
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| SparseSolverBase (SparseSolverBase &&other) |
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| ~SparseSolverBase () |
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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 solves for the least-squares solution to A x = b 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
-
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;
SparseMatrix<double>
A(
m,
n);
LeastSquaresConjugateGradient<SparseMatrix<double> > lscg;
std::cout << "#iterations: " << lscg.iterations() << std::endl;
std::cout << "estimated error: " << lscg.error() << std::endl;
Matrix< double, Dynamic, 1 > VectorXd
DynamicĂ—1 vector of type double.
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
Definition at line 151 of file LeastSquareConjugateGradient.h.