Belos Version of the Day
Belos::LSQRSolMgr< ScalarType, MV, OP > Class Template Reference

The LSQRSolMgr managers the LSQR linear least squares solver. More...

#include <BelosLSQRSolMgr.hpp>

Inheritance diagram for Belos::LSQRSolMgr< ScalarType, MV, OP >:
Inheritance graph
[legend]

List of all members.

Public Member Functions

Construct/Destroy
 LSQRSolMgr ()
 Empty constructor for LSQRSolMgr. This constructor takes no arguments and sets the default values for the solver. The linear problem must be passed in using setProblem() before solve() is called on this object. The solver values can be changed using setParameters().
 LSQRSolMgr (const Teuchos::RCP< LinearProblem< ScalarType, MV, OP > > &problem, const Teuchos::RCP< Teuchos::ParameterList > &pl)
 Basic constructor for LSQRSolMgr.
virtual ~LSQRSolMgr ()
 Destructor.
Accessor methods
const LinearProblem
< ScalarType, MV, OP > & 		getProblem () const
 Get current linear problem being solved for in this object.
Teuchos::RCP< const
Teuchos::ParameterList > 		getValidParameters () const
 Get a parameter list containing the valid parameters for this object.
Teuchos::RCP< const
Teuchos::ParameterList > 		getCurrentParameters () const
 Get a parameter list containing the current parameters for this object.
Teuchos::Array< Teuchos::RCP
< Teuchos::Time > > 		getTimers () const
 Return the timers for this object.
int getNumIters () const
 Iteration count from the last solve.
MagnitudeType getMatCondNum () const
 Estimated matrix condition number from the last solve.
MagnitudeType getMatNorm () const
 Estimated matrix Frobenius norm from the last solve.
MagnitudeType getResNorm () const
 Estimated residual norm from the last solve.
MagnitudeType getMatResNorm () const
 Estimate of $A^* r$ (residual vector $r$) from the last solve.
bool isLOADetected () const
 Whether a loss of accuracy was detected during the last solve.
Set methods
void setProblem (const Teuchos::RCP< LinearProblem< ScalarType, MV, OP > > &problem)
 Set the linear problem that needs to be solved.
void setParameters (const Teuchos::RCP< Teuchos::ParameterList > &params)
 Set the parameters the solver manager should use to solve the linear problem.
Reset methods
void reset (const ResetType type)
 reset the solver manager as specified by the ResetType, informs the solver manager that the solver should prepare for the next call to solve by resetting certain elements of the iterative solver strategy.
Solver application methods
ReturnType solve ()
 method that performs possibly repeated calls to the underlying linear solver's iterate() routine until the problem has been solved (as defined by the solver manager) or the solver manager decides to quit.
Overridden from Teuchos::Describable
std::string description () const
 Method to return description of the LSQR solver manager.

Detailed Description

template<class ScalarType, class MV, class OP>
class Belos::LSQRSolMgr< ScalarType, MV, OP >

The LSQRSolMgr managers the LSQR linear least squares solver.

Implementation of the LSQR method for solving least-squares problems.

Author:
David Day
Sarah Knepper and David Day

The LSQR method (Paige and Saunders 1982)

LSQR solves a least-squares problem. A converged preconditioned residual norm suffices for convergence, but is not necessary. LSQR sometimes returns a larger relative residual norm than what would have been returned by a linear solver. For details on the stopping criteria, see the documentation of LSQRStatusTest, which implements the three-part stopping criterion recommended by Paige and Saunders.

If the linear problem to solve includes a preconditioner, then the least-squares problem is solved for the preconditioned linear system. Preconditioning changes the least-squares problem (in the sense of changing the norms), and the solution depends on the preconditioner in this sense.

In the context of linear least-squares problems, "preconditioning" refers to the regularization matrix. In this solver, the regularization matrix is always a scalar multiple of the identity (standard form least squares).

The "loss of accuracy" concept is not yet implemented here, becuase it is unclear what this means for linear least squares. LSQR solves an inconsistent system in a least-squares sense. "Loss of accuracy" would correspond to the difference between the preconditioned residual and the unpreconditioned residual.

References:

C. C. Paige and M. A. Saunders, LSQR: An algorithm for sparse linear equations and sparse least squares, TOMS 8(1), 43-71 (1982).

C. C. Paige and M. A. Saunders, Algorithm 583; LSQR: Sparse linear equations and least-squares problems, TOMS 8(2), 195-209 (1982).

See also the LSQR web page.

Definition at line 171 of file BelosLSQRSolMgr.hpp.

Constructor & Destructor Documentation

template<class ScalarType , class MV , class OP >
Belos::LSQRSolMgr< ScalarType, MV, OP >::LSQRSolMgr ( )

Empty constructor for LSQRSolMgr. This constructor takes no arguments and sets the default values for the solver. The linear problem must be passed in using setProblem() before solve() is called on this object. The solver values can be changed using setParameters().

Definition at line 411 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
Belos::LSQRSolMgr< ScalarType, MV, OP >::LSQRSolMgr ( const Teuchos::RCP< LinearProblem< ScalarType, MV, OP > > &  problem,
const Teuchos::RCP< Teuchos::ParameterList > &  pl 
)

Basic constructor for LSQRSolMgr.

This constructor accepts the LinearProblem to be solved in addition to a parameter list of options for the solver manager. Blocks of size > 1 are not implemented. The options are otherwise the BlockGmres options.

  • "Maximum Iterations" - the maximum number of iterations the LSQR solver is allowed to perform. Default: 1000
  • "Condition Limit" - a MagnitudeType specifying the upper limit of the estimate of the norm of Abar to decide convergence. Default: 0.
  • "Term Iter Max" - the number of consecutive successful iterations required before convergence is declared. Default: 1.
  • "Rel RHS Err" - an estimate of the error in the data defining the RHS. Default: 10*sqrt(eps).
  • "Rel Mat Err" - an estimate of the error in the data defining the matrix. Default: 10*sqrt(eps).
  • "Orthogonalization" - a string specifying the desired orthogonalization method. Default: "DGKS". See OrthoManagerFactory for a list of the available orthogonalization methods.
  • "Verbosity" - a sum of MsgType specifying the verbosity. Default: Belos::Errors
  • "Output Style" - a OutputType specifying the style of output. Default: Belos::General
  • "Lambda" - a MagnitudeType that specifies the regularization parameter.

Definition at line 420 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
virtual Belos::LSQRSolMgr< ScalarType, MV, OP >::~LSQRSolMgr ( ) [inline, virtual]

Destructor.

Definition at line 224 of file BelosLSQRSolMgr.hpp.

Member Function Documentation

template<class ScalarType , class MV , class OP >
const LinearProblem<ScalarType,MV,OP>& Belos::LSQRSolMgr< ScalarType, MV, OP >::getProblem ( ) const [inline, virtual]

Get current linear problem being solved for in this object.

Implements Belos::SolverManager< ScalarType, MV, OP >.

Definition at line 232 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
Teuchos::RCP< const Teuchos::ParameterList > Belos::LSQRSolMgr< ScalarType, MV, OP >::getValidParameters ( ) const [virtual]

Get a parameter list containing the valid parameters for this object.

Implements Belos::SolverManager< ScalarType, MV, OP >.

Definition at line 441 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
Teuchos::RCP<const Teuchos::ParameterList> Belos::LSQRSolMgr< ScalarType, MV, OP >::getCurrentParameters ( ) const [inline, virtual]

Get a parameter list containing the current parameters for this object.

Implements Belos::SolverManager< ScalarType, MV, OP >.

Definition at line 242 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
Teuchos::Array<Teuchos::RCP<Teuchos::Time> > Belos::LSQRSolMgr< ScalarType, MV, OP >::getTimers ( ) const [inline]

Return the timers for this object.

The timers are ordered as follows:

Definition at line 249 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
int Belos::LSQRSolMgr< ScalarType, MV, OP >::getNumIters ( ) const [inline, virtual]

Iteration count from the last solve.

Implements Belos::SolverManager< ScalarType, MV, OP >.

Definition at line 254 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
MagnitudeType Belos::LSQRSolMgr< ScalarType, MV, OP >::getMatCondNum ( ) const [inline]

Estimated matrix condition number from the last solve.

LSQR computes a running condition number estimate of the (preconditioned, if applicable) operator.

Definition at line 262 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
MagnitudeType Belos::LSQRSolMgr< ScalarType, MV, OP >::getMatNorm ( ) const [inline]

Estimated matrix Frobenius norm from the last solve.

LSQR computes a running Frobenius norm estimate of the (preconditioned, if applicable) operator.

Definition at line 270 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
MagnitudeType Belos::LSQRSolMgr< ScalarType, MV, OP >::getResNorm ( ) const [inline]

Estimated residual norm from the last solve.

LSQR computes the current residual norm. LSQR can solve inconsistent linear systems in a least-squares sense, so the residual norm may not necessarily be small, even if LSQR converges. (LSQR defines "convergence" to allow for possibly inconsistent systems. See the documentation of LSQRStatusTest for details.)

Definition at line 282 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
MagnitudeType Belos::LSQRSolMgr< ScalarType, MV, OP >::getMatResNorm ( ) const [inline]

Estimate of $A^* r$ (residual vector $r$) from the last solve.

Definition at line 287 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
bool Belos::LSQRSolMgr< ScalarType, MV, OP >::isLOADetected ( ) const [inline, virtual]

Whether a loss of accuracy was detected during the last solve.

The "loss of accuracy" concept is not yet implemented here, becuase it is unclear what this means for linear least squares. LSQR solves a possibly inconsistent linear system in a least-squares sense. "Loss of accuracy" would correspond to the difference between the preconditioned residual and the unpreconditioned residual.

Implements Belos::SolverManager< ScalarType, MV, OP >.

Definition at line 299 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
void Belos::LSQRSolMgr< ScalarType, MV, OP >::setProblem ( const Teuchos::RCP< LinearProblem< ScalarType, MV, OP > > &  problem) [inline, virtual]

Set the linear problem that needs to be solved.

Implements Belos::SolverManager< ScalarType, MV, OP >.

Definition at line 307 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
void Belos::LSQRSolMgr< ScalarType, MV, OP >::setParameters ( const Teuchos::RCP< Teuchos::ParameterList > &  params) [virtual]

Set the parameters the solver manager should use to solve the linear problem.

Implements Belos::SolverManager< ScalarType, MV, OP >.

Definition at line 528 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
void Belos::LSQRSolMgr< ScalarType, MV, OP >::reset ( const ResetType  type) [inline, virtual]

reset the solver manager as specified by the ResetType, informs the solver manager that the solver should prepare for the next call to solve by resetting certain elements of the iterative solver strategy.

Implements Belos::SolverManager< ScalarType, MV, OP >.

Definition at line 320 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
Belos::ReturnType Belos::LSQRSolMgr< ScalarType, MV, OP >::solve ( ) [virtual]

method that performs possibly repeated calls to the underlying linear solver's iterate() routine until the problem has been solved (as defined by the solver manager) or the solver manager decides to quit.

This method calls LSQRIter::iterate(), which will return either because a specially constructed status test evaluates to Passed or an std::exception is thrown.

A return from LSQRIter::iterate() signifies that either

  • the maximum number of iterations has been exceeded ... "return ::Unconverged".
  • ... or convergence ... "solver manager will return ::Converged" In either case the current solution is in the linear problem
Returns:
ReturnType specifying:
  • Converged: the linear problem was solved to the specification required by the solver manager.
  • Unconverged: the linear problem was not solved to the specification desired by the solver manager.

Implements Belos::SolverManager< ScalarType, MV, OP >.

Definition at line 834 of file BelosLSQRSolMgr.hpp.

template<class ScalarType , class MV , class OP >
std::string Belos::LSQRSolMgr< ScalarType, MV, OP >::description ( ) const [virtual]

Method to return description of the LSQR solver manager.

Reimplemented from Teuchos::Describable.

Definition at line 977 of file BelosLSQRSolMgr.hpp.

The documentation for this class was generated from the following file:
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines
Generated on Tue May 22 2012 09:11:24 for Belos by  doxygen 1.7.4