Public Member Functions | |
def | __init__ |
def | getProblem |
def | getNumIters |
def | getTimers |
def | solve |
def | setGlobalStatusTest |
def | getGlobalStatusTest |
def | setLockingStatusTest |
def | getLockingStatusTest |
def | setDebugStatusTest |
def | getDebugStatusTest |
def | __init__ |
def | getProblem |
def | getNumIters |
def | getTimers |
def | solve |
def | setGlobalStatusTest |
def | getGlobalStatusTest |
def | setLockingStatusTest |
def | getLockingStatusTest |
def | setDebugStatusTest |
def | getDebugStatusTest |
Public Attributes | |
this |
The BlockDavidsonSolMgr provides a powerful solver manager over the BlockDavidson eigensolver. This solver manager implements a hard-locking mechanism, whereby eigenpairs designated to be locked are moved from the eigensolver and placed in auxilliary storage. The eigensolver is then restarted and continues to iterate, orthogonal to the locked eigenvectors. The solver manager provides to the solver a StatusTestCombo object constructed as follows: combo = globaltest OR lockingtest OR debugtest where globaltest terminates computation when global convergence has been detected. It is encapsulated in a StatusTestWithOrdering object, to ensure that computation is terminated only after the most significant eigenvalues/eigenvectors have met the convergence criteria. If not specified via setGlobalStatusTest(), globaltest is a StatusTestResNorm object which tests the M-norms of the direct residuals relative to the Ritz values. lockingtest halts BlockDavidson::iterate() in order to deflate converged eigenpairs for locking. It will query the underlying BlockDavidson eigensolver to determine when eigenvectors should be locked. If not specified via setLockingStatusTest(), lockingtest is a StatusTestResNorm object. debugtest allows a user to specify additional monitoring of the iteration, encapsulated in a StatusTest object If not specified via setDebugStatusTest(), debugtest is ignored. In most cases, it should return Failed; if it returns Passed, solve() will throw an AnasaziError exception. Additionally, the solver manager will terminate solve() after a specified number of restarts. Much of this behavior is controlled via parameters and options passed to the solver manager. For more information, see BlockDavidsonSolMgr(). Chris Baker, Ulrich Hetmaniuk, Rich Lehoucq, Heidi Thornquist C++ includes: AnasaziBlockDavidsonSolMgr.hpp
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::__init__ | ( | self, | ||
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__init__(self, Teuchos::RCP<(Anasazi::Eigenproblem<(double,Epetra_MultiVector,Epetra_Operator)>)> problem, ParameterList pl) -> BlockDavidsonSolMgrEpetra Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::BlockDavidsonSolMgr(const Teuchos::RCP< Eigenproblem< ScalarType, MV, OP > > &problem, Teuchos::ParameterList &pl) Basic constructor for BlockDavidsonSolMgr. This constructor accepts the Eigenproblem to be solved in addition to a parameter list of options for the solver manager. These options include the following: Solver parameters "Which" - a string specifying the desired eigenvalues: SM, LM, SR or LR. Default: "SR" "Block Size" - a int specifying the block size to be used by the underlying block Davidson solver. Default: problem->getNEV() "Num Blocks" - a int specifying the number of blocks allocated for the Krylov basis. Default: 2 "Maximum Restarts" - a int specifying the maximum number of restarts the underlying solver is allowed to perform. Default: 20 "Verbosity" - a sum of MsgType specifying the verbosity. Default: Errors Convergence parameters (if using default convergence test; see setGlobalStatusTest()) "Convergence Tolerance" - a MagnitudeType specifying the level that residual norms must reach to decide convergence. Default: machine precision. "Relative Convergence Tolerance" - a bool specifying whether residuals norms should be scaled by their eigenvalues for the purposing of deciding convergence. Default: true "Convergence Norm" - a string specifying the norm for convergence testing: "2" or "M" Locking parameters (if using default locking test; see setLockingStatusTest()) "Use Locking" - a bool specifying whether the algorithm should employ locking of converged eigenpairs. Default: false "Max Locked" - a int specifying the maximum number of eigenpairs to be locked. Default: problem->getNEV() "Locking Quorum" - a int specifying the number of eigenpairs that must meet the locking criteria before locking actually occurs. Default: 1 "Locking Tolerance" - a MagnitudeType specifying the level that residual norms must reach to decide locking. Default: 0.1*convergence tolerance "Relative Locking Tolerance" - a bool specifying whether residuals norms should be scaled by their eigenvalues for the purposing of deciding locking. Default: true "Locking Norm" - a string specifying the norm for locking testing: "2" or "M"
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::__init__ | ( | self, | ||
args | ||||
) |
__init__(self, Teuchos::RCP<(Anasazi::Eigenproblem<(double,Epetra_MultiVector,Epetra_Operator)>)> problem, ParameterList pl) -> BlockDavidsonSolMgrEpetra Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::BlockDavidsonSolMgr(const Teuchos::RCP< Eigenproblem< ScalarType, MV, OP > > &problem, Teuchos::ParameterList &pl) Basic constructor for BlockDavidsonSolMgr. This constructor accepts the Eigenproblem to be solved in addition to a parameter list of options for the solver manager. These options include the following: Solver parameters "Which" - a string specifying the desired eigenvalues: SM, LM, SR or LR. Default: "SR" "Block Size" - a int specifying the block size to be used by the underlying block Davidson solver. Default: problem->getNEV() "Num Blocks" - a int specifying the number of blocks allocated for the Krylov basis. Default: 2 "Maximum Restarts" - a int specifying the maximum number of restarts the underlying solver is allowed to perform. Default: 20 "Verbosity" - a sum of MsgType specifying the verbosity. Default: Errors Convergence parameters (if using default convergence test; see setGlobalStatusTest()) "Convergence Tolerance" - a MagnitudeType specifying the level that residual norms must reach to decide convergence. Default: machine precision. "Relative Convergence Tolerance" - a bool specifying whether residuals norms should be scaled by their eigenvalues for the purposing of deciding convergence. Default: true "Convergence Norm" - a string specifying the norm for convergence testing: "2" or "M" Locking parameters (if using default locking test; see setLockingStatusTest()) "Use Locking" - a bool specifying whether the algorithm should employ locking of converged eigenpairs. Default: false "Max Locked" - a int specifying the maximum number of eigenpairs to be locked. Default: problem->getNEV() "Locking Quorum" - a int specifying the number of eigenpairs that must meet the locking criteria before locking actually occurs. Default: 1 "Locking Tolerance" - a MagnitudeType specifying the level that residual norms must reach to decide locking. Default: 0.1*convergence tolerance "Relative Locking Tolerance" - a bool specifying whether residuals norms should be scaled by their eigenvalues for the purposing of deciding locking. Default: true "Locking Norm" - a string specifying the norm for locking testing: "2" or "M"
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getDebugStatusTest | ( | self, | ||
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) |
getDebugStatusTest(self) -> Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > & Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getDebugStatusTest() const Get the status test for debugging.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getDebugStatusTest | ( | self, | ||
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) |
getDebugStatusTest(self) -> Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > & Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getDebugStatusTest() const Get the status test for debugging.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getGlobalStatusTest | ( | self, | ||
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) |
getGlobalStatusTest(self) -> Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > & Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getGlobalStatusTest() const Get the status test defining global convergence.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getGlobalStatusTest | ( | self, | ||
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) |
getGlobalStatusTest(self) -> Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > & Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getGlobalStatusTest() const Get the status test defining global convergence.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getLockingStatusTest | ( | self, | ||
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getLockingStatusTest(self) -> Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > & Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getLockingStatusTest() const Get the status test defining locking.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getLockingStatusTest | ( | self, | ||
args | ||||
) |
getLockingStatusTest(self) -> Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > & Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getLockingStatusTest() const Get the status test defining locking.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getNumIters | ( | self, | ||
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getNumIters(self) -> int int Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getNumIters() const Get the iteration count for the most recent call to solve().
Reimplemented from PyTrilinos::Anasazi::SolverManagerEpetra.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getNumIters | ( | self, | ||
args | ||||
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getNumIters(self) -> int int Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getNumIters() const Get the iteration count for the most recent call to solve().
Reimplemented from PyTrilinos::Anasazi::SolverManagerEpetra.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getProblem | ( | self, | ||
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getProblem(self) -> EigenproblemEpetra const Eigenproblem<ScalarType,MV,OP>& Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getProblem() const Return the eigenvalue problem.
Reimplemented from PyTrilinos::Anasazi::SolverManagerEpetra.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getProblem | ( | self, | ||
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getProblem(self) -> EigenproblemEpetra const Eigenproblem<ScalarType,MV,OP>& Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getProblem() const Return the eigenvalue problem.
Reimplemented from PyTrilinos::Anasazi::SolverManagerEpetra.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getTimers | ( | self, | ||
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getTimers(self) -> Teuchos::Array<(Teuchos::RCP<(Teuchos::Time)>)> Teuchos::Array<Teuchos::RCP<Teuchos::Time> > Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getTimers() const Return the timers for this object. The timers are ordered as follows: time spent in solve() routine time spent restarting time spent locking converged eigenvectors
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::getTimers | ( | self, | ||
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getTimers(self) -> Teuchos::Array<(Teuchos::RCP<(Teuchos::Time)>)> Teuchos::Array<Teuchos::RCP<Teuchos::Time> > Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::getTimers() const Return the timers for this object. The timers are ordered as follows: time spent in solve() routine time spent restarting time spent locking converged eigenvectors
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::setDebugStatusTest | ( | self, | ||
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setDebugStatusTest(self, Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> debug) void Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::setDebugStatusTest(const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > &debug) Set the status test for debugging.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::setDebugStatusTest | ( | self, | ||
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setDebugStatusTest(self, Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> debug) void Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::setDebugStatusTest(const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > &debug) Set the status test for debugging.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::setGlobalStatusTest | ( | self, | ||
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setGlobalStatusTest(self, Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> _global) void Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::setGlobalStatusTest(const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > &global) Set the status test defining global convergence.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::setGlobalStatusTest | ( | self, | ||
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setGlobalStatusTest(self, Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> _global) void Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::setGlobalStatusTest(const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > &global) Set the status test defining global convergence.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::setLockingStatusTest | ( | self, | ||
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setLockingStatusTest(self, Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> locking) void Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::setLockingStatusTest(const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > &locking) Set the status test defining locking.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::setLockingStatusTest | ( | self, | ||
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setLockingStatusTest(self, Teuchos::RCP<(Anasazi::StatusTest<(double,Epetra_MultiVector,Epetra_Operator)>)> locking) void Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::setLockingStatusTest(const Teuchos::RCP< StatusTest< ScalarType, MV, OP > > &locking) Set the status test defining locking.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::solve | ( | self, | ||
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solve(self) -> ReturnType ReturnType Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::solve() This method performs possibly repeated calls to the underlying eigensolver's iterate() routine until the problem has been solved (as decided by the solver manager) or the solver manager decides to quit. This method calls BlockDavidson::iterate(), which will return either because a specially constructed status test evaluates to Passed or an exception is thrown. A return from BlockDavidson::iterate() signifies one of the following scenarios: the maximum number of restarts has been exceeded. In this scenario, the solver manager will place all converged eigenpairs into the eigenproblem and return Unconverged. the locking conditions have been met. In this scenario, some of the current eigenpairs will be removed from the eigensolver and placed into auxiliary storage. The eigensolver will be restarted with the remaining part of the Krylov subspace and some random information to replace the removed subspace. global convergence has been met. In this case, the most significant NEV eigenpairs in the solver and locked storage have met the convergence criterion. (Here, NEV refers to the number of eigenpairs requested by the Eigenproblem.) In this scenario, the solver manager will return Converged. ReturnType specifying: Converged: the eigenproblem was solved to the specification required by the solver manager. Unconverged: the eigenproblem was not solved to the specification desired by the solver manager.
Reimplemented from PyTrilinos::Anasazi::SolverManagerEpetra.
def PyTrilinos::Anasazi::BlockDavidsonSolMgrEpetra::solve | ( | self, | ||
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) |
solve(self) -> ReturnType ReturnType Anasazi::BlockDavidsonSolMgr< ScalarType, MV, OP >::solve() This method performs possibly repeated calls to the underlying eigensolver's iterate() routine until the problem has been solved (as decided by the solver manager) or the solver manager decides to quit. This method calls BlockDavidson::iterate(), which will return either because a specially constructed status test evaluates to Passed or an exception is thrown. A return from BlockDavidson::iterate() signifies one of the following scenarios: the maximum number of restarts has been exceeded. In this scenario, the solver manager will place all converged eigenpairs into the eigenproblem and return Unconverged. the locking conditions have been met. In this scenario, some of the current eigenpairs will be removed from the eigensolver and placed into auxiliary storage. The eigensolver will be restarted with the remaining part of the Krylov subspace and some random information to replace the removed subspace. global convergence has been met. In this case, the most significant NEV eigenpairs in the solver and locked storage have met the convergence criterion. (Here, NEV refers to the number of eigenpairs requested by the Eigenproblem.) In this scenario, the solver manager will return Converged. ReturnType specifying: Converged: the eigenproblem was solved to the specification required by the solver manager. Unconverged: the eigenproblem was not solved to the specification desired by the solver manager.
Reimplemented from PyTrilinos::Anasazi::SolverManagerEpetra.