Concrete class implementing several nonlinear CG algorithms.
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#include <OptiPack_NonlinearCG_decl.hpp>
Inherits Describable, VerboseObject< NonlinearCG< Scalar > >, and ParameterListAcceptorDefaultBase.
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| typedef ScalarTraits< Scalar >::magnitudeType | ScalarMag |
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(Note that these are not member functions.)
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| const RCP< NonlinearCG< Scalar > > | nonlinearCG () |
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| template<typename Scalar > |
| const RCP< NonlinearCG< Scalar > > | nonlinearCG (const RCP< const Thyra::ModelEvaluator< Scalar > > &model, const int paramIndex, const int responseIndex, const RCP< GlobiPack::LineSearchBase< Scalar > > &linesearch) |
| | Nonmember constructor. More...
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template<typename Scalar>
class OptiPack::NonlinearCG< Scalar >
Concrete class implementing several nonlinear CG algorithms.
ToDo: Finish Documentation!
Definition at line 88 of file OptiPack_NonlinearCG_decl.hpp.
◆ ScalarMag
template<typename Scalar>
◆ NonlinearCG()
template<typename Scalar >
◆ initialize()
template<typename Scalar>
| void OptiPack::NonlinearCG< Scalar >::initialize |
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const RCP< const Thyra::ModelEvaluator< Scalar > > & |
model, |
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const int |
paramIndex, |
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const int |
responseIndex, |
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const RCP< GlobiPack::LineSearchBase< Scalar > > & |
linesearch |
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◆ get_solverType()
template<typename Scalar >
◆ get_alpha_init()
template<typename Scalar >
◆ get_alpha_reinit()
template<typename Scalar >
◆ get_and_conv_tests()
template<typename Scalar >
◆ get_minIters()
template<typename Scalar >
◆ get_maxIters()
template<typename Scalar >
◆ get_g_reduct_tol()
template<typename Scalar >
◆ get_g_grad_tol()
template<typename Scalar >
◆ get_g_mag()
template<typename Scalar >
◆ setParameterList()
template<typename Scalar >
◆ getValidParameters()
template<typename Scalar >
◆ doSolve()
template<typename Scalar>
Perform a solve.
- Parameters
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| p | [in/out] On input p is the initial guess for the solution. On output, will be the final estimate for the solution. |
| g_opt | [out] On output, *g_opt will be set to the final value of the objective function. |
| tol | [in] If !is_null(tol), then *tol will be the tolerance used to determine the convergence of the algorithm by comparing to norm(g_grad) (where norm(...) is the natural norm defined by the vector spaces scalar product). If is_null(tol), then the tolerance will be determined in some other way. |
| alpha_init | [in] If !is_null(alpha_init), then *alpha_init will be the initial line search step length on the very first nonlinear CG iteration. If is_null(alpha_init), the initial step length will be determined automatically. |
| numIters | [out] If nonnull(numIters), then on output *numIters gives the number of iterations taken by the algorithm. |
- Returns
- Returns
true if the solution was found. Returns false if a line search failure is encountered.
Definition at line 257 of file OptiPack_NonlinearCG_def.hpp.
◆ nonlinearCG() [1/2]
template<typename Scalar >
◆ nonlinearCG() [2/2]
template<typename Scalar >
| const RCP< NonlinearCG< Scalar > > nonlinearCG |
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const RCP< const Thyra::ModelEvaluator< Scalar > > & |
model, |
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const int |
paramIndex, |
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const int |
responseIndex, |
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const RCP< GlobiPack::LineSearchBase< Scalar > > & |
linesearch |
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related |
◆ model_
template<typename Scalar>
◆ paramIndex_
template<typename Scalar>
◆ responseIndex_
template<typename Scalar>
◆ linesearch_
template<typename Scalar>
◆ solverType_
template<typename Scalar>
◆ alpha_init_
template<typename Scalar>
◆ alpha_reinit_
template<typename Scalar>
◆ and_conv_tests_
template<typename Scalar>
◆ minIters_
template<typename Scalar>
◆ maxIters_
template<typename Scalar>
◆ g_reduct_tol_
template<typename Scalar>
◆ g_grad_tol_
template<typename Scalar>
◆ g_mag_
template<typename Scalar>
◆ numIters_
template<typename Scalar>
◆ solverType_validator_
template<typename Scalar>
| RCP< Teuchos::ParameterEntryValidator > OptiPack::NonlinearCG< Scalar >::solverType_validator_ = Teuchos::null |
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staticprivate |
The documentation for this class was generated from the following files: