MoochoPack : Framework for Large-Scale Optimization Algorithms Version of the Day
MoochoPack_QuasiRangeSpaceStepTailoredApproach_Strategy.cpp
00001 #if 0
00002 
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00006 // Moocho: Multi-functional Object-Oriented arCHitecture for Optimization
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00043 
00044 #include "MoochoPack_QuasiRangeSpaceStepTailoredApproach_Strategy.hpp"
00045 #include "MoochoPack_MoochoAlgorithmStepNames.hpp"
00046 #include "MoochoPack_NLPAlgo.hpp"
00047 #include "MoochoPack_NLPAlgoState.hpp"
00048 #include "MoochoPack/src/NLPrSQPTailoredApproach.h"
00049 #include "MoochoPack_EvalNewPointTailoredApproach_Step.hpp"
00050 #include "ConstrainedOptPack/src/DenseIdentVertConcatMatrixSubclass.h"
00051 #include "AbstractLinAlgPack/src/AbstractLinAlgPack_MatrixOp.hpp"
00052 #include "DenseLinAlgPack_LinAlgOpPack.hpp"
00053 #include "MiWorkspacePack.h"
00054 #include "Midynamic_cast_verbose.h"
00055 
00056 namespace LinAlgOpPack {
00057   using AbstractLinAlgPack::Vp_StMtV;
00058 }
00059 
00060 namespace MoochoPack {
00061 
00062 bool QuasiRangeSpaceStepTailoredApproach_Strategy::solve_quasi_range_space_step(
00063   std::ostream& out, EJournalOutputLevel olevel, NLPAlgo *algo, NLPAlgoState *s
00064   ,const DVectorSlice& xo, const DVectorSlice& c_xo, DVectorSlice* v
00065     )
00066 {
00067   using Teuchos::dyn_cast;
00068   using Teuchos::Workspace;
00069   Teuchos::WorkspaceStore* wss = Teuchos::get_default_workspace_store().get();
00070 
00071   // Get NLP reference
00072 #ifdef _WINDOWS
00073   NLPrSQPTailoredApproach
00074     &nlp  = dynamic_cast<NLPrSQPTailoredApproach&>(algo->nlp());
00075 #else
00076   NLPrSQPTailoredApproach
00077     &nlp  = dyn_cast<NLPrSQPTailoredApproach>(algo->nlp());
00078 #endif
00079 
00080   // Get D for Z_k = [ D; I ]
00081   const MatrixOp
00082     &Z_k = s->Z().get_k(0);
00083 #ifdef _WINDOWS
00084   const DenseIdentVertConcatMatrixSubclass
00085     &cZ_k = dynamic_cast<const DenseIdentVertConcatMatrixSubclass&>(Z_k);
00086 #else
00087   const DenseIdentVertConcatMatrixSubclass
00088     &cZ_k = dyn_cast<const DenseIdentVertConcatMatrixSubclass>(Z_k);
00089 #endif
00090   const DMatrixSlice
00091     D = cZ_k.m().D();
00092 
00093   // Get reference to EvalNewPoint step
00094 #ifdef _WINDOWS
00095   EvalNewPointTailoredApproach_Step
00096     &eval_tailored = dynamic_cast<EvalNewPointTailoredApproach_Step&>(
00097       *algo->get_step(algo->get_step_poss(EvalNewPoint_name)));
00098 #else
00099   EvalNewPointTailoredApproach_Step
00100     &eval_tailored = dyn_cast<EvalNewPointTailoredApproach_Step>(
00101       *algo->get_step(algo->get_step_poss(EvalNewPoint_name)));
00102 #endif
00103 
00104   // Compute an approximate newton step for constriants wy
00105   DVector c_xo_tmp = c_xo, vy_tmp;  // This is hacked.  This sucks!
00106   nlp.calc_semi_newton_step(xo,&c_xo_tmp,false,&vy_tmp);
00107     
00108   // Compute wy, Ywy
00109   eval_tailored.recalc_py_Ypy(D,&vy_tmp(),v,olevel,out);
00110 
00111   return true;
00112 }
00113 
00114 void QuasiRangeSpaceStepTailoredApproach_Strategy::print_step( std::ostream& out, const std::string& L ) const
00115 {
00116   out << L << "*** Compute the approximate range space step by calling on the \"Tailored Approach\" NLP interface:\n"
00117     << L << "Compute vy s.t. ||Gc_k'*Y_k*vy + c_xo|| << ||c_xo|| (nlp.calc_semi_newton_step(...))\n"
00118     << L << "update vy and compute v = Yvy from EvalNewPointTailoredApproach_Step::recalc_py_Ypy(...)\n";
00119     ;
00120 }
00121 
00122 } // end namespace MoochoPack
00123 
00124 #endif // 0
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