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MoochoPack : Framework for Large-Scale Optimization Algorithms
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00001 // @HEADER 00002 // *********************************************************************** 00003 // 00004 // Moocho: Multi-functional Object-Oriented arCHitecture for Optimization 00005 // Copyright (2003) Sandia Corporation 00006 // 00007 // Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive 00008 // license for use of this work by or on behalf of the U.S. Government. 00009 // 00010 // Redistribution and use in source and binary forms, with or without 00011 // modification, are permitted provided that the following conditions are 00012 // met: 00013 // 00014 // 1. Redistributions of source code must retain the above copyright 00015 // notice, this list of conditions and the following disclaimer. 00016 // 00017 // 2. Redistributions in binary form must reproduce the above copyright 00018 // notice, this list of conditions and the following disclaimer in the 00019 // documentation and/or other materials provided with the distribution. 00020 // 00021 // 3. Neither the name of the Corporation nor the names of the 00022 // contributors may be used to endorse or promote products derived from 00023 // this software without specific prior written permission. 00024 // 00025 // THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY 00026 // EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 00027 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 00028 // PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE 00029 // CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, 00030 // EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, 00031 // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00032 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00033 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00034 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00035 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00036 // 00037 // Questions? Contact Roscoe A. Bartlett (rabartl@sandia.gov) 00038 // 00039 // *********************************************************************** 00040 // @HEADER 00041 00042 #include <ostream> 00043 #include <typeinfo> 00044 #include <iostream> 00045 #include <math.h> 00046 00047 #include "AbstractLinAlgPack_VectorAuxiliaryOps.hpp" 00048 #include "AbstractLinAlgPack_MatrixSymDiagStd.hpp" 00049 #include "AbstractLinAlgPack_VectorStdOps.hpp" 00050 #include "AbstractLinAlgPack_VectorOut.hpp" 00051 #include "NLPInterfacePack_NLPBarrier.hpp" 00052 #include "MoochoPack_PostProcessBarrierLineSearch_Step.hpp" 00053 #include "MoochoPack_IpState.hpp" 00054 #include "MoochoPack_moocho_algo_conversion.hpp" 00055 #include "IterationPack_print_algorithm_step.hpp" 00056 #include "Teuchos_dyn_cast.hpp" 00057 #include "Teuchos_Assert.hpp" 00058 00059 #define min(a,b) ( (a < b) ? a : b ) 00060 #define max(a,b) ( (a > b) ? a : b ) 00061 00062 namespace MoochoPack { 00063 00064 PostProcessBarrierLineSearch_Step::PostProcessBarrierLineSearch_Step( 00065 Teuchos::RCP<NLPInterfacePack::NLPBarrier> barrier_nlp 00066 ) 00067 : 00068 barrier_nlp_(barrier_nlp) 00069 { 00070 TEUCHOS_TEST_FOR_EXCEPTION( 00071 !barrier_nlp_.get(), 00072 std::logic_error, 00073 "PostProcessBarrierLineSearch_Step given NULL NLPBarrier." 00074 ); 00075 } 00076 00077 00078 bool PostProcessBarrierLineSearch_Step::do_step( 00079 Algorithm& _algo, poss_type step_poss, IterationPack::EDoStepType type 00080 ,poss_type assoc_step_poss 00081 ) 00082 { 00083 using Teuchos::dyn_cast; 00084 using IterationPack::print_algorithm_step; 00085 using AbstractLinAlgPack::Vp_StV; 00086 00087 NLPAlgo &algo = dyn_cast<NLPAlgo>(_algo); 00088 IpState &s = dyn_cast<IpState>(_algo.state()); 00089 00090 EJournalOutputLevel olevel = algo.algo_cntr().journal_output_level(); 00091 std::ostream& out = algo.track().journal_out(); 00092 00093 // print step header. 00094 if( static_cast<int>(olevel) >= static_cast<int>(PRINT_ALGORITHM_STEPS) ) 00095 { 00096 using IterationPack::print_algorithm_step; 00097 print_algorithm_step( _algo, step_poss, type, assoc_step_poss, out ); 00098 } 00099 00100 // Get iteration quantities... 00101 value_type& f_kp1 = s.f().set_k(+1); 00102 f_kp1 = barrier_nlp_->objective_term(); 00103 00104 VectorMutable& Gf_kp1 = s.Gf().set_k(+1); 00105 Gf_kp1 = *(barrier_nlp_->grad_objective_term()); 00106 00107 if( static_cast<int>(olevel) >= static_cast<int>(PRINT_ALGORITHM_STEPS) ) 00108 { 00109 out << "\nf = " << f_kp1 00110 << "\nbarrier_term = " << barrier_nlp_->barrier_term() << std::endl; 00111 00112 } 00113 00114 if( static_cast<int>(olevel) >= static_cast<int>(PRINT_VECTORS) ) 00115 { 00116 out << "Gf = \n" << Gf_kp1 00117 << "\ngrad_barrier_term = \n" << *(barrier_nlp_->grad_barrier_term()); 00118 00119 } 00120 return true; 00121 } 00122 00123 00124 void PostProcessBarrierLineSearch_Step::print_step( 00125 const Algorithm& _algo, poss_type step_poss, IterationPack::EDoStepType type 00126 ,poss_type assoc_step_poss, std::ostream& out, const std::string& L 00127 ) const 00128 { 00129 //const NLPAlgo &algo = rsqp_algo(_algo); 00130 //const NLPAlgoState &s = algo.rsqp_state(); 00131 out << L << "# Process out the temporary barrier term used for line search\n" 00132 << L << "f_k -= barrier_term_k\n"; 00133 } 00134 } // end namespace MoochoPack
1.7.6.1