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MoochoPack : Framework for Large-Scale Optimization Algorithms
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00001 #if 0 00002 00003 // @HEADER 00004 // *********************************************************************** 00005 // 00006 // Moocho: Multi-functional Object-Oriented arCHitecture for Optimization 00007 // Copyright (2003) Sandia Corporation 00008 // 00009 // Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive 00010 // license for use of this work by or on behalf of the U.S. Government. 00011 // 00012 // Redistribution and use in source and binary forms, with or without 00013 // modification, are permitted provided that the following conditions are 00014 // met: 00015 // 00016 // 1. Redistributions of source code must retain the above copyright 00017 // notice, this list of conditions and the following disclaimer. 00018 // 00019 // 2. Redistributions in binary form must reproduce the above copyright 00020 // notice, this list of conditions and the following disclaimer in the 00021 // documentation and/or other materials provided with the distribution. 00022 // 00023 // 3. Neither the name of the Corporation nor the names of the 00024 // contributors may be used to endorse or promote products derived from 00025 // this software without specific prior written permission. 00026 // 00027 // THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY 00028 // EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 00029 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 00030 // PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE 00031 // CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, 00032 // EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, 00033 // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00034 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF 00035 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING 00036 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 00037 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00038 // 00039 // Questions? Contact Roscoe A. Bartlett (rabartl@sandia.gov) 00040 // 00041 // *********************************************************************** 00042 // @HEADER 00043 00044 #include <ostream> 00045 00046 #include "MoochoPack_ActSetStats_AddedStep.hpp" 00047 #include "MoochoPack_active_set_change.hpp" 00048 #include "MoochoPack_moocho_algo_conversion.hpp" 00049 #include "IterationPack_print_algorithm_step.hpp" 00050 #include "AbstractLinAlgPack/src/AbstractLinAlgPack_SpVectorClass.hpp" 00051 00052 bool MoochoPack::ActSetStats_AddedStep::do_step(Algorithm& _algo 00053 , poss_type step_poss, IterationPack::EDoStepType type, poss_type assoc_step_poss) 00054 { 00055 NLPAlgo &algo = rsqp_algo(_algo); 00056 NLPAlgoState &s = algo.rsqp_state(); 00057 00058 EJournalOutputLevel olevel = algo.algo_cntr().journal_output_level(); 00059 EJournalOutputLevel ns_olevel = algo.algo_cntr().null_space_journal_output_level(); 00060 std::ostream& out = algo.track().journal_out(); 00061 00062 // print step header. 00063 if( static_cast<int>(ns_olevel) >= static_cast<int>(PRINT_ALGORITHM_STEPS) ) { 00064 using IterationPack::print_algorithm_step; 00065 print_algorithm_step( algo, step_poss, type, assoc_step_poss, out ); 00066 } 00067 00068 if( s.nu().updated_k(0) ) { 00069 size_type 00070 num_active = 0, num_adds = 0, num_drops = 0, 00071 num_active_indep = 0, num_adds_indep = 0, num_drops_indep = 0; 00072 const SpVector &nu_k = s.nu().get_k(0); 00073 num_active = nu_k.nz(); 00074 if( s.nu().updated_k(-1) ) { 00075 const SpVector &nu_km1 = s.nu().get_k(-1); 00076 active_set_change( 00077 nu_k(), nu_km1(), s.var_indep(), olevel, &out 00078 ,&num_adds, &num_drops, &num_active_indep, &num_adds_indep, &num_drops_indep ); 00079 act_set_stats_(s).set_k(0).set_stats(num_active,num_adds,num_drops 00080 ,num_active_indep,num_adds_indep,num_drops_indep); 00081 } 00082 else { 00083 act_set_stats_(s).set_k(0).set_stats( 00084 num_active, ActSetStats::NOT_KNOWN, ActSetStats::NOT_KNOWN 00085 , nu_k(s.var_indep()).nz(), ActSetStats::NOT_KNOWN, ActSetStats::NOT_KNOWN ); 00086 } 00087 } 00088 else { 00089 if( static_cast<int>(ns_olevel) >= static_cast<int>(PRINT_ALGORITHM_STEPS) ) { 00090 out << "\nnu not calculated for the kth iteration\n"; 00091 } 00092 } 00093 00094 return true; 00095 } 00096 00097 void MoochoPack::ActSetStats_AddedStep::print_step( const Algorithm& algo 00098 , poss_type step_poss, IterationPack::EDoStepType type, poss_type assoc_step_poss 00099 , std::ostream& out, const std::string& L ) const 00100 { 00101 out 00102 << L << "*** Updates active set statistics for changes from the last iteration\n" 00103 << L << "Given nu_km1 and nu_k update:\n" 00104 << L << " act_set_stats_k(num_active,num_adds,num_drops,num_active_indep,num_adds_indep,num_drops_indep)\n"; 00105 } 00106 00107 #endif // 0
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