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Diffstat (limited to 'experimental/alignment-enabled/MGIZA/src/mkcls/RRTOptimization.cpp')
| -rw-r--r-- | experimental/alignment-enabled/MGIZA/src/mkcls/RRTOptimization.cpp | 217 |
1 files changed, 217 insertions, 0 deletions
diff --git a/experimental/alignment-enabled/MGIZA/src/mkcls/RRTOptimization.cpp b/experimental/alignment-enabled/MGIZA/src/mkcls/RRTOptimization.cpp new file mode 100644 index 0000000..55e2122 --- /dev/null +++ b/experimental/alignment-enabled/MGIZA/src/mkcls/RRTOptimization.cpp @@ -0,0 +1,217 @@ +/* + +Copyright (C) 1997,1998,1999,2000,2001 Franz Josef Och + +mkcls - a program for making word classes . + +This program is free software; you can redistribute it and/or +modify it under the terms of the GNU General Public License +as published by the Free Software Foundation; either version 2 +of the License, or (at your option) any later version. + +This program is distributed in the hope that it will be useful, +but WITHOUT ANY WARRANTY; without even the implied warranty of +MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +GNU General Public License for more details. + +You should have received a copy of the GNU General Public License +along with this program; if not, write to the Free Software +Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, +USA. + +*/ + + + + +#include "RRTOptimization.h" +#include "ProblemTest.h" + +double RRTOptimization::defaultAnnRate=0.6; +double RRTOptimization::defaultMultiple=2.0; + + + +RRTOptimization::RRTOptimization(Problem &p,double t,double dt,int m) +: IterOptimization(p,m),deviation(t),deltaDeviation(dt) +{ + assert(deviation>=0); +} + + + +RRTOptimization:: RRTOptimization(Problem &p,int m) +: IterOptimization(p,m),deviation(-1),deltaDeviation(0) +{ +} + + + +RRTOptimization::RRTOptimization(RRTOptimization &o) +: IterOptimization(o) +{ + deviation = o.deviation; + deltaDeviation= o.deltaDeviation; + record = o.record; +} + + + +void RRTOptimization::zInitialize() +{ + IterOptimization::zInitialize(); + if( deviation<0 ) + { + + + int n; + + StatVar &v=problem.deviationStatVar(*this,ANZ_VERSCHLECHTERUNGEN); + + if( maxStep>0 ) + n=(int)(maxStep*4.0/5.0); + else + maxStep=n=(int)(problem.expectedNumberOfIterations()*defaultMultiple); + + deviation = v.quantil(defaultAnnRate); + deltaDeviation = deviation/(float)n; + + if( verboseMode>0 ) + cout << "#Algorithm: Record-To-Record-Travel: (anfAnnRate=" + << defaultAnnRate << ",T=" << deviation << ",deltaT=" + << deltaDeviation << ")\n"; + + curStep=0; + endFlag=0; + delete &v; + problem.initialize(); + IterOptimization::zInitialize(); + } + record=problem.value(); + assert(deviation>=0); +} + +short RRTOptimization::end() +{ + return ( endFlag>0 && deviation==0.0 ); +} +void RRTOptimization::abkuehlen() +{ + if( deviation>=0 ) + { + deviation -= deltaDeviation; + if(deviation<0) + deviation=0; + } +} +short RRTOptimization::accept(double delta) +{ + if( deviation<0 ) + return 1; + else + { + if( delta + curValue - deviation < record ) + { + if( delta + curValue < record ) + record = delta+curValue; + return 1; + } + else + return 0; + } +} + +void RRTOptimization::makeGraphOutput() +{ + IterOptimization::makeGraphOutput(); + *GraphOutput << deviation; +} + + + + +double RRTOptimization::optimizeValue(Problem &p,int proParameter,int numParameter,int typ, + int optimierungsschritte,int print) +{ + switch(typ) + { + case 1: + { + double bestPar=-1,best=1e100; + if( print ) + cout << "#RRT-optimizeValues: Quantil: " << numParameter << endl; + for(int i=0;i<=numParameter;i++) + { + StatVar end,laufzeit,init; + double now; + if(i==0) defaultAnnRate=0.2; + else defaultAnnRate = 0.3+(float)(0.6*i)/numParameter; + solveProblem(0,p,proParameter,optimierungsschritte,RRT_OPT,now, + end,laufzeit,init); + if( best>now ) + { + best=now; + bestPar=defaultAnnRate; + } + if( print ) + { + cout << defaultAnnRate << " "; + cout << end.getMean() << " " << end.quantil(0.2) << " " + << end.quantil(0.79) << " " << laufzeit.getMean() << " " + << end.quantil(0.0) << " " << end.getSigma() << " " + << end.getSigmaSmaller() << " " << end.getSigmaBigger() + << " " << now << endl; + } + } + if( print ) + cout << "#Parameter Mittelwert 0.2-Quantil 0.8-Quantil Laufzeit " + "Bester Sigma SigmaSmaller SigmaBigger\n"; + defaultAnnRate=0.8; + return bestPar; + } + break; + case 10: + { + double i; + double bestPar=-1,best=1e100; + StatVar end,laufzeit,init; + + if( print ) + cout << "#RRT-optimizeValues: defaultMultiple" << 8 << endl; + for(i=0.5;i<=10;i+=1.5) + { + double now; + defaultMultiple = i; + solveProblem(0,p,proParameter,optimierungsschritte,RRT_OPT,now, + end,laufzeit,init); + if( best>now ) + { + best=now; + bestPar=defaultMultiple; + } + if( print ) + { + cout << defaultMultiple << " "; + cout << end.getMean() << " " << end.quantil(0.2) << " " + << end.quantil(0.79) << " " << laufzeit.getMean() << " " + << end.quantil(0.0) << " " << end.getSigma() << " " + << end.getSigmaSmaller() << " " << end.getSigmaBigger() + << " " << now << endl; + } + } + if( print ) + cout << "#Parameter Mittelwert 0.2-Quantil 0.8-Quantil Laufzeit " + "Bester Sigma SigmaSmaller SigmaBigger\n"; + defaultMultiple=2.0; + return bestPar; + } + break; + default: + cerr << "Error: wrong parameter-type in RRTOptimization::optimizeValue (" + << typ << ")\n"; + exit(1); + } + return 1e100; +} + + |