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Diffstat (limited to 'mkcls-v2/TAOptimization.cpp')
| -rw-r--r-- | mkcls-v2/TAOptimization.cpp | 208 |
1 files changed, 208 insertions, 0 deletions
diff --git a/mkcls-v2/TAOptimization.cpp b/mkcls-v2/TAOptimization.cpp new file mode 100644 index 0000000..074ff62 --- /dev/null +++ b/mkcls-v2/TAOptimization.cpp @@ -0,0 +1,208 @@ +/* + +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 "TAOptimization.h" +#include "ProblemTest.h" + + +double TAOptimization::defaultAnnRate=0.4; +double TAOptimization::defaultMultiple=2.0; + + +TAOptimization::TAOptimization(Problem &p,double t,double d,int m) +: IterOptimization(p,m) , temperatur(t) , deltaTemperatur(d) +{ + assert(t>0 && d>0); +} + + + +TAOptimization::TAOptimization(Problem&p,int m) +: IterOptimization(p,m), temperatur(-1) +{ +} + + + +TAOptimization::TAOptimization(TAOptimization &o) +: IterOptimization(o) +{ + temperatur= o.temperatur; + deltaTemperatur= o.deltaTemperatur; +} + + + + +void TAOptimization::zInitialize() +{ + IterOptimization::zInitialize(); + if( temperatur<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); + + temperatur = v.quantil(defaultAnnRate); + deltaTemperatur = temperatur/n; + + if( verboseMode>0 ) + cout << "#TA: (anfAnnRate=" + << defaultAnnRate << ",T=" << temperatur << ",deltaT=" + << deltaTemperatur << ")\n"; + curStep=0; + endFlag=0; + delete &v; + } +} + + +short TAOptimization::end() +{ + + + if( temperatur>0 ) + { + endFlag=0; + bestStep=curStep; + } + return endFlag>0; +} + +short TAOptimization::accept(double delta) +{ + if( temperatur<0 ) + return 1; + else + if( delta < temperatur ) + return 1; + else + return 0; +} + +void TAOptimization::abkuehlen() +{ + if( temperatur>=0 ) + temperatur=(temperatur-deltaTemperatur>0)?(temperatur-deltaTemperatur):0; +} + +void TAOptimization::makeGraphOutput() +{ + IterOptimization::makeGraphOutput(); + *GraphOutput << temperatur; +} + + + + +double TAOptimization::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 << "#TA-optimizeValues: " << numParameter << endl; + for(int i=0;i<=numParameter;i++) + { + StatVar end,laufzeit,init; + double now; + defaultAnnRate = (float)(i)/numParameter; + solveProblem(0,p,proParameter,optimierungsschritte,TA_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 << "#Mittelwert 0.2-Quantil 0.8-Quantil Laufzeit Bester" + " Sigma SigmaSmaller SigmaBigger\n"; + defaultAnnRate=0.5; + return bestPar; + } + break; + case 10: + { + double bestPar=-1,best=1e100; + if( print ) + cout << "#TA-optimizeValues: defaultMultiple " << 10 << endl; + for(int i=1;i<=6;i++) + { + StatVar end,laufzeit,init; + double now; + defaultMultiple = i; + solveProblem(0,p,proParameter,optimierungsschritte,TA_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 << "#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 TAOptimization::optimizeValue (" + << typ << ")\n"; + exit(1); + } + return 1e100; +} + + |