// Return 0 if everything is OK, non-zero if error. If we did not set anything
// then we return non-zero (this is not an error, but we indicate that we did
// not do anything).
// The set method must set both the GA's parameter and the value in the
// parameter list (kind of stupid to maintain two copies of the same data, but
// oh well). The call to set on params is redundant for the times when this
// method is called *after* the parameter list has been updated, but it is
// necessary when this method is called directly by the user.
int
GAGeneticAlgorithm::setptr(const char* name, const void* value){
int status=1;
params.set(name, value); // redundant for some cases, but not others
if(strcmp(name, gaNnBestGenomes) == 0 ||
strcmp(name, gaSNnBestGenomes) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((int*)value) << "'\n";
#endif
nBestGenomes(*((int*)value));
status = 0;
}
else if(strcmp(name, gaNpopulationSize) == 0 ||
strcmp(name, gaSNpopulationSize) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((int*)value) << "'\n";
#endif
populationSize(*((int*)value));
status = 0;
}
else if(strcmp(name, gaNminimaxi) == 0 ||
strcmp(name, gaSNminimaxi) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((int*)value) << "'\n";
#endif
minimaxi(*((int*)value));
status = 0;
}
else if(strcmp(name, gaNnGenerations) == 0 ||
strcmp(name, gaSNnGenerations) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((int*)value) << "'\n";
#endif
nGenerations(*((int*)value));
status = 0;
}
else if(strcmp(name, gaNpConvergence) == 0 ||
strcmp(name, gaSNpConvergence) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((float*)value) << "'\n";
#endif
pConvergence(*((float*)value));
status = 0;
}
else if(strcmp(name, gaNnConvergence) == 0 ||
strcmp(name, gaSNnConvergence) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((int*)value) << "'\n";
#endif
nConvergence(*((int*)value));
status = 0;
}
else if(strcmp(name, gaNpCrossover) == 0 ||
strcmp(name, gaSNpCrossover) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((float*)value) << "'\n";
#endif
pCrossover(*((float*)value));
status = 0;
}
else if(strcmp(name, gaNpMutation) == 0 ||
strcmp(name, gaSNpMutation) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((float*)value) << "'\n";
#endif
pMutation(*((float*)value));
status = 0;
}
else if(strcmp(name,gaNscoreFrequency) == 0 ||
strcmp(name,gaSNscoreFrequency) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((int*)value) << "'\n";
#endif
stats.scoreFrequency(*((int*)value));
status = 0;
}
else if(strcmp(name,gaNflushFrequency) == 0 ||
strcmp(name,gaSNflushFrequency) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((int*)value) << "'\n";
#endif
stats.flushFrequency(*((int*)value));
status = 0;
}
else if(strcmp(name,gaNrecordDiversity) == 0 ||
strcmp(name,gaSNrecordDiversity) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((int*)value) << "'\n";
#endif
stats.recordDiversity(*((int*)value) ? gaTrue : gaFalse);
status = 0;
}
else if(strcmp(name,gaNselectScores) == 0 ||
strcmp(name,gaSNselectScores)==0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << *((int*)value) << "'\n";
#endif
stats.selectScores(*((int*)value));
status = 0;
}
else if(strcmp(name,gaNscoreFilename) == 0 ||
strcmp(name,gaSNscoreFilename) == 0){
#ifdef GA_DEBUG
cerr << "GAGeneticAlgorithm::setptr\n setting '" << name << "' to '" << ((char*)value) << "'\n";
#endif
char tmpname[64];
memcpy(tmpname, value, strlen((char*)value)+1);
stats.scoreFilename(tmpname);
status = 0;
}
return status;
}
int main (int argc, char **argv) {
try { //Parser exceptions
printf("Constructing parser...\n");
TCLAP::CmdLine cmd("Simulator - simulates test system database files",' ',"0");
TCLAP::ValueArg<std::string> filename("f","filename","Database file name",false,"sys.db","string");
TCLAP::ValueArg<double> fieldStrength("","fieldStrength","Target simulation field strength",false,0.1,"double");
TCLAP::ValueArg<int> numGens("","numGens","Number of iterations to simulate",false,300,"int");
TCLAP::ValueArg<double> alpha("","alpha","Weight of squared error to spacing relaxation",false,0.99,"double");
TCLAP::ValueArg<int> populationSize("","populationSize","Size of test population (genetic algorithm only)",false,100,"int");
TCLAP::ValueArg<int> maxStepTime("","maxStepTime","Maximum time (MS) to search for a better next-state (simulated annealing only)",false,1000,"int");
TCLAP::ValueArg<double> mutationRate("","mutationRate","Sigma of normal mutation (genetic algorithm only)",false,0.1,"double");
TCLAP::ValueArg<double> startingTemperature("","startTemp","Starting normal temperature (simulated annealing only)",false,1,"double");
TCLAP::ValueArg<double> endingTemperature("","endTemp","Ending normal temperature (simulated annealing only)",false,0,"double");
cmd.add(filename);
cmd.add(fieldStrength);
cmd.add(numGens);
cmd.add(alpha);
cmd.add(populationSize);
cmd.add(maxStepTime);
cmd.add(mutationRate);
cmd.add(startingTemperature);
cmd.add(endingTemperature);
//Add XOR switches
TCLAP::SwitchArg annealSwitch("","anneal","Use simulated annealing algorithm",false);
TCLAP::SwitchArg geneticSwitch("","genetic","Use genetic optimization algorithm",false);
std::vector<TCLAP::Arg*> xorlist;
xorlist.push_back(&annealSwitch);
xorlist.push_back(&geneticSwitch);
cmd.xorAdd(xorlist);
//Parse arguments
printf("Parsing options...\n");
cmd.parse(argc,argv);
//Retrieve options
std::string filename_v = filename.getValue();
double fieldStrength_v = fieldStrength.getValue();
int numGens_v = numGens.getValue();
double alpha_v = alpha.getValue();
int populationSize_v = populationSize.getValue();
int maxStepTime_v = maxStepTime.getValue();
double mutationRate_v = mutationRate.getValue();
double startingTemperature_v = startingTemperature.getValue();
double endingTemperature_v = endingTemperature.getValue();
//Load lamina and source from the database
Database db(filename_v);
if (!db.getTotalParticlesInDB() || db.getMaxGenerationNumber()) {
printf("Database is empty or already simulated.\n");
return 0;
}
Lamina lamina = db.getLaminaParticlesForGeneration(0);
Source source = db.getSourceParticles();
//Create the appropriate simulator
Simulation* s = nullptr;
if (annealSwitch.getValue()) {
s = new AnnealingSimulation(lamina,source,fieldStrength_v,numGens_v,alpha_v,maxStepTime_v,startingTemperature_v,
endingTemperature_v);
} else if (geneticSwitch.getValue()) {
s = new GeneticAlgorithm(lamina,source,fieldStrength_v,numGens_v,alpha_v,populationSize_v,mutationRate_v);
} else {
printf("Should have selected an operation mode...\n");
return 0;
}
//Step the simulator and save out the generations
while (s->step()) {
int generationNumber = s->getGeneration();
double currentEnergy = s->finalEnergy();
printf("Simulating generation %d, energy = %f\n",generationNumber,currentEnergy);
db.insertLaminaParticles(s->getLamina(),generationNumber);
}
//Print some final statistics
printf("\nStarting Energy: %f\n",s->startingEnergy());
printf("Final Energy: %f\n",s->finalEnergy());
//Save out the fitness log
db.insertFitnessLog(s->getFitnessLog());
//End
printf("Process completed.\n");
delete s;
} catch (TCLAP::ArgException &e) {
std::cerr << "error: " << e.error() << " for arg " << e.argId() << std::endl;
return 1;
}
return 0;
}
