// rareEvents() function callable from R via Rcpp -- which is essentially
// the same as main() from SMCTC's examples/rare-events/main.cc
extern "C" SEXP rareEvents(SEXP numberS, SEXP iteratesS, SEXP thresholdS, SEXP scheduleS) {
long lNumber = Rcpp::as<long>(numberS); // Number of particles
lIterates = Rcpp::as<long>(iteratesS); // Number of iterations
dThreshold = Rcpp::as<double>(thresholdS); // Rare event threshold
dSchedule = Rcpp::as<double>(scheduleS); // Annealing schedule constant
try{
///An array of move function pointers
void (*pfMoves[])(long, smc::particle<mChain<double> > &,smc::rng*) = {fMove1, fMove2};
smc::moveset<mChain<double> > Moveset(fInitialiseMC, fSelect, sizeof(pfMoves) / sizeof(pfMoves[0]), pfMoves, fMCMC);
smc::sampler<mChain<double> > Sampler(lNumber, SMC_HISTORY_RAM);
Sampler.SetResampleParams(SMC_RESAMPLE_STRATIFIED,0.5);
Sampler.SetMoveSet(Moveset);
Sampler.Initialise();
Sampler.IterateUntil(lIterates);
///Estimate the normalising constant of the terminal distribution
double zEstimate = Sampler.IntegratePathSampling(pIntegrandPS, pWidthPS, NULL) - log(2.0);
///Estimate the weighting factor for the terminal distribution
double wEstimate = Sampler.Integrate(pIntegrandFS, NULL);
// cout << zEstimate << " " << log(wEstimate) << " " << zEstimate + log(wEstimate) << endl;
Rcpp::NumericVector res = Rcpp::NumericVector::create(Rcpp::Named("zEstimate") = zEstimate,
Rcpp::Named("log(wEstimate)") = log(wEstimate),
Rcpp::Named("sum") = zEstimate + log(wEstimate));
return res;
}
catch(smc::exception e) {
Rcpp::Rcout << e; // not cerr, as R doesn't like to mix with i/o
//exit(e.lCode); // we're just called from R so we should not exit
}
return R_NilValue; // to provide a return
}
// [ref] ${SMCTC_HOME}/examples/rare-events/main.cc
void rare_events_example()
{
// Number of Particles
const long lNumber = 1000;
// An array of move function pointers
void (*pfMoves[])(long, smc::particle<mChain<double> > &, smc::rng *) = { simfunctions::fMove1, simfunctions::fMove2 };
smc::moveset<mChain<double> > Moveset(simfunctions::fInitialise, simfunctions::fSelect, sizeof(pfMoves) / sizeof(pfMoves[0]), pfMoves, simfunctions::fMCMC);
smc::sampler<mChain<double> > Sampler(lNumber, SMC_HISTORY_RAM);
Sampler.SetResampleParams(SMC_RESAMPLE_STRATIFIED, 0.5);
Sampler.SetMoveSet(Moveset);
Sampler.Initialise();
Sampler.IterateUntil(simfunctions::lIterates);
// Estimate the normalising constant of the terminal distribution
const double zEstimate = Sampler.IntegratePathSampling(simfunctions::pIntegrandPS, simfunctions::pWidthPS, NULL) - std::log(2.0);
// Estimate the weighting factor for the terminal distribution
const double wEstimate = Sampler.Integrate(simfunctions::pIntegrandFS, NULL);
std::cout << zEstimate << " " << std::log(wEstimate) << " " << zEstimate + std::log(wEstimate) << endl;
}
