inline typename McSimulation<MC,RNG,S>::result_type
McSimulation<MC,RNG,S>::value(Real tolerance,
Size maxSamples,
Size minSamples) const {
Size sampleNumber =
mcModel_->sampleAccumulator().samples();
if (sampleNumber<minSamples) {
mcModel_->addSamples(minSamples-sampleNumber);
sampleNumber = mcModel_->sampleAccumulator().samples();
}
Size nextBatch;
Real order;
result_type error(mcModel_->sampleAccumulator().errorEstimate());
while (maxError(error) > tolerance) {
QL_REQUIRE(sampleNumber<maxSamples,
"max number of samples (" << maxSamples
<< ") reached, while error (" << error
<< ") is still above tolerance (" << tolerance << ")");
// conservative estimate of how many samples are needed
order = maxError(error*error)/tolerance/tolerance;
nextBatch =
Size(std::max<Real>(static_cast<Real>(sampleNumber)*order*0.8 - static_cast<Real>(sampleNumber),
static_cast<Real>(minSamples)));
// do not exceed maxSamples
nextBatch = std::min(nextBatch, maxSamples-sampleNumber);
sampleNumber += nextBatch;
mcModel_->addSamples(nextBatch);
error = result_type(mcModel_->sampleAccumulator().errorEstimate());
}
return result_type(mcModel_->sampleAccumulator().mean());
}
// ##### getErrorComb() ##############################################
AxIndex ScanLine::getErrorComb(AxComb testAxComb) {
NodeIndex testError= getErrorCombVec(testAxComb);
return maxError(testError);
}
// ##### getError() ##################################################
AxIndex ScanLine::getError(Axis testAx) {
NodeIndex testError= getErrorVec(testAx);
return maxError(testError);
}
