EmpiricMeasureLevelMaps.cpp

#include "EmpiricMeasureLevelMaps.hpp"
#include "Exponents.hpp"


void MonteCarloMap::UpdateSampleCounter(double epsilon) {
    int optimalM;

    double factor = 0.0;
    for (auto &[level, mc] : _levelMap)
        factor += sqrt(mc.vars.Y * mc.avgs.Cost);

    for (auto &[level, mc] : _levelMap) {
        optimalM = (int) (ceil(2 * pow(epsilon, -2) * factor *
            sqrt(mc.vars.Y / mc.avgs.Cost)));
        if (optimalM == 1) optimalM++;  // Hack
        mc.ctr.UpdateSampleCounter(optimalM - mc.ctr.M);
    }
}

void MonteCarloMap::AppendLevel(double epsilon, Exponents exponents, Level newLevel) {
    if (newLevel <= maxLevel) {
        auto oldLevel = this->rbegin();
        double varsY = oldLevel->second.vars.Y / pow(2.0, exponents.beta);
        double avgsCost = oldLevel->second.avgs.Cost * pow(2.0, exponents.gamma);
        _levelMap.insert(LevelMonteCarloPair(newLevel, MonteCarlo(newLevel, 0, false)));
        _levelMap.find(newLevel)->second.vars.Y = varsY;
        _levelMap.find(newLevel)->second.avgs.Cost = avgsCost;
        this->UpdateSampleCounter(epsilon);
    } else {
        Exit ("Maximum level has been reached.")
    }
}

void SampleCounterMap::Update(const MonteCarloMap &mcMap) {
    for (auto &[level, mc]: mcMap)
        _levelMap[level] = mc.ctr;
}

bool SampleCounterMap::NoSamplesLeft() {
    bool noSamplesLeft = true;
    for (auto &&[level, entry]: _levelMap)
        if (entry.dM > 0) {
            noSamplesLeft = false;
            break;
        }
    return noSamplesLeft;
}

void AveragesMap::Update(const MonteCarloMap &mcMap) {
    for (auto &&[level, mc]: mcMap) {
        _levelMap[level] = mc.avgs;
        Q += mc.avgs.Y;
        Cost += mc.avgs.Cost; // Todo at the right place?
    }
}

void VariancesMap::Update(const MonteCarloMap &mcMap) {
    for (auto &[level, mc]: mcMap)
        _levelMap[level] = mc.vars;
}

void KurtosisMap::Update(const MonteCarloMap &mcMap) {
    for (auto &[level, mc]: mcMap)
        _levelMap[level] = mc.kurtosis;
}