void SphereState::decrementBetaInTime(double deltaTime) {
beta -= 0.5 * deltaTime;
adjustBeta();
}
void match_prevalence(int treatmentNumber, int simNumber, double treatment, double startingBeta)
{
std::cout << "Treatment #" << treatmentNumber << " and simulation #" << simNumber << ":" << std::endl;
std::array<double, INIT_NUM_STYPES> betas;
betas.fill(startingBeta);
std::array<double, INIT_NUM_STYPES> serotype_ranks;
for(int i = 0; i < INIT_NUM_STYPES; i++)
{
serotype_ranks[i] = i + 1;
}
double best_likelihood = std::numeric_limits<double>::lowest();
std::array<double, INIT_NUM_STYPES> best_betas = betas;
std::array<double, INIT_NUM_STYPES> best_serotype_ranks = serotype_ranks;
double prevError = 10.0;
double oldPrevError = 1.0;
double weight = INIT_WEIGHT;
std::array<int, INIT_NUM_STYPES + 1> observed_prevalence = {283, 237, 184, 117, 90, 85, 84, 70, 56, 54, 53, 51, 49, 49, 43, 38, 34, 34, 29, 25, 23, 21, 19, 18, 15, 0, 10079};
for(int attempt = 0; attempt < 10; attempt++)
{
SimPars thesePars(treatmentNumber, simNumber);
thesePars.set_serotype_ranks(serotype_ranks);
thesePars.set_betas(betas);
Simulation thisSim(treatmentNumber, simNumber, &thesePars);
thisSim.runDemSim();
auto serotype_counts = thisSim.runTestEpidSim();
std::array<double, INIT_NUM_STYPES + 1> expected_prevalence = {0};
std::array<double, INIT_NUM_STYPES> prevalence_error = {0};
double expected_population = std::accumulate(serotype_counts.begin(), serotype_counts.end(), 0.0);
double infected_prevalence = 0;
int observed_population = std::accumulate(observed_prevalence.begin(), observed_prevalence.begin() + INIT_NUM_STYPES + 1, 0);
double target_prevalence = std::accumulate(observed_prevalence.begin(), observed_prevalence.begin() + INIT_NUM_STYPES, 0.0) / observed_population;
for(int i = 0; i < INIT_NUM_STYPES; i++)
{
infected_prevalence += serotype_counts[i] / (double)expected_population;
prevalence_error[i] = expected_prevalence[i] - observed_prevalence[i] / (double)observed_population;
if(i == HFLU_INDEX)
{
prevalence_error[i] = 0;
}
expected_prevalence[i] = (serotype_counts[i] + 0.01) / (expected_population + INIT_NUM_STYPES * 0.01);
}
expected_prevalence.back() = 1 - infected_prevalence;
double likelihood = calculate_likelihood(expected_prevalence, observed_prevalence);
if(likelihood > best_likelihood)
{
best_likelihood = likelihood;
best_betas = betas;
best_serotype_ranks = serotype_ranks;
}
else
{
betas = best_betas;
serotype_ranks = best_serotype_ranks;
}
std::cout << "Likelihood=" << likelihood << "(best=" << best_likelihood << ")" << std::endl;
if(attempt % 2 == 0)
{
std::cout << "Fitting overall prevalence" << std::endl;
prevError = infected_prevalence - target_prevalence;
std::cout << "Observed prevalence=" << target_prevalence << "; expected prevalence=" << infected_prevalence << "; error=" << prevError << "; weight = " << weight << std::endl;
if(abs(prevError) > PREV_ERROR_THOLD)
{
// if error changed signs and overshot, reduce weight
if(prevError * oldPrevError < 0)
{
weight *= COOL_DOWN;
}
// if climbing too slowly, increase weight
else if(abs(target_prevalence - prevError) / abs(target_prevalence - oldPrevError) > TEMP_THOLD)
{
weight *= WARM_UP;
}
adjustBeta(prevError, weight, betas);
oldPrevError = prevError;
}
}
else
{
std::cout << "Fitting per-serotype prevalence" << std::endl;
adjust_ranks(prevalence_error, serotype_ranks);
}
}
}
