Simulation::Simulation(InfoFile &info, ProgramOptions &theProgOpt, ThreadPool &_tp)
: progOpt(theProgOpt)
, numGen(progOpt.getNumberOfGenerations())
, tp(_tp)
{
// create chromosomes
Randomness &rng = tp[0].getRNG();
vector<seqLen_t> lengths = progOpt.get<vector<seqLen_t> >("length");
nat idC = 0;
nat numPop = 1; // TODO pops
for(auto& length : lengths)
{
FitnessFunction fFun(progOpt.get<vector<string>>("selCoef"));
Chromosome* chromo = new Chromosome(length, theProgOpt.hasOption("neutral"), fFun, idC++, numPop);
chromo->init(rng);
chromosomes.push_back(chromo);
}
// create parameters of populations
vector<nat> popSizes = progOpt.get<vector<nat> >("popSize");
assert(popSizes.size() == 1 );
popParams.push_back( PopulationParams(0, numGen, popSizes[0], progOpt));
fractionalSimulation = new FractionalSimulation(tp,info, progOpt, numGen, chromosomes, popParams);
}
Chromosome make_chromo(const Mat& m, const int size) {
Chromosome c;
c.init(size);
for(size_t x = 0; x < m.rows; ++x) {
for(size_t y = 0; y < m.cols; ++y) {
c[c.getKernelOffset() + (x * m.cols) + y] = m.at<double>(x, y);
}
}
//FIXME properly calculate the weight
c[1] = -1.0;
c[0] = 0.1;
while(c.getKernelSize() < m.rows) {
c[1] += 0.01;
}
CHECK(c.getKernelSize() == m.rows);
return c;
}
