vector<double> GradientDescent::maximize(const vector<double> &start_point)
{
return extremum(start_point, EType::Maximun);
}
vector<double> GradientDescent::minimize(const vector<double> &start_point, const vector<vector<double>> &c,
const vector<double> &d)
{
return extremum(start_point, c, d, EType::Minimum);
}
std::vector<NSEProperties> EOSNSE::GetExteriorProtonDensity(double ne,
double nno, double T) {
OneDimensionalRoot rootFinder1D(1.e-8, 100);
double np_min = 1.e-300;
double np_max = 1.2*ne;
// Find a good interval
auto nse_func = [nno, ne, T, this](double xx)->double{
double npo = exp(xx);
EOSData eosOut = mpEos->FromNAndT(EOSData::InputFromTNnNp(T, nno, npo));
auto nucleiProps = GetNucleiScalars(eosOut, ne);
double yy = 1.0 - (nucleiProps.np + (1.0 - nucleiProps.uNuc)*npo)/ne;
return yy;
};
// Try finding the maximum of nse_func
//double npmax = exp(minimize(nse_func, log(0.8*ne), log(1.e-300), log(ne)));
//double npmax2 = exp(minimize(nse_func, log(0.8*ne), log(0.7*ne), log(ne)));
//
//if (nse_func(log(npmax))*nse_func(log(np_low)) < 0.0) np_high = npmax;
//else if (nse_func(log(npmax))*nse_func(log(np_high)) < 0.0) np_low = npmax;
double two, one, zero;
double ntwo, none, nzero;
double nstart = 1.e-5;
ntwo = nstart; none = nstart; nzero = nstart;
two = nse_func(log(nstart));
one = nse_func(log(nstart));
zero = nse_func(log(nstart));
std::vector<double> extremum(1, 1.e-300);
// The 1.1 seems to be critical, increasing it's value makes things not work
for (double npt = nstart; npt<=np_max; npt*=1.05) {
ntwo = none;
two = one;
none = nzero;
one = zero;
nzero = std::min(npt, ne);
zero = nse_func(log(nzero));
double npmax2 = -1.0;
if (one>=two && one>=zero) {
OneDimensionalMinimization minimize(1.e-7, 25);
npmax2 = exp(minimize(nse_func, log(none), log(ntwo), log(nzero), true));
extremum.push_back(npmax2);
//std::cerr << " Should be local maximum " << ntwo << " " << npmax2 << " "
// << nzero;
}
if (one<=two && one<=zero) {
OneDimensionalMinimization minimize(1.e-7, 25);
npmax2 = exp(minimize(nse_func, log(none), log(ntwo), log(nzero)));
extremum.push_back(npmax2);
//std::cerr << " Should be local minimum " << ntwo << " " << npmax2 << " "
// << nzero;
}
if (npt >= ne) {
OneDimensionalMinimization minimize(1.e-7, 25);
npmax2 = exp(minimize(nse_func, log(none), log(ntwo), log(nzero), true));
if (npmax2>ntwo*(1.0+1.e-6) && npmax2<nzero*(1.0-1.e-6)) {
extremum.push_back(npmax2);
} else {
npmax2 = -1.0;
}
}
}
//extremum.push_back(ne);
extremum.push_back(np_max);
std::sort(extremum.begin(), extremum.end(),
[](double a, double b) {
return b>a;
});
std::vector<double> npsol;
std::vector<NSEProperties> output;
for (int i=0; i<extremum.size()-1; i++) {
double np_low = extremum[i];
double np_high = extremum[i+1];
if (nse_func(log(np_high))*nse_func(log(np_low))>0.0) continue;
try {
double npo = exp(rootFinder1D(nse_func, log(np_low), log(np_high)));
// Make sure we don't have two solutions that are the same
//for (auto npt : npsol) {
// if (fabs(npo/npt - 1.0)<1.e-2) continue;
//}
npsol.push_back(npo);
EOSData eosOut = mpEos->FromNAndT(EOSData::InputFromTNnNp(T, nno, npo));
auto nucleiProps = GetNucleiScalars(eosOut, ne);
output.push_back(NSEProperties(
nucleiProps.nn + eosOut.Nn()*(1.0 - nucleiProps.uNuc),
nucleiProps.np + eosOut.Np()*(1.0 - nucleiProps.uNuc),
T, eosOut, nucleiProps.uNuc));
} catch (...) { std::cout << "Did not find root " << np_low << " "
<< np_high << std::endl;}
}
return output;
}
