int main(){
std::vector<double> initparams;
initparams.push_back(5.0);
FFF::FitSimple fit(&myNLL,&myMC);
FFF::DataWrapper* data = fit.GenerateData(initparams);
std::cout << "The correct answer is 5.0, with a likelihood of 0.0" << std::endl;
std::vector<double> results = fit.MigradFit(initparams,data);
std::cout << "Migrad: " << results[0] << " L=" << results[1] << std::endl;
TNtuple *lspace = fit.MCMCMapLikelihood(initparams,data);
TFile f("lspace.root","RECREATE");
lspace->Write();
f.Close();
results = fit.MCMCFit(initparams,data);
std::cout << "MCMC: " << results[0] << " L=" << results[1] << std::endl;
results = fit.SAnnealFit(initparams,data);
std::cout << "SAnneal: " << results[0] << " L=" << results[1] << std::endl;
// You can also do normal minuit2 stuff
ROOT::Minuit2::FCNBase* migradfunc = fit.GetMinuit2FCNBase(data);
std::vector<double> verrors;
for (size_t i=0;i<initparams.size();i++)
verrors.push_back(0.0); //FIXME
ROOT::Minuit2::MnUserParameters mnParams(initparams,verrors);
ROOT::Minuit2::MnMigrad migrad(*migradfunc,mnParams);
ROOT::Minuit2::FunctionMinimum theMin = migrad(); //FIXME maxfcn, tol
ROOT::Minuit2::MnUserParameters migradresult = theMin.UserParameters();
ROOT::Minuit2::MnMinos minos(*migradfunc,theMin);
std::pair<double, double> errors = minos(0);
std::cout << "Minos errors:" << std::endl;
std::cout << migradresult.Params()[0] << " +" << errors.second << " -" << -1*errors.first << std::endl;
return 0;
}
int main() {
std::vector<double> positions;
std::vector<double> measurements;
std::vector<double> var;
double nmeas = 0;
#ifdef USE_SEALBASE
seal::Filename inputFile (seal::Filename ("$SEAL/src/MathLibs/Minuit/tests/MnSim/paul2.txt").substitute (seal::ShellEnvironment ()));
std::ifstream in(inputFile.name() );
#else
std::ifstream in("paul2.txt");
#endif
if (!in) {
std::cerr << "Error opening input data file" << std::endl;
return 1;
}
// read input data
{
double x = 0., y = 0., width = 0., err = 0., un1 = 0., un2 = 0.;
while(in>>x>>y>>width>>err>>un1>>un2) {
if(err < 1.e-8) continue;
positions.push_back(x);
measurements.push_back(y);
var.push_back(err*err);
nmeas += y;
}
std::cout<<"size= "<<var.size()<<std::endl;
assert(var.size() > 0);
std::cout<<"nmeas: "<<nmeas<<std::endl;
}
// create FCN function
GaussFcn theFCN(measurements, positions, var);
std::vector<double> meas = theFCN.measurements();
std::vector<double> pos = theFCN.positions();
// create initial starting values for parameters
double x = 0.;
double x2 = 0.;
double norm = 0.;
double area = 0.;
double dx = pos[1]-pos[0];
for(unsigned int i = 0; i < meas.size(); i++) {
norm += meas[i];
x += (meas[i]*pos[i]);
x2 += (meas[i]*pos[i]*pos[i]);
area += dx*meas[i];
}
double mean = x/norm;
double rms2 = x2/norm - mean*mean;
std::cout<<"initial mean: "<<mean<<std::endl;
std::cout<<"initial sigma: "<<sqrt(rms2)<<std::endl;
std::cout<<"initial area: "<<area<<std::endl;
std::vector<double> init_val(3);
init_val[0] = mean;
init_val[1] = sqrt(rms2);
init_val[2] = area;
std::cout<<"initial fval: "<<theFCN(init_val)<<std::endl;
MnUserParameters upar;
upar.add("mean", mean, 1.);
upar.add("sigma", sqrt(rms2), 1.);
upar.add("area", area, 10.);
MnMigrad migrad(theFCN, upar);
std::cout<<"start migrad "<<std::endl;
FunctionMinimum min = migrad();
std::cout<<"minimum: "<<min<<std::endl;
std::cout<<"start minos"<<std::endl;
MnMinos minos(theFCN, min);
std::pair<double,double> e0 = minos(0);
std::pair<double,double> e1 = minos(1);
std::pair<double,double> e2 = minos(2);
std::cout<<"par0: "<<min.userState().value("mean")<<" "<<e0.first<<" "<<e0.second<<std::endl;
std::cout<<"par1: "<<min.userState().value(1)<<" "<<e1.first<<" "<<e1.second<<std::endl;
std::cout<<"par2: "<<min.userState().value(2)<<" "<<e2.first<<" "<<e2.second<<std::endl;
return 0;
}
