const double* AmFitter::findmin() {
double wdeg = _wdeg;
// A is LNB gain -- "gain"
// B is "slope"
// C is "offset"
// OLD STUFF FOR ROOT-BASED MINIMIZER
double A_start = 66.0;
double A_step = 0.01;
double B_start = 0.025; //0.025;
double B_step = 0.0001;
double C_start = -63.0;
double C_step = 0.01;
double n_start = 0.0E-10;
double n_step = 1.0E-12;
double t_shift_start = 0.0;
double t_shift_step = 1.0;
double X_start = -126.9;
double X_step = A_step;
// FOR THE PARAMETER SCAN METHOD
// i = 'initial', f = 'final', s = 'stepsize'
/*double Bi = 0.01;
double Bf = 0.045;
double Bs = 0.001;
double Xi = -160.0;
double Xf = -110.0;
double Xs = 0.1;
double ni = 5.0e-10;
double nf = 15.0e-10;
double ns = 1.0e-11;
double ti = 0.0;
double tf = 0.0;
double ts = 1.0;
double Xpars[3];
Xpars[0] = Xi;
Xpars[1] = Xf;
Xpars[2] = Xs;
double npars[3];
npars[0] = ni;
npars[1] = nf;
npars[2] = ns;
double tpars[3];
tpars[0] = ti;
tpars[1] = tf;
tpars[2] = ts;
double* minpars[10];
for(int i=0;i<10;i++) {
minpars[i] = new double[5];
}*/
double val = -1;
double minval = -1;
// PARAMETER SCAN
// burn in a non-NaN value
/*for(double B = Bi; B <= Bf; B = B + Bs) {
for(double X = Xi; X <= Xf; X = X + Xs) {
for(double n = ni; n <= nf; n = n + ns) {
for(double t = ti; t <= tf; t = t + ts) {
val = chi_sq_sum(B,X,n,t);
if(val == val) {
minval = val;
n = nf;
X = Xf;
B = Bf;
break;
}
}
}
}
}*/
double* ret = new double[4];
/*for(double B = 0.01; B <= 0.05; B = B + 0.01) {
for(double X = -160.0; X <= -110.0; X = X + 1.0) {
for(double n = 5.0e-10; n <= 15.0e-10; n = n + 1.0e-10) {
for(double t = -10; t <= 10; t = t + 1.0) {
val = chi_sq_sum(B,X,n,t);
//cout << " " << B << " " << X << " " << n << " " << t << " " << val << endl;
if(val<=minval) {
minval = val;
ret[0] = B;
ret[1] = X;
ret[2] = n;
ret[3] = t;
}
}
}
}
}*/
// PARAMETER SCAN
/*boost::thread* scanthread[10];
for(int i=0; i<10; i++) {
//scanfunc(0,minval,minpars[0],Xpars,npars,tpars);
scanthread[i] = new boost::thread(&AmFitter::scanfunc, this, i, minval, minpars[i], Xpars, npars, tpars);
}
for(int i=0; i<10; i++) {
scanthread[i]->join();
}
minval = minpars[0][0];
for(int i=0; i<10; i++ ) {
if(minpars[i][0] <= minval) {
minval = minpars[i][0];
ret[0] = minpars[i][1];
ret[1] = minpars[i][2];
ret[2] = minpars[i][3];
ret[3] = minpars[i][4];
}
}
for(int i=0; i<10; i++ ) {
delete scanthread[i];
}*/
// UNCOMMENT FOR MORE SUBTLE ROOT MINIMIZATION
// not exactly as per tutorial -- didn't do 'algoName'
double noise = 0.0;
minval = chi_sq_sum(B_start,X_start,noise,t_shift_start);
while(true) {
/*if( !(val == val) && (_file_id != -1)) {
noise -= 0.01e-10;
noise -= 0.01e-10;
}*/
ROOT::Math::Minimizer* min = ROOT::Math::Factory::CreateMinimizer("Minuit2","Migrad");
// just as in tutorial
//min->SetMaxFunctionCalls(5000);
//min->SetMaxFunctionCalls(1);
min->SetMaxIterations(10000000);
min->SetTolerance(0.0001);
min->SetPrintLevel(0);
// wrap up the function
ROOT::Math::Functor f(this,&AmFitter::minfunc,4); // tricky, tricky
min->SetFunction(f);
//min->SetFixedVariable(0,"B",0.02462491128); //0.02462491128
//min->SetFixedVariable(1,"X",-128.3733503); //-128.3733503
//min->SetVariable(0,"B",B_start,B_step);
//min->SetLimitedVariable(0,"B",B_start,B_step,0.022,0.032); // used to find reasonable fits for everything but C4
min->SetLimitedVariable(0,"B",B_start,B_step,0.022,0.045);
min->SetVariable(1,"X",X_start,X_step);
//min->SetLimitedVariable(2,"n",n_start,n_step,0.0,15.0E-10);
min->SetFixedVariable(2,"n",noise); // 7.611546967e-10
//min->SetVariable(2,"n",noise,1.0e-12); // 7.611546967e-10
min->SetLimitedVariable(3,"t_shift",t_shift_start,t_shift_step,-400.0,400.0);
//min->SetFixedVariable(3,"t_shift",0.0);
min->Minimize();
val = chi_sq_sum(min->X()[0],min->X()[1],min->X()[2],min->X()[3]);
if( !(val == val) /*&& (_file_id != -1)*/ ) {
delete min;
break;
}
if(val <= minval) {
minval = val;
ret[0] = min->X()[0];
ret[1] = min->X()[1];
ret[2] = min->X()[2];
ret[3] = min->X()[3];
}
if( _file_id == -1 ) {
//cout << "curr_val: " << val << " " << noise << endl;
}
noise += 0.01e-10;
delete min;
}
// now let's check to see if this fit was pathological
/*double B = ret[0]; //min->X()[0];
double X = ret[1]; //min->X()[1];
double n = ret[2]; //min->X()[2];
double t_shift = ret[3]; //min->X()[3];
double y1[216];
double y2[216];
double x[216];
// sum that we'll test against for the blacklist
double testsum = 0;
for(int i=0;i<215;i++) {
y1[i-0] = 10*log10((5.0E8)*(1.38065E-23)*(temps_func(time_arr[0][i]))/.001);
//y2[i] = 10*log((A*exp(amfitter.hsk_func(amfitter.time_arr[0][i])*B+C) - n)/1);
y2[i-0] = 10*log10( (pow(10,0.1*(hsk_func(time_arr[0][i]+t_shift)*B+X)) - n)/1);
x[i-0] = time_arr[0][i];
testsum += fabs( y1[i-0] - y2[i-0] );
if( (i>100) && (i<120) ) {
//cout << x[i-0] << " " << y1[i-0] << " " << y2[i-0] << endl;
}
}*/
//cout << endl;
if( false ) { //8.0
_blacklist[_file_id] = 1;
}
else if(_blacklist[_file_id] == 1) {
_blacklist[_file_id] = 1;
}
else {
_blacklist[_file_id] = 0;
}
cout << "Minimizer run completed " << ret[0]<< " " << ret[1] << " " << ret[2]<< " " << ret[3]<< " " << endl;
return ret;
//return min->X();
}
int main(int argc, char** argv)
{
// ROOT::Math::Minimizer* minuit = ROOT::Math::Factory::CreateMinimizer("Genetic"); //---> next ROOT release!
ROOT::Math::Minimizer* minuit = ROOT::Math::Factory::CreateMinimizer("Minuit", "Migrad2");
ROOT::Math::Functor functorChi2(&Chi2Func,6);
TString genCut; //==== (eleFBrem<0.8&&eleCharge>0)
bool traslationX ;
bool traslationY ;
bool traslationZ ;
bool rotationPhi ;
bool rotationTheta ;
bool rotationPsi ;
std::string fileName (argv[1]) ;
boost::shared_ptr<edm::ParameterSet> parameterSet = edm::readConfig(fileName) ;
edm::ParameterSet subPSetInput = parameterSet->getParameter<edm::ParameterSet> ("inputTree") ;
std::vector<std::string> nameFileIn = subPSetInput.getParameter<std::vector<std::string> > ("inputFiles") ;
std::string nameTree = subPSetInput.getParameter<std::string> ("nameTree") ;
std::string selection = subPSetInput.getParameter<std::string> ("selection") ;
genCut = Form("%s",selection.c_str());
traslationX = subPSetInput.getParameter<bool> ("traslationX") ;
traslationY = subPSetInput.getParameter<bool> ("traslationY") ;
traslationZ = subPSetInput.getParameter<bool> ("traslationZ") ;
rotationPhi = subPSetInput.getParameter<bool> ("rotationPhi") ;
rotationTheta = subPSetInput.getParameter<bool> ("rotationTheta") ;
rotationPsi = subPSetInput.getParameter<bool> ("rotationPsi") ;
double setRotationPhi = subPSetInput.getUntrackedParameter<double> ("setRotationPhi",0) ;
double setRotationTheta = subPSetInput.getUntrackedParameter<double> ("setRotationTheta",0) ;
double setRotationPsi = subPSetInput.getUntrackedParameter<double> ("setRotationPsi",0) ;
even = subPSetInput.getUntrackedParameter<bool> ("even",true) ;
odd = subPSetInput.getUntrackedParameter<bool> ("odd",true) ;
edm::ParameterSet subPSetOutput = parameterSet->getParameter<edm::ParameterSet> ("outputTree") ;
std::string nameFileOut = subPSetOutput.getParameter<std::string> ("outputFile") ;
//==== plot input/output ====
std::cout << " nameFileIn = ";
for (unsigned int i=0; i<nameFileIn.size(); i++ ) std::cout << " " << nameFileIn.at(i) << std::endl;
std::cout << " nameFileOut = " << nameFileOut << std::endl;
std::cout << " genCut = " << genCut.Data() << std::endl;
///==== input DATA ====
myTree = new TChain(nameTree.c_str());
int numberInput = 0;
for (std::vector<std::string>::const_iterator listIt = nameFileIn.begin () ; listIt != nameFileIn.end () ; ++listIt) {
numberInput++;
myTree->Add (listIt->c_str ()) ;
if (numberInput%4 == 0) std::cerr << "Input number " << numberInput << " ... " << listIt->c_str () << std::endl;
}
///==== bias functions ====
std::string FunctionDetaName = subPSetInput.getUntrackedParameter<std::string> ("DetaBias","0") ; // x = eta, y = charge
std::string FunctionDphiName = subPSetInput.getUntrackedParameter<std::string> ("DphiBias","0") ;
FunctionDeta = new TF2 ("DetaBias",FunctionDetaName.c_str(),-5,5,-2,2);
FunctionDphi = new TF2 ("DphiBias",FunctionDphiName.c_str(),-5,5,-2,2);
//==== output DATA ====
///==== Input ECAL position ====
std::string inputFilesPosition = subPSetInput.getUntrackedParameter<std::string> ("inputFilesPosition","") ;
///==== Build variables ====
double DX_SC_Mean[4];
double DX_SC_RMS[4];
double DY_SC_Mean[4];
double DY_SC_RMS[4];
double DZ_SC_Mean[4];
double DZ_SC_RMS[4];
double DTHETAe_SC_Mean[4];
double DTHETAe_SC_RMS[4];
double DPSIe_SC_Mean[4];
double DPSIe_SC_RMS[4];
double DPHIe_SC_Mean[4];
double DPHIe_SC_RMS[4];
std::ifstream* file;
if (inputFilesPosition != ""){
file = new std::ifstream(inputFilesPosition.c_str());
if(!file->is_open())
{
return false;
}
}
for (int iSC = 0; iSC<4; iSC++){
TString cut;
cut = Form("%s && iDetEB < -10 && iDetEE == %d",genCut.Data(),iSC);
std::cout << " cut = " << cut.Data() << std::endl;
///===========================
///==== Chi2 minimization ====
double inputDX = 0;
double inputDY = 0;
double inputDZ = 0;
double inputDPHIe = 0;
double inputDTHETAe = 0;
double inputDPSIe = 0;
if (inputFilesPosition != ""){
std::string buffer;
getline(*file,buffer);
std::stringstream line( buffer );
line >> inputDPHIe;
line >> inputDTHETAe;
line >> inputDPSIe;
line >> inputDX; inputDX/=100;
line >> inputDY; inputDY/=100;
line >> inputDZ; inputDZ/=100;
}
std::cerr << " inputDPHIe = " << inputDPHIe << std::endl;
std::cerr << " inputDTHETAe = " << inputDTHETAe << std::endl;
std::cerr << " inputDPSIe = " << inputDPSIe << std::endl;
std::cerr << " inputDX = " << inputDX << std::endl;
std::cerr << " inputDY = " << inputDY << std::endl;
std::cerr << " inputDZ = " << inputDZ << std::endl;
std::cout << " Chi2 minimization " << std::endl;
globalCut = cut;
// unsigned int iNoSteps = 1000;
// unsigned int iPar_NoBG = 0;
minuit->SetFunction(functorChi2);
minuit->SetMaxFunctionCalls(100000);
minuit->SetMaxIterations(10000);
minuit->SetTolerance(0.000002);
if (traslationX) minuit->SetLimitedVariable(0,"DX",inputDX, 0.00001,-0.050,0.050);
else minuit->SetFixedVariable(0,"DX",0);
if (traslationY) minuit->SetLimitedVariable(1,"DY",inputDY, 0.00001,-0.050,0.050);
else minuit->SetFixedVariable(1,"DY",0);
if (traslationZ) minuit->SetLimitedVariable(2,"DZ",inputDZ, 0.00001,-0.050,0.050);
else minuit->SetFixedVariable(2,"DZ",0);
if (rotationPhi) minuit->SetLimitedVariable(3,"DPHIe",inputDPHIe, 0.00001,-3.15,3.15);
else minuit->SetFixedVariable(3,"DPHIe",inputDPHIe);
if (rotationTheta) minuit->SetLimitedVariable(4,"DTHETAe",inputDTHETAe, 0.00001,-3.15,3.15);
else minuit->SetFixedVariable(4,"DTHETAe",inputDTHETAe);
if (rotationPsi) minuit->SetLimitedVariable(5,"DPSIe",inputDPSIe, 0.00001,-3.15,3.15);
else minuit->SetFixedVariable(5,"DPSIe",inputDPSIe);
minuit->Minimize();
minuit->PrintResults();
DX_SC_Mean[iSC] = (minuit->X()[0]);
DY_SC_Mean[iSC] = (minuit->X()[1]);
DZ_SC_Mean[iSC] = (minuit->X()[2]);
DX_SC_RMS[iSC] = (minuit->Errors()[0]);
DY_SC_RMS[iSC] = (minuit->Errors()[1]);
DZ_SC_RMS[iSC] = (minuit->Errors()[2]);
DPHIe_SC_Mean[iSC] = (minuit->X()[3]);
DTHETAe_SC_Mean[iSC] = (minuit->X()[4]);
DPSIe_SC_Mean[iSC] = (minuit->X()[5]);
DPHIe_SC_RMS[iSC] = (minuit->Errors()[3]);
DTHETAe_SC_RMS[iSC] = (minuit->Errors()[4]);
DPSIe_SC_RMS[iSC] = (minuit->Errors()[5]);
///==== end Chi2 minimization ====
std::cout << " iSC = " << iSC << " DPhi = " << DPHIe_SC_Mean[iSC] << " +/- " << DPHIe_SC_RMS[iSC] << std::endl;
std::cout << " iSC = " << iSC << " DTheta = " << DTHETAe_SC_Mean[iSC] << " +/- " << DTHETAe_SC_RMS[iSC] << std::endl;
std::cout << " iSC = " << iSC << " DPsi = " << DPSIe_SC_Mean[iSC] << " +/- " << DPSIe_SC_RMS[iSC] << std::endl;
std::cout << " iSC = " << iSC << " DX = " << DX_SC_Mean[iSC] << " +/- " << DX_SC_RMS[iSC] << std::endl;
std::cout << " iSC = " << iSC << " DY = " << DY_SC_Mean[iSC] << " +/- " << DY_SC_RMS[iSC] << std::endl;
std::cout << " iSC = " << iSC << " DZ = " << DZ_SC_Mean[iSC] << " +/- " << DZ_SC_RMS[iSC] << std::endl;
std::cout << "============================================================================" << std::endl;
std::cout << "============================================================================" << std::endl;
std::cout << "============================================================================" << std::endl;
}
