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doVariationGaussianFit.C
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doVariationGaussianFit.C
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using namespace RooFit;
struct fitResults
{
int ph_bin;
float mean;
};
enum model{
singleGaussian,doubleGaussian,tripleGaussian
};
TH1* GetHistogram(TFile *f, int col, int ph_bin);
fitResults WriteGaussianFitResults(ofstream &fout, TH1 *h, int col, int ph_bin,
double deltaMean,
double mean1val,
double sig1,
double sig2,
double c1,
double c2);
//some parameters to configure
const Int_t col=20; //first column to fit
const Int_t ncol=1; //number of column to fit
const Int_t ph_binlow[ncol]= {23
// 20,23,24,20,23,//1-5
// 15,19,20,25,26,//6-10
// 24,25,24,22,25,//11-15
// 23,24,23,25,23,//16-20
// 27,26,25,26,21,//21-25
// 23,25,23,27,23,//26-30
// 24,31,23,22,22,//31-35
// 21,27,27,25,28,//36-40
// 25,23,13,11,15,//41-45
// 14,13,11,14,13,//46-50
// 11,16,15,12,14,//51-55
// 14,15,16,14,14,//56-60
// 13,17,19,17,15,//61-65
// 13,17,19,16,17,//66-70
// 15,17,11,17,12,//71-76
// 15,15,15,13,18,//76-80
// 15,15,15,17,16,//81-85
// 14,10,18,17,15,//86-90
// 17,17,15,18,14,//91-95
// 15,12,17,14,16
};//96-100
const Int_t n = 30; //number of pp
Int_t ph_binup[ncol];
const Float_t dph_bin=16;
const Int_t dt_low=-3;
const Int_t dt_up=10;
const int nVar = 10;
double deltaMeanVar[4] = {0,1,2,3};
double mean1Var[nVar];
double sig1Var[nVar];
double sig2Var[nVar];
double c1Var[nVar];
double c2Var[nVar];
double mean1Min = 0.5;
double mean1Max = 2.5;
double sig1min = 0.3;
double sig1max = 2.;
double sig2min = 0.;
double sig2max = 2.;
double c1min = 0.;
double c1max = 1.0;
double c2min = 0.;
double c2max = 1.0;
bool useMinos = kTRUE;
model fitModel = tripleGaussian;
int doVariationGaussianFit(TString rootFile="root/hd_root-r72369.root") {
for(int icol=0;icol<ncol;icol++) ph_binup[icol] = ph_binlow[icol]+n;
double deltaMean1 = (mean1Max-mean1Min)/nVar;
double deltaSig1 = (sig1max-sig1min)/nVar;
double deltaSig2 = (sig2max-sig2min)/nVar;
double deltaC1 = (c1max-c1min)/nVar;
double deltaC2 = (c2max-c2min)/nVar;
for(int i=0;i<nVar;i++){
sig1Var[i] = sig1min + i*deltaSig1;
sig2Var[i] = sig2min + i*deltaSig2;
mean1Var[i] = mean1Min + i*deltaMean1;
c1Var[i] = c1min + i*deltaC1;
c2Var[i] = c2min + i*deltaC2;
}
TFile *f = new TFile(rootFile,"read");
for(int j=col;j<col+ncol;j++){
Float_t mean[n];
Float_t ph_bina[n];
stringstream ss; ss << j;
for (int i=ph_binlow[j-col];i<ph_binup[j-col];i++)
{
stringstream sph; sph << (i-0.5)*dph_bin;
system("mkdir -p variation-gaussian-fits-csv/col_"+TString(ss.str()));
ofstream fout; fout.open("variation-gaussian-fits-csv/col_"+TString(ss.str())+"/"+ TString(sph.str()) +".csv");
for (size_t ideltaMeanVar = 0; ideltaMeanVar < 4; ideltaMeanVar++)
{
for (size_t isig1Var = 0; isig1Var < nVar; isig1Var++)
{
for (size_t isig2Var = 0; isig2Var < nVar; isig2Var++)
{
for (size_t imean1Var = 0; imean1Var < nVar; imean1Var++)
{
for (size_t ic1Var = 0; ic1Var < nVar; ic1Var++)
{
for (size_t ic2Var = 0; ic2Var < nVar; ic2Var++){
TH1 *h = GetHistogram(f,j,i);
fitResults fR = WriteGaussianFitResults(fout,h,j,i,
deltaMeanVar[ideltaMeanVar],
mean1Var[imean1Var],
sig1Var[isig1Var],
sig2Var[isig2Var],
c1Var[ic1Var],
c2Var[ic2Var]
);
delete h;
}
}
}
}
}
}
fout.close();
}
}
return 0;
}
TH1* GetHistogram(TFile *f, int col, int ph_bin){
stringstream ss_c; ss_c << col;
TH2I *h2 = (TH2I*)f->Get("TAGM_TW/t-rf/h_dt_vs_pp_"+TString(ss_c.str()));
stringstream ss_ph; ss_ph << h2->GetXaxis()->GetBinCenter(ph_bin);
TH1 *h;
h = h2->ProjectionY(TString(h2->GetName())+"_"+TString(ss_ph.str()),ph_bin,ph_bin);
h->GetXaxis()->SetRangeUser(dt_low,dt_up);
h->SetTitle("TAGM column "+TString(ss_c.str())+", Pulse-peak "+TString(ss_ph.str()));
h->GetXaxis()->SetTitle("time(TDC) - time(RF) [ns]");
delete h2;
return h;
}
fitResults WriteGaussianFitResults(ofstream &fout, TH1 *h, int col, int ph_bin,
double deltaMean,
double mean1val,
double sig1,
double sig2,
double c1,
double c2)
{
TString sep = ",";
RooRealVar x("TDC time difference","TDC time difference [ns]",dt_low,dt_up);
RooDataHist data("data","data",RooArgList(x),h);
RooRealVar mean1("mean1","mean1",mean1val,dt_low,dt_up);
RooRealVar sigma1("sigma1","sigma1",sig1,sig1min,sig1max);
RooPlot *plot = x.frame();
if (fitModel==singleGaussian){
RooGaussian fitFunction("gauss1","gauss1",x,mean1,sigma1);
fitFunction.fitTo(data,RooFit::Minos(useMinos));//
data.plotOn(plot);
fitFunction.plotOn(plot);
fout << col << sep << ph_bin << sep << deltaMean << sep << mean1val << sep << sig1 << sep << sig2 << sep << 0 << sep << 0 << sep << plot->chiSquare() << endl;
}
else{
if (fitModel==doubleGaussian){
RooRealVar mean2("mean2","mean2",mean1val-deltaMean,dt_low,dt_up);
RooRealVar sigma1("sigma1","sigma1",sig1,sig1min,sig1max);
RooGaussian gauss1("gauss1","gauss1",x,mean1,sigma1);
RooRealVar sigma2("sigma2","sigma2",sig2,sig2min,sig2max);
RooGaussian gauss2("gauss2","gauss2",x,mean2,sigma2);
RooRealVar f1("f1","f1",0.9,0.1,c1);
RooAddPdf fitFunction("doubleGauss","doubleGauss",RooArgList(gauss1,gauss2),RooArgList(f1));
fitFunction.fitTo(data,RooFit::Minos(useMinos));
data.plotOn(plot);
fitFunction.plotOn(plot);
fout << col << sep << ph_bin << sep << deltaMean << sep << mean1val << sep << sig1 << sep << sig2 << sep << c1 << sep << 0 << sep << plot->chiSquare() << endl;
}
else
{
if (fitModel==tripleGaussian){
RooRealVar mean2("mean2","mean2",mean1val-deltaMean,dt_low,dt_up);
RooRealVar mean3("mean3","mean3",mean1val,dt_low,dt_up);
RooGaussian gauss1("gauss1","gauss1",x,mean1,sigma1);
RooRealVar sigma2("sigma2","sigma2",sig2,sig2min,sig2max);
RooGaussian gauss2("gauss2","gauss2",x,mean2,sigma2);
RooRealVar sigma3("sigma3","sigma3",sig1,sig1min,sig1max);
RooGaussian gauss3("gauss3","gauss3",x,mean3,sigma3);
RooRealVar f1("f1","f1",0.01,0.01,c1);
RooRealVar f2("f2","f2",0.01,0.01,c2);
RooAddPdf fitFunction("tripleGaussian","tripleGaussian",RooArgList(gauss1,gauss2,gauss3),RooArgList(f1,f2));
fitFunction.fitTo(data,RooFit::Minos(useMinos));//
data.plotOn(plot);
fitFunction.plotOn(plot);
fout << col << sep << ph_bin << sep << deltaMean << sep << mean1val << sep << sig1 << sep << sig2 << sep << c1 << sep << c2 << sep << plot->chiSquare() << endl;
}
else
{
cout << "Error! Incorrect choosen model.";
EXIT_FAILURE;
}
}
} delete plot;
fitResults fResults;
fResults.mean = mean1.getVal();
fResults.ph_bin = ph_bin;
return fResults;
}