void trisCheckCorrection_unbinnedfit(Char_t* EBEE = 0,
Int_t evtsPerPoint = 0,
float laserCorrMin = -1.,
float laserCorrMax = -1.)
{
// Set style options
gROOT->Reset();
gROOT->SetStyle("Plain");
gStyle->SetPadTickX(1);
gStyle->SetPadTickY(1);
gStyle->SetOptTitle(0);
gStyle->SetOptStat(1110);
gStyle->SetOptFit(1);
// Check qualifiers
if ( strcmp(EBEE,"EB")!=0 && strcmp(EBEE,"EE")!=0 )
{
std::cout << "CHK-STB Error: unknown partition " << EBEE << std::endl;
std::cout << "CHK-STB Select either EB or EE ! " << std::endl;
return;
}
if ( strcmp(EBEE,"EB") == 0 )
{
lcMin = 0.99;
lcMax = 1.05;
}
else
{
lcMin = 0.99;
lcMax = 1.11;
}
if( (laserCorrMin != -1.) && (laserCorrMax != -1.) )
{
lcMin = laserCorrMin;
lcMax = laserCorrMax;
}
// Get trees
std::cout << std::endl;
TChain* ntu_DA = new TChain("ntu");
FillChain(ntu_DA,"inputDATA.txt");
std::cout << " DATA: " << std::setw(8) << ntu_DA->GetEntries() << " entries" << std::endl;
TChain* ntu_MC = new TChain("ntu");
FillChain(ntu_MC,"inputMC.txt");
std::cout << "REFERENCE: " << std::setw(8) << ntu_MC->GetEntries() << " entries" << std::endl;
if (ntu_DA->GetEntries() == 0 || ntu_MC->GetEntries() == 0 )
{
std::cout << "CHK-STB Error: At least one file is empty" << std::endl;
return;
}
// Set branch addresses
int runId;
int isW, isZ;
int timeStampHigh;
float seedLaserAlpha;
float avgLaserCorrection, scCrackCorrection;
float EoP;
float scE, scERaw, scEta, scEtaWidth, scPhiWidth;
int seedIeta,seedIphi;
int seedIx,seedIy,seedZside;
float esE;
float seedLaserCorrection;
int iPhi,iEta;
ntu_DA->SetBranchAddress("runId", &runId);
ntu_DA->SetBranchAddress("isW", &isW);
//ntu_DA->SetBranchAddress("isZ", &isZ);
ntu_DA->SetBranchAddress("timeStampHigh", &timeStampHigh);
ntu_DA->SetBranchAddress("ele1_scCrackCorr", &scCrackCorrection);
ntu_DA->SetBranchAddress("ele1_scLaserCorr", &avgLaserCorrection);
ntu_DA->SetBranchAddress("ele1_seedLaserCorr", &seedLaserCorrection);
ntu_DA->SetBranchAddress("ele1_seedLaserAlpha", &seedLaserAlpha);
ntu_DA->SetBranchAddress("ele1_es", &esE);
ntu_DA->SetBranchAddress("ele1_scE", &scE);
ntu_DA->SetBranchAddress("ele1_scERaw", &scERaw);
ntu_DA->SetBranchAddress("ele1_scEta", &scEta);
ntu_DA->SetBranchAddress("ele1_scEtaWidth", &scEtaWidth);
ntu_DA->SetBranchAddress("ele1_scPhiWidth", &scPhiWidth);
ntu_DA->SetBranchAddress("ele1_EOverP", &EoP);
ntu_DA->SetBranchAddress("ele1_seedIphi", &iPhi);
ntu_DA->SetBranchAddress("ele1_seedIeta", &iEta);
ntu_DA->SetBranchAddress("ele1_seedIeta", &seedIeta);
ntu_DA->SetBranchAddress("ele1_seedIphi", &seedIphi);
ntu_DA->SetBranchAddress("ele1_seedIx", &seedIx);
ntu_DA->SetBranchAddress("ele1_seedIy", &seedIy);
ntu_DA->SetBranchAddress("ele1_seedZside", &seedZside);
ntu_MC->SetBranchAddress("isW", &isW);
ntu_MC->SetBranchAddress("isZ", &isZ);
ntu_MC->SetBranchAddress("ele1_scEta", &scEta);
ntu_MC->SetBranchAddress("ele1_EOverP", &EoP);
float params[42];
InitializeParams(params);
// Build the reference from 'infile2'
std::cout << std::endl;
std::cout << "***** Build reference for " << EBEE << " *****" << std::endl;
templateHisto = new TH1F("templateHisto", "", 1200, 0., 5.);
for(int ientry = 0; ientry < ntu_MC->GetEntries(); ++ientry)
{
if( (ientry%100000 == 0) ) std::cout << "reading MC entry " << ientry << std::endl;
ntu_MC->GetEntry(ientry);
if (strcmp(EBEE,"EB")==0 && fabs(scEta) > 1.4442) continue; // barrel
if (strcmp(EBEE,"EE")==0 && (fabs(scEta) < 1.56 || fabs(scEta) > 2.5 )) continue; // endcap
//if( seedLaserAlpha > 1.5 ) continue;
//if( fabs(scEta) > 0.44 ) continue;
//if( fabs(scEta) < 0.44 || fabs(scEta) > 0.77 ) continue;
//if( fabs(scEta) < 0.77 || fabs(scEta) > 1.10 ) continue;
//if( fabs(scEta) < 1.10 || fabs(scEta) > 1.56 ) continue;
//if( fabs(scEta) < 1.56 || fabs(scEta) > 2.00 ) continue;
//if( fabs(scEta) < 2.00 ) continue;
templateHisto -> Fill(EoP);
}
int rebin = 4;
if (strcmp(EBEE,"EB")==0) rebin = 2;
templateHisto -> Rebin(rebin);
FitTemplate();
std::cout << "Reference built for " << EBEE << " - " << templateHisto->GetEntries() << " events" << std::endl;
// Loop and sort events
std::cout << std::endl;
std::cout << "***** Sort events and define bins *****" << std::endl;
int nEntries = ntu_DA -> GetEntriesFast();
int nSavePts = 0;
std::vector<bool> isSavedEntries(nEntries);
std::vector<SorterLC> sortedEntries;
for(int ientry = 0; ientry < nEntries; ++ientry)
{
ntu_DA -> GetEntry(ientry);
isSavedEntries.at(ientry) = false;
// save only what is needed for the analysis!!!
if (strcmp(EBEE,"EB")==0 && fabs(scEta) > 1.4442) continue; // barrel
if (strcmp(EBEE,"EE")==0 && (fabs(scEta) < 1.56 || fabs(scEta) > 2.5 )) continue; // endcap
//if( fabs(scEta) > 0.44 ) continue;
//if( fabs(scEta) < 0.44 || fabs(scEta) > 0.77 ) continue;
//if( fabs(scEta) < 0.77 || fabs(scEta) > 1.10 ) continue;
//if( fabs(scEta) < 1.10 || fabs(scEta) > 1.56 ) continue;
//if( fabs(scEta) < 1.56 || fabs(scEta) > 2.00 ) continue;
//if( fabs(scEta) < 2.00 ) continue;
if( seedLaserCorrection <= 1.) continue;
if( seedLaserAlpha < 1.5 ) continue;
//if( timeStampHigh > 1303862400 ) continue;
if( seedZside < 0 )
if( (seedIx > 20 ) && (seedIx < 50) && (seedIy > 85) && (seedIy < 92) ) continue;
if( seedZside == -1 )
if( (seedIx > 35 ) && (seedIx < 55) && (seedIy > 80) && (seedIy < 87) ) continue;
if( seedZside > 0 )
if( (seedIx > 65 ) && (seedIx < 77) && (seedIy > 33) && (seedIy < 57) ) continue;
if( seedZside > 0 )
if( (seedIx > 75 ) && (seedIx < 93) && (seedIy > 18) && (seedIy < 37) ) continue;
//if ( runId < 163045 ) continue;
//if ( runId >= 163232 ) continue;
//if ( runId < 163232 ) continue;
//*********************** CLUSTER CORR *****************************
//if( (ientry%1 == 0) ) std::cout << "\n\n\nreading entry " << ientry << std::endl;
//Ediff -> Fill( ( (scCrackCorrection*fClusterCorrections(scERaw+esE,scEta,scPhiWidth/scEtaWidth,params))-scE)/scE );
//Ediff_vsEta -> Fill( scEta, ( (esE+scCrackCorrection*fClusterCorrections(scERaw,scEta,scPhiWidth/scEtaWidth,params))-scE)/scE );
//if( fabs(fClusterCorrections(scERaw,scEta,scPhiWidth/scEtaWidth,params)-scE) > 0.001 )
//{
// std::cout << "\n\n" << std::endl;
// std::cout << "scEta = " << scEta << " scE = " << scE << " scERaw = " << scERaw << std::endl;
// std::cout << "scERaw_corr = " << fClusterCorrections(scERaw,scEta,scPhiWidth/scEtaWidth,params) << std::endl;
//}
//*********************** CLUSTER CORR *****************************
isSavedEntries.at(ientry) = true;
SorterLC dummy;
dummy.laserCorr = avgLaserCorrection;
dummy.entry = ientry;
sortedEntries.push_back(dummy);
nSavePts++;
}
std::sort(sortedEntries.begin(),sortedEntries.end(),SorterLC());
std::cout << "Data sorted in " << EBEE << " - " << nSavePts << " events" << std::endl;
//TCanvas* c_diff = new TCanvas("c_diff","c_diff");
//c_diff -> cd();
//Ediff -> Draw();
//
//TCanvas* c_diff_vsEta = new TCanvas("c_diff_vsEta","c_diff");
//c_diff_vsEta -> cd();
//Ediff_vsEta -> Draw("colz");
// bins with evtsPerPoint events per bin
int nBins = std::max(1,int(nSavePts/evtsPerPoint));
int nBinPts = int( nSavePts/nBins );
int nBinTempPts = 0;
std::vector<int> binEntryMax;
binEntryMax.push_back(0);
for(int iSaved = 0; iSaved < nSavePts; ++iSaved)
{
++nBinTempPts;
if( nBinTempPts == nBinPts )
{
binEntryMax.push_back( iSaved );
nBinTempPts = 0;
}
}
binEntryMax.at(nBins) = nSavePts;
std::cout << "nBins = " << nBins << std::endl;
for(int bin = 0; bin < nBins; ++bin)
std::cout << "bin: " << bin
<< " entry min: " << setw(6) << binEntryMax.at(bin)
<< " entry max: " << setw(6) << binEntryMax.at(bin+1)
<< " events: " << setw(6) << binEntryMax.at(bin+1)-binEntryMax.at(bin)
<< std::endl;
TVirtualFitter::SetDefaultFitter("Fumili2");
// histogram definition
TH1F* h_EoP_spread;
TH1F* h_EoC_spread;
TH2F* h_LC_map = new TH2F("h_LC_map","",360,0.,360,170,-85,85);
if ( strcmp(EBEE,"EB")==0 )
{
h_EoP_spread = new TH1F("h_EoP_spread","",100,0.95,1.01);
h_EoC_spread = new TH1F("h_EoC_spread","",100,0.95,1.01);
}
else
{
h_EoP_spread = new TH1F("h_EoP_spread","",100,0.91,1.03);
h_EoC_spread = new TH1F("h_EoC_spread","",100,0.91,1.03);
}
h_EoP_spread -> SetLineColor(kRed+2);
h_EoP_spread -> SetLineWidth(2);
h_EoP_spread -> GetXaxis() -> SetTitle("Relative E/p scale");
h_EoC_spread -> SetLineColor(kGreen+2);
h_EoC_spread -> SetLineWidth(2);
h_EoC_spread -> GetXaxis() -> SetTitle("Relative E/p scale");
TH1F** h_EoP = new TH1F*[nBins];
TH1F** h_EoC = new TH1F*[nBins];
TH1F** h_Las = new TH1F*[nBins];
for(int i = 0; i < nBins; ++i)
{
char histoName[80];
sprintf(histoName, "EoP_%d", i);
h_EoP[i] = new TH1F(histoName, histoName, 1200, 0., 3.);
h_EoP[i] -> SetFillColor(kRed+2);
h_EoP[i] -> SetFillStyle(3004);
h_EoP[i] -> SetMarkerStyle(7);
h_EoP[i] -> SetMarkerColor(kRed+2);
h_EoP[i] -> SetLineColor(kRed+2);
sprintf(histoName, "EoC_%d", i);
h_EoC[i] = new TH1F(histoName, histoName, 1200, 0., 3.);
h_EoC[i] -> SetFillColor(kGreen+2);
h_EoC[i] -> SetFillStyle(3004);
h_EoC[i] -> SetMarkerStyle(7);
h_EoC[i] -> SetMarkerColor(kGreen+2);
h_EoC[i] -> SetLineColor(kGreen+2);
sprintf(histoName, "Las_%d", i);
h_Las[i] = new TH1F(histoName, histoName, 100, 0.5, 1.5);
}
// data definition
std::vector< std::vector<double>* > dataEoP;
std::vector< std::vector<double>* > dataEoC;
for (int jbin = 0; jbin< nBins; jbin++){
dataEoP.push_back(new std::vector<double>);
dataEoC.push_back(new std::vector<double>);
}
// function definition
TF1** f_EoP = new TF1*[nBins];
TF1** f_EoC = new TF1*[nBins];
// loop on the saved and sorted events
std::cout << std::endl;
std::cout << "***** Fill and fit histograms *****" << std::endl;
for(int ientry = 0; ientry < nEntries; ++ientry)
{
if( (ientry%10000 == 0) ) std::cout << "reading entry " << ientry << std::endl;
if( isSavedEntries.at(ientry) == false ) continue;
int iSaved = -1;
for(iSaved = 0; iSaved < nSavePts; ++iSaved)
if( ientry == sortedEntries[iSaved].entry ) break;
int bin = -1;
for(bin = 0; bin < nBins; ++bin)
if( iSaved >= binEntryMax.at(bin) && iSaved < binEntryMax.at(bin+1) )
break;
//std::cout << "ientry = " << ientry << " iSaved: " << iSaved << " bin: " << bin << std::endl;
ntu_DA->GetEntry(ientry);
float scale = 1.;
//scale = sqrt( pow(avgLaserCorrection,((1.52-0.7843)/1.52)-1.) );
//scale = 1. / (0.1811 + 0.7843*avgLaserCorrection);
//// fill the bins
(h_Las[bin]) -> Fill(avgLaserCorrection);
(h_EoP[bin]) -> Fill(EoP/avgLaserCorrection);
(h_EoC[bin]) -> Fill(EoP * scale);
h_LC_map->Fill(iPhi,iEta,seedLaserCorrection);
// fill te vectors data E/p
dataEoP[bin]->push_back(EoP/avgLaserCorrection);
dataEoC[bin]->push_back(EoP);
}
// Define graph and histograms
TGraphAsymmErrors* g_fit = new TGraphAsymmErrors();
TGraphAsymmErrors* g_c_fit = new TGraphAsymmErrors();
// define the fitting function
// N.B. [0] * ( [1] * f( [1]*(x-[2]) ) )
histoFunc* templateHistoFunc = new histoFunc(templateHisto);
//templateFunc = new TF1("templateFunc", templateHistoFunc, 0., 5., 3, "histoFunc");
//templateFunc -> SetParName(0,"Norm");
//templateFunc -> SetParName(1,"Scale factor");
//templateFunc -> SetLineWidth(1);
//templateFunc -> SetNpx(10000);
//templateFunc -> SetParameter(0, 1 );
//templateFunc -> SetParameter(1, 1);
//templateFunc -> FixParameter(2, 0.);
//templateFunc -> FixParameter(0, 1./templateFunc ->Integral(0.,5.) ); // normalized to 1. BUT will be renormalized to 1 at each iteration!
TFitterMinuit* myfit = new TFitterMinuit(1);
myfit->SetFCN(mylike);
myfit->SetPrintLevel(-1);
for(int i = 0; i < nBins; ++i)
{
h_EoP[i] -> Rebin(rebin*4);
h_EoC[i] -> Rebin(rebin*4);
//------------------------------------
// Fill the graph for uncorrected data
// fit uncorrected data
mydata = dataEoP.at(i);
myfit->Clear();
myfit->SetParameter(0, "scale", 1.,0.0005,0.50,1.50);
double arglist[2];
arglist[0] = 10000; // Max number of function calls
arglist[1] = 1e-5; // Tolerance on likelihood ?????????
int fStatus = myfit->ExecuteCommand("MIGRAD",arglist,2);
double amin,edm,errdef;
int nvpar,nparx;
myfit->GetStats(amin, edm, errdef, nvpar, nparx);
double bestScale = myfit->GetParameter(0);
double eee = myfit->GetParError(0);
char funcName[50];
sprintf(funcName,"f_EoP_%d",i);
f_EoP[i] = (TF1*)(templateFunc->Clone());
f_EoP[i] -> SetParameter(0,h_EoP[i]->GetEntries());
f_EoP[i] -> SetParameter(7,1.5);
f_EoP[i] -> SetParName(0,"Norm");
f_EoP[i] -> SetParName(1,"Scale factor");
f_EoP[i] -> SetLineWidth(1);
f_EoP[i] -> SetNpx(10000);
double xNorm = h_EoP[i]->GetEntries()/templateHisto->GetEntries() *
h_EoP[i]->GetBinWidth(1)/templateHisto->GetBinWidth(1);
//f_EoP[i] -> FixParameter(0, xNorm);
//f_EoP[i] -> SetParameter(1, bestScale);
//f_EoP[i] -> FixParameter(2, 0.);
f_EoP[i] -> SetLineColor(kRed+2);
// Fill the graph
if( fStatus == 0 && eee > 0. )
{
g_fit -> SetPoint(i, h_Las[i]->GetMean() , 1./bestScale);
g_fit -> SetPointError(i, h_Las[i]->GetRMS(), h_Las[i]->GetRMS(), eee, eee);
h_EoP_spread -> Fill(1./bestScale);
}
else
std::cout << "Fitting uncorrected time bin: " << i << " Fail status: " << fStatus << " sigma: " << eee << endl;
//----------------------------------
// Fill the graph for corrected data
// fit uncorrected data
mydata = dataEoC.at(i);
myfit->Clear();
myfit->SetParameter(0, "scale", 1.,0.0005,0.50,1.50);
arglist[0] = 10000; // Max number of function calls
arglist[1] = 1e-5; // Tolerance on likelihood ?????????
fStatus = myfit->ExecuteCommand("MIGRAD",arglist,2);
myfit->GetStats(amin, edm, errdef, nvpar, nparx);
bestScale = myfit->GetParameter(0);
eee = myfit->GetParError(0);
sprintf(funcName,"f_EoC_%d",i);
f_EoC[i] = (TF1*)(templateFunc->Clone());
f_EoC[i] -> SetParameter(0,h_EoC[i]->GetEntries());
f_EoC[i] -> SetParameter(7,bestScale);
f_EoC[i] -> SetParName(0,"Norm");
f_EoC[i] -> SetParName(1,"Scale factor");
f_EoC[i] -> SetLineWidth(1);
f_EoC[i] -> SetNpx(10000);
xNorm = h_EoC[i]->GetEntries()/templateHisto->GetEntries() *
h_EoC[i]->GetBinWidth(1)/templateHisto->GetBinWidth(1);
//
//f_EoC[i] -> SetParameter(1, bestScale);
//f_EoC[i] -> FixParameter(2, 0.);
f_EoC[i] -> SetLineColor(kGreen+2);
// fill the graph
if( fStatus == 0 && eee > 0. )
{
g_c_fit -> SetPoint(i, h_Las[i]->GetMean() , 1./bestScale);
g_c_fit -> SetPointError(i, h_Las[i]->GetRMS() , h_Las[i]->GetRMS() , eee, eee);
h_EoC_spread -> Fill(1./bestScale);
}
else
std::cout << "Fitting corrected time bin: " << i << " Fail status: " << fStatus << " sigma: " << eee << endl;
}
TF1* pol0 = new TF1("pol0","pol0");
pol0 -> SetLineColor(kGreen+2);
pol0 -> SetLineWidth(3);
pol0 -> SetLineStyle(2);
g_c_fit -> Fit("pol0","Q+");
// Drawings
TPaveStats** s_EoP = new TPaveStats*[nBins];
TPaveStats** s_EoC = new TPaveStats*[nBins];
TCanvas *c1[100];
for(int i = 0; i < nBins; ++i)
{
char canvasName[50];
if (i%2==0) {
sprintf(canvasName, "Fits-%0d", i/2);
c1[i/2] = new TCanvas(canvasName, canvasName);
c1[i/2] -> Divide(2,1);
}
c1[i/2] -> cd (i%2+1);
h_EoP[i] -> GetXaxis() -> SetTitle("E/p");
h_EoP[i] -> GetXaxis() -> SetRangeUser(0.5,1.5);
h_EoP[i] -> Draw("e");
gPad->Update();
s_EoP[i]= (TPaveStats*)(h_EoP[i]->GetListOfFunctions()->FindObject("stats"));
s_EoP[i]->SetTextColor(kRed+2);
h_EoC[i] -> Draw("esames");
gPad->Update();
s_EoC[i]= (TPaveStats*)(h_EoC[i]->GetListOfFunctions()->FindObject("stats"));
s_EoC[i]->SetY1NDC(0.59); //new x start position
s_EoC[i]->SetY2NDC(0.79); //new x end position
s_EoC[i]->SetTextColor(kGreen+2);
s_EoC[i]->Draw();
f_EoP[i]->Draw("same");
f_EoC[i]->Draw("same");
}
/*
TCanvas *c2[100];
for(int i = 0; i < nBins; ++i)
{
char canvasName[50];
if (i%6==0) {
sprintf(canvasName, "LaserCorr-%0d", i/6);
c2[i/6] = new TCanvas(canvasName, canvasName);
c2[i/6] -> Divide(3,2);
}
c2[i/6] -> cd (i%6+1);
h_Las[i] -> GetXaxis() -> SetTitle("laser correction");
h_Las[i] -> GetXaxis() -> SetRangeUser(0.5,1.5);
h_Las[i] -> Draw("");
gPad->Update();
s_Las[i]= (TPaveStats*)(h_Las[i]->GetListOfFunctions()->FindObject("stats"));
s_Las[i]->SetTextColor(kBlack);
}
*/
/*
TCanvas *cmap = new TCanvas("cmap","cmap");
cmap->cd();
gStyle->SetPalette(1);
h_LC_map->Draw("colz");
*/
// Final plots
TCanvas* cplot = new TCanvas("gplot", "gplot",100,100,725,500);
cplot->cd();
TPad *cLeft = new TPad("pad_0","pad_0",0.00,0.00,0.64,1.00);
TPad *cRight = new TPad("pad_1","pad_1",0.64,0.00,1.00,1.00);
cLeft->SetLeftMargin(0.15);
cLeft->SetRightMargin(0.025);
cRight->SetLeftMargin(0.025);
cLeft->Draw();
cRight->Draw();
float tYoffset = 1.5;
float labSize = 0.04;
float labSize2 = 0.07;
cLeft->cd();
cLeft->SetGridx();
cLeft->SetGridy();
// pad settings
TH1F *hPad = (TH1F*)gPad->DrawFrame(lcMin,0.9,lcMax,1.05);
hPad->GetXaxis()->SetTitle("Laser correction");
hPad->GetYaxis()->SetTitle("Relative E/p scale");
hPad->GetYaxis()->SetTitleOffset(tYoffset);
hPad->GetXaxis()->SetLabelSize(labSize);
hPad->GetXaxis()->SetTitleSize(labSize);
hPad->GetYaxis()->SetLabelSize(labSize);
hPad->GetYaxis()->SetTitleSize(labSize);
if ( strcmp(EBEE,"EB")==0 )
{
hPad -> SetMinimum(0.950);
hPad -> SetMaximum(1.010);
}
else
{
hPad -> SetMinimum(0.910);
hPad -> SetMaximum(1.030);
}
// draw trend plot
g_fit -> SetMarkerStyle(20);
g_fit -> SetMarkerSize(0.75);
g_fit -> SetMarkerColor(kRed+2);
g_fit -> SetLineColor(kRed+2);
g_fit -> Draw("P");
g_c_fit -> SetMarkerStyle(20);
g_c_fit -> SetMarkerColor(kGreen+2);
g_c_fit -> SetLineColor(kGreen+2);
g_c_fit -> SetMarkerSize(0.75);
g_c_fit -> Draw("P,same");
cRight -> cd();
TPaveStats* s_EoP_spread = new TPaveStats();
TPaveStats* s_EoC_spread = new TPaveStats();
h_EoC_spread -> SetFillStyle(3001);
h_EoC_spread -> SetFillColor(kGreen+2);
h_EoC_spread->GetYaxis()->SetLabelSize(labSize2);
h_EoC_spread->GetYaxis()->SetTitleSize(labSize2);
h_EoC_spread->GetYaxis()->SetNdivisions(505);
h_EoC_spread->GetYaxis()->SetLabelOffset(-0.02);
h_EoC_spread->GetXaxis()->SetLabelOffset(1000);
h_EoC_spread -> Draw("hbar");
gPad -> Update();
s_EoC_spread = (TPaveStats*)(h_EoC_spread->GetListOfFunctions()->FindObject("stats"));
s_EoC_spread ->SetTextColor(kGreen+2);
s_EoC_spread ->SetTextSize(0.06);
s_EoC_spread->SetX1NDC(0.49); //new x start position
s_EoC_spread->SetX2NDC(0.99); //new x end position
s_EoC_spread->SetY1NDC(0.875); //new x start position
s_EoC_spread->SetY2NDC(0.990); //new x end position
s_EoC_spread -> SetOptStat(1100);
s_EoC_spread -> Draw("sames");
h_EoP_spread -> SetFillStyle(3001);
h_EoP_spread -> SetFillColor(kRed+2);
h_EoP_spread -> Draw("hbarsames");
gPad -> Update();
s_EoP_spread = (TPaveStats*)(h_EoP_spread->GetListOfFunctions()->FindObject("stats"));
s_EoP_spread->SetX1NDC(0.49); //new x start position
s_EoP_spread->SetX2NDC(0.99); //new x end position
s_EoP_spread->SetY1NDC(0.750); //new x start position
s_EoP_spread->SetY2NDC(0.875); //new x end position
s_EoP_spread ->SetOptStat(1100);
s_EoP_spread ->SetTextColor(kRed+2);
s_EoP_spread ->SetTextSize(0.06);
s_EoP_spread -> Draw("sames");
}
void fitM(TF1* function, double& M, double& sigmaM, int& fitStatus)
{
//--- initialize Minuit
MinuitFCNadapter minuitFCNadapter(function);
TFitterMinuit* minuit = new TFitterMinuit();
minuit->SetMinuitFCN(&minuitFCNadapter);
//--- set Minuit strategy = 2,
// in order to enable reliable error estimates
// ( cf. http://www-cdf.fnal.gov/physics/statistics/recommendations/minuit.html )
minuit->SetStrategy(2);
minuit->SetMaxIterations(1000);
minuit->SetPrintLevel(-1);
minuit->SetErrorDef(0.5);
minuit->CreateMinimizer();
minuit->SetParameter(0, "M", 0., 2., 1.e-3, 1.e+1);
fitStatus = minuit->Minimize();
M = minuit->GetParameter(0);
sigmaM = minuit->GetParError(0);
}
