本文整理汇总了C++中TGraphErrors::Eval方法的典型用法代码示例。如果您正苦于以下问题:C++ TGraphErrors::Eval方法的具体用法?C++ TGraphErrors::Eval怎么用?C++ TGraphErrors::Eval使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类TGraphErrors
的用法示例。
在下文中一共展示了TGraphErrors::Eval方法的7个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: pointsed
//.........这里部分代码省略.........
if (check == "Uncor10t2_nConstituent_") PerfTitle="uncorr pt>10 #tracks > 2 & nConstituents >1";
std::vector< TString > discriminators;
for ( size_t itagger = 0; itagger < taggers.size(); ++itagger ) {
discriminators.push_back( check+"disc"+taggers[itagger]+"_udsg" );
}
// discriminators.push_back( "discTC3_udsg" );
// discriminators.push_back( "discTP_udsg" );
TCanvas *cv = new TCanvas("cv","cv",900,900);
TMultiGraph *mg =new TMultiGraph();
TLegend *legend0 = new TLegend(0.68,0.12,0.88,0.32);
// inverted axis
TMultiGraph *mginv =new TMultiGraph();
TLegend *legend1 = new TLegend(0.65,0.18,0.85,0.48);
std::ofstream salida("BTagPATop3"+check+".txt");
for ( size_t itagger = 0; itagger < taggers.size(); ++itagger ) {
TString tag = check+"g"+taggers[itagger]+"_udsg";
TGraphErrors *agraph = (TGraphErrors*) gDirectory->Get("BTagPATAnalyzer"+taggers[itagger]+"/"+taggers[itagger]+"/"+tag);
TGraph *dgraph = (TGraph*) gDirectory->Get("BTagPATAnalyzer"+taggers[itagger]+"/"+taggers[itagger]+"/"+discriminators[itagger]);
// TGraph *udsgvsdgraph = new TGraph(dgraph->GetN(),dgraph->GetY(),dgraph->GetX());
dgraph->Sort();
// udsgvsdgraph->Sort();
TGraphErrors *g = new TGraphErrors(agraph->GetN(),agraph->GetY(),agraph->GetX(),agraph->GetEY(),agraph->GetEX());
g->Sort();
g->SetLineColor(itagger+1);
legend0 -> AddEntry(g,taggers[itagger],"l");
mg->Add(g);
//inverted axis
TGraphErrors *ginv = new TGraphErrors(agraph->GetN(),agraph->GetX(),agraph->GetY(),agraph->GetEX(),agraph->GetEY());
ginv->Sort();
ginv->SetLineColor(colorlines[itagger]);
ginv->SetMarkerStyle(8);
ginv->SetMarkerColor(colorlines[itagger]);
legend1 -> AddEntry(ginv,labeltag[itagger],"l");
mginv->Add(ginv);
std::cout << " Tagger: " << tag << std::endl;
std::cout << " Loose(10%): " << " cut > " << std::setprecision(4) << dgraph->Eval(0.1) << " b-eff = " << g->Eval(0.1) << std::endl;
std::cout << " Medium(1%): " << " cut > " << std::setprecision(4) << dgraph->Eval(0.01) << " b-eff = " << g->Eval(0.01) << std::endl;
std::cout << " Tight(0.1%) = " << " cut > " << std::setprecision(4) << dgraph->Eval(0.001) << " b-eff = " << g->Eval(0.001) << std::endl;
salida << " " << taggers[itagger] << endl;
salida << " #bin \t b-eff \t err-beff \t non-beff \t err-non-b"<< endl;
for ( size_t i=0;i< agraph->GetN();i++){
salida << " " << (i+1) << " \t "
<< agraph->GetX()[i] <<" \t "
<< agraph->GetEX()[i]<<" \t "
<< agraph->GetY()[i] <<" \t "
<< agraph->GetEY()[i]
<< " "<< endl;
}
}
// cv->SetLogx();
mg->Draw("ALP");
mg->GetYaxis()->SetTitle("b-eff");
mg->GetXaxis()->SetTitle("udsg-mistagging");
legend0 -> Draw();
cv-> SetGrid();
cv-> Print ("BTagPATop"+check+".eps");
cv-> Print ("BTagPATop"+check+".png");
cv->cd(0);
cv->SetLogx();
mg->Draw("ALP");
legend0 -> Draw();
cv-> Print ("BTagPATop1"+check+".eps");
cv-> Print ("BTagPATop1"+check+".png");
//inverted axis
TCanvas *cvinv = new TCanvas("cvinv","cvinv",700,700);
cvinv->SetLogy(0);
mginv->Draw("ALP");
mginv->GetXaxis()->SetTitle("b-eff");
mginv->GetYaxis()->SetTitle("udsg-mistagging");
legend1 -> Draw();
cvinv->SetGrid();
cvinv-> Print ("BTagPATop2"+check+".eps");
cvinv-> Print ("BTagPATop2"+check+".png");
cvinv->cd(0);
// cvinv->Update();
// cvinv->SetLogx();
// mginv->SetXmin(10^-4);
// axis range using a histogram helper
TH2D*hpx = new TH2D("hpx",PerfTitle,200,0.0,1.005,200,0.00002,1.05);
hpx->SetStats(kFALSE);
hpx->Draw();
hpx->GetXaxis()->SetTitle("b-eff");
hpx->GetYaxis()->SetTitle("udsg-mistagging");
cvinv->SetLogy(1);
mginv->Draw("AP");
legend1 -> Draw();
cvinv-> Print ("BTagPATop3"+check+".eps");
cvinv-> Print ("BTagPATop3"+check+".png");
//ed}
}
示例2: if
//.........这里部分代码省略.........
yCoordinate = coordinates.at(1);
zCoorinate = 10*vectorOfReferenceChambers[ii];
Double_t errorValue = this->getChamberNumber(vectorOfReferenceChambers[ii])->getSizeOfCluster(clusterNum[ii]);
// histXZ->SetBinContent(zCoorinate,xCoordinate);
// histXZ->SetBinError(zCoorinate,errorValue/2);
//cout << xCoordinate << " " << yCoordinate << endl;
graphXZ->SetPoint(ii,vectorOfReferenceChambers[ii],xCoordinate);
graphXZ->SetPointError(ii,0,errorValue/2);
}
Double_t params[2];
graphXZ->Fit(fitfunc,"RFQ");
fitfunc->GetParameters(params);
//cout << "par1 " << params[0] << " par2 " << params[1] << " chi2 " << fitfunc->GetChisquare() << endl;
// The resudials - difference between estimated fit value and the middle of the nearest cluster
int prevReference = 0 , nextReference = 0 , prevReferencePartition = 0 , nextReferencePartition = 0;
bool currentChamberIsReference = false;
int startCounter = 0, endCounter = 0;
if ( abs(graphXZ->GetCorrelationFactor()) >= correlationFactor && abs(graphXZ->GetCorrelationFactor()) > currentBestCorrFact ) {
// in case of only one partition, get the partition number of the first reference point
currentBestCorrFact = abs(graphXZ->GetCorrelationFactor());
int referenceChambersIncrementor = 0;
bool negativeChannelNumberIsFound = false;
// ---------
for ( int currentChNumber = 0 ; currentChNumber < this->getNumberOfChambers() ; currentChNumber++ ) {
// check where the chamber is according to the reference chambers
vector<double> vectorOfpartitionsAndHit;
double channelNum = fitfunc->Eval(currentChNumber+1);
/** four cases 1. the chamber is before the first reference 2. the chamber is after the last reference 3. the chamber is between two references 4. the chamber is a reference */
for(int refCheck = 0 ; refCheck < vectorOfReferenceChambers.size(); refCheck++){
// find the surounding references
if (currentChNumber+1 == vectorOfReferenceChambers.at(refCheck)){
currentChamberIsReference = true;
break;
}
if ( vectorOfReferenceChambers.at(refCheck) > currentChNumber+1 && refCheck == 0 ){
// its before the first reference chamber
nextReference = vectorOfReferenceChambers.at(refCheck);
nextReferencePartition = this->getChamberNumber(nextReference)->getXYCoordinatesOfCluster(clusterNum[refCheck]).at(1);
break;
}
if ( vectorOfReferenceChambers.at(refCheck) < currentChNumber+1 && refCheck == vectorOfReferenceChambers.size() - 1 ){
// its after the last chamber
prevReference = vectorOfReferenceChambers.at(refCheck);
prevReferencePartition = this->getChamberNumber(prevReference)->getXYCoordinatesOfCluster(clusterNum[refCheck]).at(1);
break;
}
if ( vectorOfReferenceChambers.at(refCheck) < currentChNumber+1 && vectorOfReferenceChambers.at(refCheck+1) > currentChNumber+1 ){
// its between two references
prevReference = vectorOfReferenceChambers.at(refCheck) ;
nextReference = vectorOfReferenceChambers.at(refCheck+1);
prevReferencePartition = this->getChamberNumber(prevReference)->getXYCoordinatesOfCluster(clusterNum[refCheck]).at(1);
nextReferencePartition = this->getChamberNumber(nextReference)->getXYCoordinatesOfCluster(clusterNum[refCheck+1]).at(1);
break;
}
}
示例3: AnalyzeClipping
//.........这里部分代码省略.........
Long64_t firstIndex = 0;
Long64_t lastIndex = 0;
Long64_t inputGraphPoints = 0;
Long64_t outputGraphPoints = 0;
// hard coded values to cut the x axis of both waves
// Input wave
inputWaveName += " graph";
TGraphErrors *gInput = listOfGraphs->FindObject(inputWaveName);
gInput->SetLineColor(kRed);
gInput->SetLineWidth(2);
xInput = gInput->GetX();
yInput = gInput->GetY();
inputGraphPoints = gInput->GetN();
cout << inputGraphPoints << endl;
// Invert the input wave
for(Int_t i = 0; i < inputGraphPoints; i++) {
yInput[i] = -(yInput[i]);
}
// find the x at which the graph reaches the max value
iInputMax = TMath::LocMax(inputGraphPoints, yInput);
xInputMax = xInput[iInputMax];
cout << "iInputMax = " << iInputMax << endl;
cout << "xInputMax = " << xInputMax << endl;
InputMax = gInput->Eval(xInput[iInputMax]);
cout << "InputMax = " << InputMax << endl;
// Output wave
outputWaveName += " graph";
TGraphErrors *gOutput = listOfGraphs->FindObject(outputWaveName);
gOutput->SetLineWidth(2);
xOutput = gOutput->GetX();
yOutput = gOutput->GetY();
outputGraphPoints = gOutput->GetN();
// find the x at which the graph reaches the max value
iOutputMax = TMath::LocMax(outputGraphPoints, yOutput);
xOutputMax = xOutput[iOutputMax];
cout << "iOutputMax = " << iOutputMax << endl;
cout << "xOutputMax = " << xOutputMax << endl;
OutputMax = gOutput->Eval(xOutput[iOutputMax]);
cout << "OutputMax = " << OutputMax << endl;
// compute x delay between max points
Double_t delay = xOutputMax - xInputMax;
cout << "delay = " << delay << endl;
// Shift the x axis of the input graph and create a new graph with only a portion of the first graph
for(Int_t i = 0; i < inputGraphPoints; i++) {
xInput[i] += inputDelay;
示例4: disceff
void disceff(TString filename) {
gROOT->SetStyle("Plain");
TString cmssw;
// 167
cmssw = "$3.1.0_pre9$";
TFile *f = TFile::Open(filename);
std::vector< TString > taggers;
taggers.push_back( "TC2" );
taggers.push_back( "TC3" );
taggers.push_back( "TP" );
taggers.push_back( "BTP" );
taggers.push_back( "SSV" );
taggers.push_back( "CSV" );
taggers.push_back( "MSV" );
taggers.push_back( "SMT" );
taggers.push_back( "SETbyIP3d" );
taggers.push_back( "SETbyPt" );
taggers.push_back( "SMTbyIP3d" );
taggers.push_back( "SMTbyPt" );
std::vector< TString > discriminators;
for ( size_t itagger = 0; itagger < taggers.size(); ++itagger ) {
discriminators.push_back( "disc"+taggers[itagger]+"_udsg" );
}
// discriminators.push_back( "discTC3_udsg" );
// discriminators.push_back( "discTP_udsg" );
const int dim=taggers.size();
TCanvas *cv[dim];
TMultiGraph* mg[dim];
for ( size_t itagger = 0; itagger < taggers.size(); ++itagger ) {
TString tag = "g"+taggers[itagger]+"_udsg";
TString tagb = "g"+taggers[itagger]+"_b";
TString tagc = "g"+taggers[itagger]+"_c";
cv[itagger] = new TCanvas("cv_"+taggers[itagger],"cv_"+taggers[itagger],700,700);
TLegend *legend0 = new TLegend(0.68,0.70,0.88,0.90);
TGraphErrors *agraph = (TGraphErrors*) gDirectory->Get("BTagPATAnalyzer"+taggers[itagger]+"/"+taggers[itagger]+"/"+tag);
TGraphErrors *bgraph = (TGraphErrors*) gDirectory->Get("BTagPATAnalyzer"+taggers[itagger]+"/"+taggers[itagger]+"/"+tagb);
TGraphErrors *cgraph = (TGraphErrors*) gDirectory->Get("BTagPATAnalyzer"+taggers[itagger]+"/"+taggers[itagger]+"/"+tagc);
TGraph *dgraph = (TGraph*) gDirectory->Get("BTagPATAnalyzer"+taggers[itagger]+"/"+taggers[itagger]+"/"+discriminators[itagger]);
TGraph *bvsdgraph = new TGraph(dgraph->GetN(),dgraph->GetY(),bgraph->GetY());
TGraph *cvsdgraph = new TGraph(dgraph->GetN(),dgraph->GetY(),cgraph->GetY());
TGraph *lvsdgraph = new TGraph(dgraph->GetN(),dgraph->GetY(),agraph->GetY());
TGraph *udsgvsdgraph = new TGraph(dgraph->GetN(),dgraph->GetY(),dgraph->GetX());
dgraph->Sort();
// udsgvsdgraph->Sort();
// udsgvsdgraph->SetLineColor(1);
// legend0 -> AddEntry(udsgvsdgraph,"control","l");
lvsdgraph->Sort();
lvsdgraph->SetLineColor(2);
legend0 -> AddEntry(lvsdgraph,tag,"l");
cvsdgraph->Sort();
cvsdgraph->SetLineColor(3);
legend0 -> AddEntry(cvsdgraph,tagc,"l");
bvsdgraph->Sort();
bvsdgraph->SetLineColor(4);
legend0 -> AddEntry(bvsdgraph,tagb,"l");
mg[itagger]= new TMultiGraph();
// mg[itagger]->Add(udsgvsdgraph);
mg[itagger]->Add(lvsdgraph);
mg[itagger]->Add(cvsdgraph);
mg[itagger]->Add(bvsdgraph);
// mg[itagger]->Add(dgraph);
cv[itagger]->cd(1);
mg[itagger]->Draw("ALP");
mg[itagger]->GetYaxis()->SetTitle("eff");
mg[itagger]->GetXaxis()->SetTitle("discriminant");
legend0 -> Draw();
cv[itagger]->Update();
cv[itagger]->cd(0);
cv[itagger]-> Print ("BTagPATeff_vs_disc"+taggers[itagger]+".eps");
cv[itagger]-> Print ("BTagPATeff_vs_disc"+taggers[itagger]+".ps");
TGraphErrors *g = new TGraphErrors(agraph->GetN(),agraph->GetY(),agraph->GetX(),agraph->GetEY(),agraph->GetEX());
g->Sort();
g->SetLineColor(itagger+1);
std::cout << " Tagger: " << tag << std::endl;
std::cout << " Loose(10%): " << " cut > " << std::setprecision(4) << dgraph->Eval(0.1) << " b-eff = " << g->Eval(0.1) << std::endl;
std::cout << " Medium(1%): " << " cut > " << std::setprecision(4) << dgraph->Eval(0.01) << " b-eff = " << g->Eval(0.01) << std::endl;
std::cout << " Tight(0.1%) = " << " cut > " << std::setprecision(4) << dgraph->Eval(0.001) << " b-eff = " << g->Eval(0.001) << std::endl;
}//end for
}
示例5: make1DLimit
void make1DLimit(TString combine_dir,TString type= "WH",bool blind=true){
//TString combine_dir = "test_runSusyHgg/signalInj_sms_ChiWH_0_175/";
//WH
wh_limits.push_back(wh_125);
wh_limits.push_back(wh_150);
wh_limits.push_back(wh_175);
wh_limits.push_back(wh_200);
//HH
hh_limits.push_back(hh_125);
hh_limits.push_back(hh_150);
hh_limits.push_back(hh_175);
hh_limits.push_back(hh_200);
TGraph obser( (200-125)/25 );
TGraph graph( (200-125)/25 );
TGraphAsymmErrors error( (200-125)/25 );
TGraphAsymmErrors error2S( (200-125)/25 );
TGraph obser_r( (200-125)/25 );
TGraph graph_r( (200-125)/25 );
TGraphAsymmErrors error_r( (200-125)/25 );
TGraphAsymmErrors error_r2S( (200-125)/25 );
TGraphErrors* theo = 0;
if(type=="WH") theo = getTheoXSec("xsecs/CharginoNeutralino.txt");
else theo = getTheoXSec("xsecs/Higgsino_ElectroHiggs.txt");
//else theo = getTheoXSec("/home/amott/HggApp/SusyHgg/xsecs/Higgsino.txt");
for(int m=125;m<=200;m+=25) {
int i=(m-125)/25;
TFile limit_file(Form("%s/higgsCombineChi%s_0_%d.Asymptotic.mH120.root",combine_dir.Data(),type.Data(),m) );
TTree *limit_tree = (TTree*)limit_file.Get("limit");
TTreeFormula limit_form("get_limit","limit",limit_tree);
float down_2s = -1;
float down = -1;
float exp = -1;
float up = -1;
float up_2s = -1;
float obs = -1;
if( type == "WH" )
{
down_2s = wh_limits.at(i)[0];
down = wh_limits.at(i)[1];
exp = wh_limits.at(i)[2];
up = wh_limits.at(i)[3];
up_2s = wh_limits.at(i)[4];
obs = wh_limits.at(i)[5];
}
else if ( type == "HH")
{
down_2s = hh_limits.at(i)[0];
down = hh_limits.at(i)[1];
exp = hh_limits.at(i)[2];
up = hh_limits.at(i)[3];
up_2s = hh_limits.at(i)[4];
obs = hh_limits.at(i)[5];
}
else
{
std::cerr << "UNRECOGNIZED OPTION!!! QUITTING" << std::endl;
}
if(i==0) m+=5; //first point is actually at m=130
graph.SetPoint(i,float(m), exp);
error.SetPoint(i,float(m), exp);
error2S.SetPoint(i, float(m), exp);
error.SetPointError(i, 0, 0, exp-down, up-exp);
error2S.SetPointError(i, 0 , 0 , exp-down_2s, up_2s-exp);
graph_r.SetPoint(i,float(m),exp/theo->Eval(m));
error_r.SetPoint(i,float(m),exp/theo->Eval(m));
error_r2S.SetPoint(i,float(m),exp/theo->Eval(m));
error_r.SetPointError(i,0,0,(exp-down)/theo->Eval(m),(up-exp)/theo->Eval(m));
error_r2S.SetPointError(i, 0, 0, (exp-down_2s)/theo->Eval(m), (up_2s-exp)/theo->Eval(m) );
obser.SetPoint(i,float(m),obs);
obser_r.SetPoint(i,float(m),obs/theo->Eval(m));
if(i==0) m-=5;
}
TCanvas cv;
cv.SetLogy();
cv.SetGrid(1,1);
theo->SetMaximum(1e2);
theo->SetMinimum(1e-2);
theo->GetYaxis()->SetLabelSize(0.05);
theo->GetYaxis()->SetTitleSize(0.06);
theo->GetYaxis()->SetTitleOffset(0.8);
theo->GetYaxis()->SetTitle("95% CL #sigma upper limit (pb)");
theo->GetXaxis()->SetTitle("m_{chargino} (GeV)");
if(type=="HH") theo->GetXaxis()->SetTitle("m_{neutralino} (GeV)");
theo->SetFillColor(kBlue);
theo->SetLineStyle(kDotted);
theo->SetLineWidth(2);
error.SetMaximum(1e2);
//.........这里部分代码省略.........
示例6: AnalyzeWaveforms
//.........这里部分代码省略.........
Double_t xMin,xMax,yStart,yEnd;
Int_t graphPoints;
Double_t step;
// comparator outputs waves sum
TGraphErrors *gFirstCompWave = (TGraphErrors *)listOfCompWaves->First();
graphPoints = gFirstCompWave->GetN();
gFirstCompWave->GetPoint(0,xMin,yStart);
gFirstCompWave->GetPoint(graphPoints - 1,xMax,yEnd);
step = (xMax - xMin)/graphPoints;
cout << gFirstCompWave->GetName() << endl;
cout << "xMin = " << xMin << " xMax = " << xMax << " graphPoints = " << graphPoints << endl;
TGraphErrors *gCompSum = new TGraphErrors(graphPoints);
gCompSum->SetLineColor(kBlue);
gCompSum->SetLineWidth(2);
gCompSum->SetName("Comparator Outputs Sum");
gCompSum->SetTitle("Comparator Outputs Sum");
Int_t nCompWaves = listOfCompWaves->GetEntries();
Float_t gx,gy = 0;
// Alpha coefficiens are now written "hard coded" here
Float_t alphaArray[3] = {0.199,0.201,0.197};
// Deleays coming from the multiplexer are written "hard coded" here
Float_t muxDelayArray[3] = {0,77.14E-12,192.01E-12};
for(Int_t i = 0; i < graphPoints; i++) {
for(Int_t j = 0; j < nCompWaves; j++) {
TGraphErrors *gCompWave = (TGraphErrors *)listOfCompWaves->At(j);
gy += (gCompWave->Eval(xMin + i*step + muxDelayArray[j]))*alphaArray[j];
}
gCompSum->SetPoint(i,xMin + i*step,gy);
gy = 0;
}
// note that there is a manual correction on the x axis for the comparator waves sum to compare them better in the multigraph
Double_t *xArray = gCompSum->GetX();
for(Int_t i = 0; i < graphPoints; i++) {
xArray[i] += 5.6E-9;
}
// TCanvas *cCompSum = new TCanvas("cCompSum","Comparator Outputs Sum",800,600);
// gCompSum->Draw("AL");
// adder outputs waves sum
// THE ANALYSIS FOR THE ADDER OUTPUT WITH NOT DELAY AND 3 CHANNELS ADDED IS DEPRECATED.
// THERE WAS A MISTAKE IN THE DATA TAKING
// I'LL KEEP THE CODE HERE FOR FURTHER REFERENCE
/*
TGraphErrors *gFirstAdderWave = (TGraphErrors *)listOfAdderWaves->First();
graphPoints = gFirstAdderWave->GetN();
gFirstAdderWave->GetPoint(0,xMin,yStart);
gFirstAdderWave->GetPoint(graphPoints - 1,xMax,yEnd);
step = (xMax - xMin)/graphPoints;
cout << gFirstAdderWave->GetName() << endl;
cout << "xMin : " << xMin << " xMax : " << xMax << endl;
示例7: points
void points(TString filename) {
TString cmssw;
// 167
cmssw = "$1.6.7$";
TFile *f = TFile::Open(filename);
std::vector< TString > taggers;
taggers.push_back( "gTC2_udsg" );
taggers.push_back( "gTC3_udsg" );
taggers.push_back( "gTP_udsg" );
taggers.push_back( "gJBP_udsg" );
taggers.push_back( "gSSV_udsg" );
taggers.push_back( "gCSV_udsg" );
std::vector< TString > discriminators;
discriminators.push_back( "discTC2_udsg" );
discriminators.push_back( "discTC3_udsg" );
discriminators.push_back( "discTP_udsg" );
discriminators.push_back( "discJBP_udsg" );
discriminators.push_back( "discSSV_udsg" );
discriminators.push_back( "discCSV_udsg" );
//TCanvas *cv_TC = new TCanvas("cv_TC","cv_TC",700,700);
//TCanvas *cv_TP = new TCanvas("cv_TP","cv_TP",700,700);
std::cout << "Tagger & Point & Discriminator & light mistag & b-efficiency \\\\ \\hline" << std::endl;
for ( size_t itagger = 0; itagger < taggers.size(); ++itagger ) {
TString tag = taggers[itagger];
TGraphErrors *agraph = (TGraphErrors*) gDirectory->Get("Histograms/MCtruth/"+tag);
//if (taggers == "gTC2_udsg" || taggers =
TGraph *dgraph = (TGraph*) gDirectory->Get("Histograms/MCtruth/"+discriminators[itagger]);
dgraph->Sort();
TGraphErrors *g = new TGraphErrors(agraph->GetN(),agraph->GetY(),agraph->GetX(),agraph->GetEY(),agraph->GetEX());
g->Sort();
//cv[itagger] = new TCanvas("cv","cv",600,600);
//g->Draw("ACP");
TString se = " & ";
std::cout << tag << se << "Loose" << se << std::setprecision(3) << dgraph->Eval(0.1) << se << "0.1" << se << std::setprecision(2) << g->Eval(0.1) << "\\\\" << std::endl;
std::cout << tag << se << "Medium" << se << std::setprecision(3) << dgraph->Eval(0.01) << se << "0.01" << se << std::setprecision(2) << g->Eval(0.01) << "\\\\" << std::endl;
std::cout << tag << se << "Tight" << se << std::setprecision(3) << dgraph->Eval(0.001) << se << "0.001" << se << std::setprecision(2) << g->Eval(0.001) << "\\\\ \\hline" << std::endl;
}
}