//_________________________________________________________________________________________
Int_t checkPullTree(TString pathTree, TString pathNameThetaMap, TString pathNameSigmaMap,
TString mapSuffix, const Int_t collType /*0: pp, 1: pPb, 2: PbPb*/, const Bool_t plotPull = kTRUE,
const Double_t downScaleFactor = 1,
TString pathNameSplinesFile = "", TString prSplinesName = "",
TString fileNameTree = "bhess_PIDetaTree.root", TString treeName = "fTree")
{
const Bool_t isNonPP = collType != 0;
const Double_t massProton = AliPID::ParticleMass(AliPID::kProton);
Bool_t recalculateExpecteddEdx = pathNameSplinesFile != "";
TFile* f = 0x0;
f = TFile::Open(Form("%s/%s", pathTree.Data(), fileNameTree.Data()));
if (!f) {
std::cout << "Failed to open tree file \"" << Form("%s/%s", pathTree.Data(), fileNameTree.Data()) << "\"!" << std::endl;
return -1;
}
// Extract the data Tree
TTree* tree = dynamic_cast<TTree*>(f->Get(treeName.Data()));
if (!tree) {
std::cout << "Failed to load data tree!" << std::endl;
return -1;
}
// Extract the splines, if desired
TSpline3* splPr = 0x0;
if (recalculateExpecteddEdx) {
std::cout << "Loading splines to recalculate expected dEdx!" << std::endl << std::endl;
TFile* fSpl = TFile::Open(pathNameSplinesFile.Data());
if (!fSpl) {
std::cout << "Failed to open spline file \"" << pathNameSplinesFile.Data() << "\"!" << std::endl;
return 0x0;
}
TObjArray* TPCPIDResponse = (TObjArray*)fSpl->Get("TPCPIDResponse");
if (!TPCPIDResponse) {
splPr = (TSpline3*)fSpl->Get(prSplinesName.Data());
// If splines are in file directly, without TPCPIDResponse object, try to load them
if (!splPr) {
std::cout << "Failed to load object array from spline file \"" << pathNameSplinesFile.Data() << "\"!" << std::endl;
return 0x0;
}
}
else {
splPr = (TSpline3*)TPCPIDResponse->FindObject(prSplinesName.Data());
if (!splPr) {
std::cout << "Failed to load splines from file \"" << pathNameSplinesFile.Data() << "\"!" << std::endl;
return 0x0;
}
}
}
else
std::cout << "Taking dEdxExpected from Tree..." << std::endl << std::endl;
// Extract the correction maps
TFile* fMap = TFile::Open(pathNameThetaMap.Data());
if (!fMap) {
std::cout << "Failed to open thetaMap file \"" << pathNameThetaMap.Data() << "\"! Will not additionally correct data...." << std::endl;
}
TH2D* hMap = 0x0;
if (fMap) {
hMap = dynamic_cast<TH2D*>(fMap->Get(Form("hRefined%s", mapSuffix.Data())));
if (!hMap) {
std::cout << "Failed to load theta map!" << std::endl;
return -1;
}
}
TFile* fSigmaMap = TFile::Open(pathNameSigmaMap.Data());
if (!fSigmaMap) {
std::cout << "Failed to open simgaMap file \"" << pathNameSigmaMap.Data() << "\"!" << std::endl;
return -1;
}
TH2D* hThetaMapSigmaPar1 = dynamic_cast<TH2D*>(fSigmaMap->Get("hThetaMapSigmaPar1"));
if (!hThetaMapSigmaPar1) {
std::cout << "Failed to load sigma map for par 1!" << std::endl;
return -1;
}
Double_t c0 = -1;
TNamed* c0Info = dynamic_cast<TNamed*>(fSigmaMap->Get("c0"));
if (!c0Info) {
std::cout << "Failed to extract c0 from file with sigma map!" << std::endl;
return -1;
}
TString c0String = c0Info->GetTitle();
c0 = c0String.Atof();
printf("Loaded parameter 0 for sigma: %f\n\n", c0);
if (plotPull)
std::cout << "Plotting pull..." << std::endl << std::endl;
else
std::cout << "Plotting delta'..." << std::endl << std::endl;
Long64_t nTreeEntries = tree->GetEntriesFast();
Double_t dEdx = 0.; // Measured dE/dx
Double_t dEdxExpected = 0.; // Expected dE/dx according to parametrisation
Double_t tanTheta = 0.; // Tangens of (local) theta at TPC inner wall
Double_t pTPC = 0.; // Momentum at TPC inner wall
UShort_t tpcSignalN = 0; // Number of clusters used for dEdx
UChar_t pidType = 0;
Int_t fMultiplicity = 0;
//Double_t phiPrime = 0;
// Only activate the branches of interest to save processing time
tree->SetBranchStatus("*", 0); // Disable all branches
tree->SetBranchStatus("pTPC", 1);
tree->SetBranchStatus("dEdx", 1);
tree->SetBranchStatus("dEdxExpected", 1);
tree->SetBranchStatus("tanTheta", 1);
tree->SetBranchStatus("tpcSignalN", 1);
tree->SetBranchStatus("pidType", 1);
//tree->SetBranchStatus("phiPrime", 1);
if (isNonPP)
tree->SetBranchStatus("fMultiplicity", 1);
tree->SetBranchAddress("dEdx", &dEdx);
tree->SetBranchAddress("dEdxExpected", &dEdxExpected);
tree->SetBranchAddress("tanTheta", &tanTheta);
tree->SetBranchAddress("tpcSignalN", &tpcSignalN);
tree->SetBranchAddress("pTPC", &pTPC);
tree->SetBranchAddress("pidType", &pidType);
//tree->SetBranchAddress("phiPrime", &phiPrime);
if (isNonPP)
tree->SetBranchAddress("fMultiplicity", &fMultiplicity);
// Output file
TDatime daTime;
TString savefileName = Form("%s%s_checkPullSigma_%04d_%02d_%02d__%02d_%02d.root", fileNameTree.ReplaceAll(".root", "").Data(),
recalculateExpecteddEdx ? "_recalcdEdx" : "",
daTime.GetYear(), daTime.GetMonth(), daTime.GetDay(), daTime.GetHour(), daTime.GetMinute());
TFile* fSave = TFile::Open(Form("%s/%s", pathTree.Data(), savefileName.Data()), "recreate");
if (!fSave) {
std::cout << "Failed to open save file \"" << Form("%s/%s", pathTree.Data(), savefileName.Data()) << "\"!" << std::endl;
return -1;
}
const Double_t pBoundLow = 0.1;
const Double_t pBoundUp = 5;
const Int_t nBins1 = TMath::Ceil(180 / downScaleFactor);
const Int_t nBins2 = TMath::Ceil(100 / downScaleFactor);
const Int_t nBins3 = TMath::Ceil(60 / downScaleFactor);
const Int_t nPbinsForMap = nBins1 + nBins2 + nBins3;
Double_t binsPforMap[nPbinsForMap + 1];
Double_t binWidth1 = (1.0 - pBoundLow) / nBins1;
Double_t binWidth2 = (2.0 - 1.0 ) / nBins2;
Double_t binWidth3 = (pBoundUp - 2.0) / nBins3;
for (Int_t i = 0; i < nBins1; i++) {
binsPforMap[i] = pBoundLow + i * binWidth1;
}
for (Int_t i = nBins1, j = 0; i < nBins1 + nBins2; i++, j++) {
binsPforMap[i] = 1.0 + j * binWidth2;
}
for (Int_t i = nBins1 + nBins2, j = 0; i < nBins1 + nBins2 + nBins3; i++, j++) {
binsPforMap[i] = 2.0 + j * binWidth3;
}
binsPforMap[nPbinsForMap] = pBoundUp;
TH2D* hPull = new TH2D("hPull", "Pull vs. p_{TPC} integrated over tan(#Theta);p_{TPC} (GeV/c);Pull", nPbinsForMap, binsPforMap,
plotPull ? 120 : 240, plotPull ? -6 : -0.6, plotPull ? 6 : 0.6);
TH2D* hPullAdditionalCorr = (TH2D*)hPull->Clone("hPullAdditionalCorr");
hPullAdditionalCorr->SetTitle("Pull vs. p_{TPC} integrated over tan(#Theta) with additional dEdx correction w.r.t. tan(#Theta)");
/*
const Int_t nThetaHistos = 3;
TH2D* hPullTheta[nThetaHistos];
TH2D* hPullAdditionalCorrTheta[nThetaHistos];
Double_t tThetaLow[nThetaHistos] = { 0.0, 0.4, 0.9 };
Double_t tThetaHigh[nThetaHistos] = { 0.1, 0.5, 1.0 };
*/
const Int_t nThetaHistos = 10;
TH2D* hPullTheta[nThetaHistos];
TH2D* hPullAdditionalCorrTheta[nThetaHistos];
Double_t tThetaLow[nThetaHistos] = { 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 };
Double_t tThetaHigh[nThetaHistos] = { 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0 };
for (Int_t i = 0; i < nThetaHistos; i++) {
hPullTheta[i] = new TH2D(Form("hPullTheta_%d", i),
Form("Pull vs. p_{TPC} for %.2f <= |tan(#Theta)| < %.2f;p_{TPC} (GeV/c);Pull", tThetaLow[i], tThetaHigh[i]),
nPbinsForMap, binsPforMap, plotPull ? 120 : 240, plotPull ? -6 : -0.6, plotPull ? 6 : 0.6);
hPullAdditionalCorrTheta[i] =
new TH2D(Form("hPullAdditionalCorrTheta_%d", i),
Form("Pull vs. p_{TPC} for %.2f <= |tan(#Theta)| < %.2f with additional dEdx correction w.r.t. tan(#Theta);p_{TPC} (GeV/c);Pull",
tThetaLow[i], tThetaHigh[i]),
nPbinsForMap, binsPforMap, plotPull ? 120 : 240, plotPull ? -6 : -0.6, plotPull ? 6 : 0.6);
}
TF1 corrFuncMult("corrFuncMult", "[0] + [1]*TMath::Max([4], TMath::Min(x, [3])) + [2] * TMath::Power(TMath::Max([4], TMath::Min(x, [3])), 2)",
0., 0.2);
TF1 corrFuncMultTanTheta("corrFuncMultTanTheta", "[0] * (x -[2]) + [1] * (x * x - [2] * [2])", -1.5, 1.5);
TF1 corrFuncSigmaMult("corrFuncSigmaMul", "TMath::Max(0, [0] + [1]*TMath::Min(x, [3]) + [2] * TMath::Power(TMath::Min(x, [3]), 2))", 0., 0.2);
// LHC13b.pass2
if (isNonPP)
printf("Using corr Parameters for 13b.pass2\n!");
corrFuncMult.SetParameter(0, -5.906e-06);
corrFuncMult.SetParameter(1, -5.064e-04);
corrFuncMult.SetParameter(2, -3.521e-02);
corrFuncMult.SetParameter(3, 2.469e-02);
corrFuncMult.SetParameter(4, 0);
corrFuncMultTanTheta.SetParameter(0, -5.32e-06);
corrFuncMultTanTheta.SetParameter(1, 1.177e-05);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, 0.);
corrFuncSigmaMult.SetParameter(1, 0.);
corrFuncSigmaMult.SetParameter(2, 0.);
corrFuncSigmaMult.SetParameter(3, 0.);
/* OK, but PID task was not very satisfying
corrFuncMult.SetParameter(0, -6.27187e-06);
corrFuncMult.SetParameter(1, -4.60649e-04);
corrFuncMult.SetParameter(2, -4.26450e-02);
corrFuncMult.SetParameter(3, 2.40590e-02);
corrFuncMult.SetParameter(4, 0);
corrFuncMultTanTheta.SetParameter(0, -5.338e-06);
corrFuncMultTanTheta.SetParameter(1, 1.220e-05);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, 7.89237e-05);
corrFuncSigmaMult.SetParameter(1, -1.30662e-02);
corrFuncSigmaMult.SetParameter(2, 8.91548e-01);
corrFuncSigmaMult.SetParameter(3, 1.47931e-02);
*/
/*
// LHC11a10a
if (isNonPP)
printf("Using corr Parameters for 11a10a\n!");
corrFuncMult.SetParameter(0, 6.90133e-06);
corrFuncMult.SetParameter(1, -1.22123e-03);
corrFuncMult.SetParameter(2, 1.80220e-02);
corrFuncMult.SetParameter(3, 0.1);
corrFuncMult.SetParameter(4, 6.45306e-03);
corrFuncMultTanTheta.SetParameter(0, -2.85505e-07);
corrFuncMultTanTheta.SetParameter(1, -1.31911e-06);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, -4.29665e-05);
corrFuncSigmaMult.SetParameter(1, 1.37023e-02);
corrFuncSigmaMult.SetParameter(2, -6.36337e-01);
corrFuncSigmaMult.SetParameter(3, 1.13479e-02);
*/
/* OLD without saturation and large error for negative slopes
corrFuncSigmaMult.SetParameter(0, -4.79684e-05);
corrFuncSigmaMult.SetParameter(1, 1.49938e-02);
corrFuncSigmaMult.SetParameter(2, -7.15269e-01);
corrFuncSigmaMult.SetParameter(3, 1.06855e-02);
*/
/* OLD very good try, but with fewer pBins for the fitting
corrFuncMult.SetParameter(0, 6.88365e-06);
corrFuncMult.SetParameter(1, -1.22324e-03);
corrFuncMult.SetParameter(2, 1.81625e-02);
corrFuncMult.SetParameter(3, 0.1);
corrFuncMult.SetParameter(4, 6.36890e-03);
corrFuncMultTanTheta.SetParameter(0, -2.85505e-07);
corrFuncMultTanTheta.SetParameter(1, -1.31911e-06);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, -4.28401e-05);
corrFuncSigmaMult.SetParameter(1, 1.24812e-02);
corrFuncSigmaMult.SetParameter(2, -5.28531e-01);
corrFuncSigmaMult.SetParameter(3, 1.25147e-02);
*/
/*OLD good try
corrFuncMult.SetParameter(0, 7.50321e-06);
corrFuncMult.SetParameter(1, -1.25250e-03);
corrFuncMult.SetParameter(2, 1.85437e-02);
corrFuncMult.SetParameter(3, 0.1);
corrFuncMult.SetParameter(4, 6.21192e-03);
corrFuncMultTanTheta.SetParameter(0, -1.43112e-07);
corrFuncMultTanTheta.SetParameter(1, -1.53e-06);
corrFuncMultTanTheta.SetParameter(2, 0.3);
corrFuncSigmaMult.SetParameter(0, -2.54019e-05);
corrFuncSigmaMult.SetParameter(1, 8.68883e-03);
corrFuncSigmaMult.SetParameter(2, -3.36176e-01);
corrFuncSigmaMult.SetParameter(3, 1.29230e-02);
*/
/*
// LHC10h.pass2
if (isNonPP)
printf("Using corr Parameters for 10h.pass2\n!");
corrFuncMult.SetParameter(0, 3.21636e-07);
corrFuncMult.SetParameter(1, -6.65876e-04);
corrFuncMult.SetParameter(2, 1.28786e-03);
corrFuncMult.SetParameter(3, 1.47677e-02);
corrFuncMult.SetParameter(4, 0.);
corrFuncMultTanTheta.SetParameter(0, 7.23591e-08);
corrFuncMultTanTheta.SetParameter(1, 2.7469e-06);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, -1.22590e-05);
corrFuncSigmaMult.SetParameter(1, 6.88888e-03);
corrFuncSigmaMult.SetParameter(2, -3.20788e-01);
corrFuncSigmaMult.SetParameter(3, 1.07345e-02);
*/
/*OLD bad try
corrFuncMult.SetParameter(0, 2.71514e-07);
corrFuncMult.SetParameter(1, -6.92031e-04);
corrFuncMult.SetParameter(2, 3.56042e-03);
corrFuncMult.SetParameter(3, 1.47497e-02);
corrFuncMult.SetParameter(4, 0.);
corrFuncMultTanTheta.SetParameter(0, 8.53204e-08);
corrFuncMultTanTheta.SetParameter(1, 2.85591e-06);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, -6.82477e-06);
corrFuncSigmaMult.SetParameter(1, 4.97051e-03);
corrFuncSigmaMult.SetParameter(2, -1.64954e-01);
corrFuncSigmaMult.SetParameter(3, 9.21061e-03);
*/
//TODO NOW
TF1* fShapeSmallP = new TF1("fShapeSmallP", "pol5", -0.4, 0.4);
fShapeSmallP->SetParameters(1.01712, -0.0202725, -0.260692, 0.261623, 0.671854, -1.14014);
for (Long64_t i = 0; i < nTreeEntries; i++) {
tree->GetEntry(i);
if (dEdx <= 0 || dEdxExpected <= 0 || tpcSignalN <= 10)
continue;
/*
Double_t pT = pTPC*TMath::Sin(-TMath::ATan(tanTheta)+TMath::Pi()/2.0);
if ((phiPrime > 0.072/pT+TMath::Pi()/18.0-0.035 && phiPrime < 0.07/pT/pT+0.1/pT+TMath::Pi()/18.0+0.035))
continue;
*/
if (pidType != kMCid) {
if (pidType == kTPCid && pTPC > 0.6)
continue;
if (pidType == kTPCandTOFid && (pTPC < 0.6 || pTPC > 2.0))
continue;
if ((collType == 2) && pidType == kTPCandTOFid && pTPC > 1.0)
continue;// Only V0's in case of PbPb above 1.0 GeV/c
if (pidType == kV0idPlusTOFrejected) //TODO NOW NEW
continue;
}
if (recalculateExpecteddEdx) {
dEdxExpected = 50. * splPr->Eval(pTPC / massProton); //WARNING: What, if MIP is different from 50.? Seems not to be used (tested for pp, MC_pp, PbPb and MC_PbPb), but can in principle happen
}
//TODO NOW
/*
if (TMath::Abs(tanTheta) <= 0.4) {
Double_t p0 = fShapeSmallP->Eval(tanTheta) - 1.0; // Strength of the correction
Double_t p1 = -9.0; // How fast the correction is turned off
Double_t p2 = -0.209; // Turn off correction around 0.2 GeV/c
Double_t p3 = 1.0; // Delta' for large p should be 1
Double_t corrFactor = TMath::Erf((pTPC + p2) * p1) * p0 + p3 + p0; // Add p0 to have 1 for p3 = 1 and large pTPC
dEdxExpected *= corrFactor;
}*/
/*TODO old unsuccessful try
Double_t thetaGlobalTPC = -TMath::ATan(tanTheta) + TMath::Pi() / 2.;
Double_t pTtpc = pTPC * TMath::Sin(thetaGlobalTPC);
Double_t pTtpcInv = (pTtpc > 0) ? 1. / pTtpc : 0;
Double_t p0 = 1.0;
Double_t p1 = 1./ 0.5;//TODO 2.0;
Double_t p2 = -0.2;//TODO 0.1
Double_t pTcorrFactor = p0 + (pTtpcInv > p1) * p2 * (pTtpcInv - p1);
dEdxExpected *= pTcorrFactor;
*/
// From the momentum (via dEdxExpected) and the tanTheta of the track, the expected dEdx can be calculated (correctedDeDxExpected).
// If the splines are correct, this should give in average the same value as dEdx.
// Now valid: Maps created from corrected data with splines adopted to corrected data, so lookup should be for dEdxExpected=dEdxSplines (no further
// eta correction) or the corrected dEdx from the track (which should ideally be = dEdxSplines)
// Tested with corrected data for LHC10d.pass2: using dEdx for the lookup (which is the corrected value and should ideally be = dEdxSplines):
// Results almost the same. Maybe slightly better for dEdxExpected.
// No longer valid: Note that the maps take always the uncorrected dEdx w.r.t.
// tanTheta, so that correctedDeDxExpected is needed here normally. However, the information for the correction will be lost at some point.
// Therefore, dEdxExpected can be used instead and should provide a good approximation.
Double_t c1FromSigmaMap = hThetaMapSigmaPar1->GetBinContent(getBinX(hThetaMapSigmaPar1, tanTheta), getBinY(hThetaMapSigmaPar1, 1./dEdxExpected));
Double_t expectedSigma = dEdxExpected * TMath::Sqrt( c0 * c0 + (c1FromSigmaMap * c1FromSigmaMap) / tpcSignalN);
Double_t pull = (dEdx - dEdxExpected) / (plotPull ? expectedSigma: dEdxExpected);
// Fill pull histo
hPull->Fill(pTPC, pull);
Double_t tanThetaAbs = TMath::Abs(tanTheta);
for (Int_t j = 0; j < nThetaHistos; j++) {
if (tanThetaAbs >= tThetaLow[j] && tanThetaAbs < tThetaHigh[j]) {
hPullTheta[j]->Fill(pTPC, pull);
}
}
if (!hMap)
continue;
Double_t correctionFactor = 1.;
if (isNonPP) {
// 1. Correct eta dependence
correctionFactor = hMap->GetBinContent(getBinX(hMap, tanTheta), getBinY(hMap, 1./dEdxExpected));
// 2. Correct for multiplicity dependence:
Double_t multCorrectionFactor = 1.;
if (fMultiplicity > 0) {
Double_t relSlope = corrFuncMult.Eval(1. / (dEdxExpected * correctionFactor));
relSlope += corrFuncMultTanTheta.Eval(tanTheta);
multCorrectionFactor = 1. + relSlope * fMultiplicity;
}
c1FromSigmaMap = hThetaMapSigmaPar1->GetBinContent(getBinX(hThetaMapSigmaPar1, tanTheta), getBinY(hThetaMapSigmaPar1, 1./dEdxExpected));
// Multiplicity dependence of sigma depends on the real dEdx at zero multiplicity, i.e. the eta (only) corrected dEdxExpected value has to be used
// since all maps etc. have been created for ~zero multiplicity
Double_t relSigmaSlope = corrFuncSigmaMult.Eval(1. / (dEdxExpected * correctionFactor));
Double_t multSigmaCorrectionFactor = 1. + relSigmaSlope * fMultiplicity;
dEdxExpected *= correctionFactor * multCorrectionFactor;
expectedSigma = dEdxExpected * TMath::Sqrt( c0 * c0 + (c1FromSigmaMap * c1FromSigmaMap) / tpcSignalN);
expectedSigma *= multSigmaCorrectionFactor;
pull = (dEdx - dEdxExpected) / (plotPull ? expectedSigma: dEdxExpected);
}
else {
correctionFactor = hMap->GetBinContent(getBinX(hMap, tanTheta), getBinY(hMap, 1./dEdxExpected));
c1FromSigmaMap = hThetaMapSigmaPar1->GetBinContent(getBinX(hThetaMapSigmaPar1, tanTheta), getBinY(hThetaMapSigmaPar1, 1./dEdxExpected));
dEdxExpected *= correctionFactor; // If data is not corrected, but the sigma map is for corrected data, re-do analysis with corrected dEdx
expectedSigma = dEdxExpected * TMath::Sqrt( c0 * c0 + (c1FromSigmaMap * c1FromSigmaMap) / tpcSignalN);
pull = (dEdx - dEdxExpected) / (plotPull ? expectedSigma: dEdxExpected);
}
pull = (dEdx - dEdxExpected) / (plotPull ? expectedSigma: dEdxExpected);
hPullAdditionalCorr->Fill(pTPC, pull);
for (Int_t j = 0; j < nThetaHistos; j++) {
if (tanThetaAbs >= tThetaLow[j] && tanThetaAbs < tThetaHigh[j]) {
hPullAdditionalCorrTheta[j]->Fill(pTPC, pull);
}
}
}
/*
// Mean, Sigma, chi^2/NDF of pull of different theta bins and all in one plot
TCanvas* canvPullMean = new TCanvas("canvPullMean", "canvPullMean", 100,10,1380,800);
canvPullMean->SetLogx(kTRUE);
canvPullMean->SetGridx(kTRUE);
canvPullMean->SetGridy(kTRUE);
TCanvas* canvPullSigma = new TCanvas("canvPullSigma", "canvPullSigma", 100,10,1380,800);
canvPullSigma->SetLogx(kTRUE);
canvPullSigma->SetGridx(kTRUE);
canvPullSigma->SetGridy(kTRUE);
TCanvas* canvPullChi2 = new TCanvas("canvPullChi2", "canvPullChi2", 100,10,1380,800);
canvPullChi2->SetLogx(kTRUE);
canvPullChi2->SetGridx(kTRUE);
canvPullChi2->SetGridy(kTRUE);
TCanvas* canvPull[nThetaHistos + 1];
for (Int_t i = 0, j = nThetaHistos; i < nThetaHistos + 1; i++, j--) {
canvPull[i] = new TCanvas(Form("canvPull_%d", i), "canvPull", 100,10,1380,800);
canvPull[i]->cd();
canvPull[i]->SetLogx(kTRUE);
canvPull[i]->SetLogz(kTRUE);
canvPull[i]->SetGrid(kTRUE, kTRUE);
TH2D* hTemp = 0x0;
TString thetaString = "";
if (i == nThetaHistos) {
hTemp = hPull;
thetaString = "tan(#Theta) integrated";
}
else {
hTemp = hPullTheta[i];
thetaString = Form("%.2f #leq |tan(#Theta)| < %.2f", tThetaLow[i], tThetaHigh[i]);
}
normaliseHisto(hTemp);
hTemp->FitSlicesY();
hTemp->GetYaxis()->SetNdivisions(12);
hTemp->GetXaxis()->SetMoreLogLabels(kTRUE);
TH1D* hTempMean = (TH1D*)gDirectory->Get(Form("%s_1", hTemp->GetName()));
hTempMean->SetTitle(Form("mean(pull), %s", thetaString.Data()));
hTempMean->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempMean->SetLineWidth(2);
hTempMean->SetMarkerStyle(20);
TH1D* hTempSigma = (TH1D*)gDirectory->Get(Form("%s_2", hTemp->GetName()));
hTempSigma->SetTitle(Form("#sigma(pull), %s", thetaString.Data()));
hTempSigma->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempSigma->SetLineColor(kMagenta);
hTempSigma->SetMarkerStyle(20);
hTempSigma->SetMarkerColor(kMagenta);
hTempSigma->SetLineWidth(2);
TH1D* hTempChi2 = (TH1D*)gDirectory->Get(Form("%s_chi2", hTemp->GetName()));
hTempChi2->SetTitle(Form("#chi^{2} / NDF (pull), %s", thetaString.Data()));
hTempChi2->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempChi2->SetLineColor(kMagenta + 2);
hTempChi2->SetMarkerStyle(20);
hTempChi2->SetMarkerColor(kMagenta + 2);
hTempChi2->SetLineWidth(2);
hTemp->DrawCopy("colz");
hTempMean->DrawCopy("same");
hTempSigma->DrawCopy("same");
hTempChi2->Scale(-1./10.);
hTempChi2->DrawCopy("same");
hTempChi2->Scale(-10.);
canvPullMean->cd();
hTempMean->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempMean->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempMean->DrawCopy((i == 0 ? "" : "same"));
canvPullSigma->cd();
hTempSigma->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempSigma->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempSigma->DrawCopy((i == 0 ? "" : "same"));
canvPullChi2->cd();
hTempChi2->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempChi2->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempChi2->DrawCopy((i == 0 ? "" : "same"));
}
canvPullMean->BuildLegend();
canvPullSigma->BuildLegend();
canvPullChi2->BuildLegend();
*/
// Histograms with additional correction
TCanvas* canvPullMeanCorr = 0x0;
TCanvas* canvPullSigmaCorr = 0x0;
TCanvas* canvPullChi2Corr = 0x0;
TCanvas* canvPullCorr[nThetaHistos + 1];
for (Int_t i = 0; i < nThetaHistos + 1; i++)
canvPullCorr[i] = 0x0;
if (hMap) {
// Mean, Sigma, chi^2/NDF of pull of different theta bins and all in one plot
canvPullMeanCorr = new TCanvas("canvPullMeanCorr", "canvPullMeanCorr", 100,10,1380,800);
canvPullMeanCorr->SetLogx(kTRUE);
canvPullMeanCorr->SetGridx(kTRUE);
canvPullMeanCorr->SetGridy(kTRUE);
canvPullSigmaCorr = new TCanvas("canvPullSigmaCorr", "canvPullSigmaCorr", 100,10,1380,800);
canvPullSigmaCorr->SetLogx(kTRUE);
canvPullSigmaCorr->SetGridx(kTRUE);
canvPullSigmaCorr->SetGridy(kTRUE);
canvPullChi2Corr = new TCanvas("canvPullChi2Corr", "canvPullChi2Corr", 100,10,1380,800);
canvPullChi2Corr->SetLogx(kTRUE);
canvPullChi2Corr->SetGridx(kTRUE);
canvPullChi2Corr->SetGridy(kTRUE);
for (Int_t i = 0, j = nThetaHistos; i < nThetaHistos + 1; i++, j--) {
canvPullCorr[i] = new TCanvas(Form("canvPullCorr_%d", i), "canvPullCorr", 100,10,1380,800);
canvPullCorr[i]->cd();
canvPullCorr[i]->SetLogx(kTRUE);
canvPullCorr[i]->SetLogz(kTRUE);
canvPullCorr[i]->SetGrid(kTRUE, kTRUE);
TH2D* hTemp = 0x0;
TString thetaString = "";
if (i == nThetaHistos) {
hTemp = hPullAdditionalCorr;
thetaString = "tan(#Theta) integrated";
}
else {
hTemp = hPullAdditionalCorrTheta[i];
thetaString = Form("%.2f #leq |tan(#Theta)| < %.2f", tThetaLow[i], tThetaHigh[i]);
}
normaliseHisto(hTemp);
hTemp->FitSlicesY();
hTemp->GetYaxis()->SetNdivisions(12);
hTemp->GetXaxis()->SetMoreLogLabels(kTRUE);
TH1D* hTempMean = (TH1D*)gDirectory->Get(Form("%s_1", hTemp->GetName()));
hTempMean->SetTitle(Form("mean(pull), %s", thetaString.Data()));
hTempMean->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempMean->SetLineWidth(2);
hTempMean->SetMarkerStyle(20);
TH1D* hTempSigma = (TH1D*)gDirectory->Get(Form("%s_2", hTemp->GetName()));
hTempSigma->SetTitle(Form("#sigma(pull), %s", thetaString.Data()));
hTempSigma->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempSigma->SetLineColor(kMagenta);
hTempSigma->SetMarkerStyle(20);
hTempSigma->SetMarkerColor(kMagenta);
hTempSigma->SetLineWidth(2);
TH1D* hTempChi2 = (TH1D*)gDirectory->Get(Form("%s_chi2", hTemp->GetName()));
hTempChi2->SetTitle(Form("#chi^{2} / NDF (pull), %s", thetaString.Data()));
hTempChi2->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempChi2->SetLineColor(kMagenta + 2);
hTempChi2->SetMarkerStyle(20);
hTempChi2->SetMarkerColor(kMagenta + 2);
hTempChi2->SetLineWidth(2);
hTemp->DrawCopy("colz");
hTempMean->DrawCopy("same");
hTempSigma->DrawCopy("same");
hTempChi2->Scale(-1./10.);
hTempChi2->DrawCopy("same");
hTempChi2->Scale(-10.);
canvPullMeanCorr->cd();
hTempMean->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempMean->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempMean->DrawCopy((i == 0 ? "" : "same"));
canvPullSigmaCorr->cd();
hTempSigma->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempSigma->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempSigma->DrawCopy((i == 0 ? "" : "same"));
canvPullChi2Corr->cd();
hTempChi2->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempChi2->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempChi2->DrawCopy((i == 0 ? "" : "same"));
}
canvPullMeanCorr->BuildLegend();
canvPullSigmaCorr->BuildLegend();
canvPullChi2Corr->BuildLegend();
}
fSave->cd();
/*canvPullMean->Write();
canvPullSigma->Write();
canvPullChi2->Write();
for (Int_t i = 0; i < nThetaHistos + 1; i++) {
canvPull[i]->Write();
}*/
canvPullMeanCorr->Write();
canvPullSigmaCorr->Write();
canvPullChi2Corr->Write();
for (Int_t i = 0; i < nThetaHistos + 1; i++) {
canvPullCorr[i]->Write();
}
TNamed* info = new TNamed(Form("Theta map: %s\n\nSigma map: %s\n\nSplines file: %s\n\nSplines name: %s", pathNameThetaMap.Data(),
pathNameSigmaMap.Data(), pathNameSplinesFile.Data(), prSplinesName.Data()),
"info");
info->Write();
fSave->Close();
return 0;
}
void makePlots (string configFilePath){
if (( inputRootFileNum.size() > 0 ))
{
for (int i=0; i<numHistos; i++)
{
double y_max = 0.0;
TCanvas *c = new TCanvas(theHistNameStrings.at(i).c_str(), "", 81,58,500,602);
TH1* h_num; // histograms for Numerator
TH1* h_den; // histohrams for Denominator
int whichHisto = 0;
TMultiGraph *mg = new TMultiGraph();
for (int j=0;j<inputRootFileNum.size();j++)
{
whichHisto=j*numHistos;
int a = 0;
bool foundHisto = false;
if (theHistNameStrings.at(i) == theHistNameStrings.at(i+whichHisto))
{
foundHisto=true;
a=i;
}
else
{
for (a = 0; a < numHistos; a++)
{
if (theHistNameStrings.at(i) == theHistNameStrings.at(a+whichHisto))
{
foundHisto = true;
break;
}
}
}
//-----------------------------------------------------------
string hist2name = listHistosNum->At(a+whichHisto)->GetName();
if (foundHisto == true)
{
h_num = (TH1*)listHistosNum->At(i+whichHisto);
h_den = (TH1*)listHistosDen->At(a+whichHisto);
TH1F* H_bins_num;
TH1F* H_bins_den;
int id = 0;
for (int k = 0; k < inputXtitle.size(); k++)
{
if (hist2name == inputHistoName.at(k)){
id=k;
}
}
if (inputdifferentBinSize.at(id)==1){
int Nbins = h_num->GetXaxis()->GetNbins();
int arrayD = (int*)inputNbins.at(id);
float *BINS = new float [arrayD];
for (int b = 0; b <= arrayD; b++ )
{
if (b < (arrayD-1))
{
BINS[b] = (float)b*(h_num->GetXaxis()->GetBinWidth(b));
}
else {
BINS[b] = (float)inputBinSize.at(id);
}
}
H_bins_num = new TH1F("h_NUM", "h_NUM", inputNbinMax.at(id), BINS);
H_bins_den = new TH1F("h_DEN", "h_DEN", inputNbinMax.at(id), BINS);
for (int b = 0; b <= (Nbins+1); b++ )
{
H_bins_num->SetBinContent(b, h_num->GetBinContent(b));
H_bins_den->SetBinContent(b, h_den->GetBinContent(b));
}
}
if (inputdifferentBinSize.at(id)==1){
TGraphAsymmErrors* gr1 = new TGraphAsymmErrors( H_bins_num, H_bins_den, "b(1,1) mode" );
} else{
cout << "h_num "<<h_num->GetXaxis()->GetNbins() << " h_den "<<h_den->GetXaxis()->GetNbins()<<endl;
cout << "h_num "<<h_num->Integral() << " h_den "<<h_den->Integral()<<endl;
TGraphAsymmErrors* gr1 = new TGraphAsymmErrors( h_num, h_den, "b(1,1) mode" );
}
int setcolor = inputColor.at(j);
int marker = inputMarkerStyle.at(j);
string processlegend = (inputLegend.at(j)).c_str();
gr1->SetMarkerStyle(marker);
gr1->SetMarkerColor(setcolor);
gr1->SetTitle(processlegend.c_str());
gr1->SetFillStyle(0);
mg->SetTitle(hist2name.c_str());
mg->Add(gr1);
}// close if (foundHisto)
c->cd();
c->SetGrid();
} // close for loop inputRootFile
mg->Draw("APsame");
for (int k = 0; k < inputXtitle.size(); k++)
{
if (hist2name == inputHistoName.at(k))
{
mg->GetXaxis()->SetTitle((inputXtitle.at(k)).c_str());
mg->GetYaxis()->SetTitle((inputYtitle.at(k)).c_str());
mg->GetXaxis()->SetTitleSize(0.05);
mg->GetYaxis()->SetTitleSize(0.05);
mg->SetMaximum((float)inputYrangeMax.at(k));
}
}
c->Update();
TLegend* legend = c->BuildLegend(0.55,0.8,0.90,0.94);
//TLegend *legend = new TLegend(0.2, 0.85-.035*inputLegend.size(), 0.5, 0.90,NULL,"brNDC");
legend->SetTextFont(42);
legend->SetLineColor(1);
legend->SetLineStyle(1);
legend->SetLineWidth(1);
legend->SetFillColor(0);
legend->SetFillStyle(1001);
legend->SetBorderSize(0);
legend->SetFillColor(kWhite);
TFile *hfile = (TFile*)gROOT->FindObject(HistosOutputRootFile.c_str());
if (hfile) {hfile->Close();}
hfile = new TFile(HistosOutputRootFile.c_str(),"UPDATE");
for (int o = 0; o < inputHistoName.size(); o++)
{
if ( c->GetName() == inputHistoName.at(o) )
{
string save = configFilePath+"/"+inputHistoName.at(o)+".pdf";
c->SaveAs(save.c_str());
c->Write();
break;
}
}
hfile->Close();
c->Close();
} // close foor loop numHistos
} // close if numHistos % inputRootFile.size() == 0
} // close makePlots function
void
Example(Bool_t fit=true)
{
// Load the class - if not already done
if (!gROOT->GetClass("GraphSysErr"))
gROOT->LoadMacro("GraphSysErr.C+g");
// Adjust size along X of common errors
gStyle->SetErrorX(.2);
// Adjust size of hat, cap, ... - depends on canvas size!
gStyle->SetEndErrorSize(10);
// Make our object
GraphSysErr* gse = new GraphSysErr("foo", "Gaussian");
// Draw data with-out ticks
gse->SetDataOption(GraphSysErr::kNoTick);
gse->SetXTitle("X");
gse->SetYTitle("Y");
// Set some key/value pairs
gse->SetKey("laboratory", "The Center");
gse->SetKey("accelerator", "Mega Collider");
gse->SetKey("detector", "Huge Experiment");
gse->SetKey("author", "Christensen");
gse->SetKey("reference","Jour.All.Things A1,999");
gse->SetKey("doi","9999-9999-9999-9999");
gse->SetKey("abstract", "The data");
gse->SetKey("location", "In the paper");
gse->SetKey("reackey", "graviton -> tachyons");
gse->SetKey("obskey", "GUT");
// Adding qualifiers
gse->AddQualifier("question", "Life, universe, and everything");
// Two sources of common errors one relative, one absolue
UInt_t cm1 = gse->DefineCommon("Common 0.05", false, .05);
UInt_t cm2 = gse->DefineCommon("Common 10%", true, .1);
// Two sources of point-to-point errors, one relative, one absolute
UInt_t pp1 = gse->DeclarePoint2Point("Point-to-Point 0.1-0.2", true);
UInt_t pp2 = gse->DeclarePoint2Point("Point-to-Point 5-10%", false);
// Set options on summed errors (in case of option COMBINED)
gse->SetSumLineColor(kRed+2);
gse->SetSumLineWidth(2);
gse->SetSumTitle("All errors");
gse->SetSumOption(GraphSysErr::kHat);
// Set attributes of common errors
gse->SetSysFillColor(cm1, kRed+2);
gse->SetSysFillStyle(cm1, 3001);
gse->SetSysLineColor(cm1, kRed+2);
gse->SetSysFillColor(cm2, kCyan+2);
gse->SetSysFillStyle(cm2, 3001);
gse->SetSysOption(cm1, GraphSysErr::kBox);
gse->SetSysOption(cm2, GraphSysErr::kRect);
// Set attributes of other errors
gse->SetSysLineColor(pp1, kBlue+2);
gse->SetSysLineWidth(pp1, 2);
gse->SetSysLineColor(pp2, kGreen+2);
gse->SetSysLineWidth(pp2, 3);
gse->SetSysOption(pp1, GraphSysErr::kBar);
gse->SetSysOption(pp2, GraphSysErr::kHat);
// Fill a histogram with a Guassian random deviate
TH1* h = new TH1F("h", "h", 30, -3, 3);
h->Sumw2();
h->SetDirectory(0);
h->FillRandom("gaus",1000);
h->Scale(1./1000, "width");
// Fill in the data points
for (Int_t i = 0; i < h->GetNbinsX(); i++) {
Int_t bin = i+1;
Double_t x = h->GetXaxis()->GetBinCenter(bin);
Double_t y = h->GetBinContent(bin);
Double_t sta = h->GetBinError(bin);
Double_t w = h->GetXaxis()->GetBinWidth(bin);
// Set data
gse->SetPoint(i, x, y);
gse->SetPointError(i, w/2, w/2);
gse->SetStatError(i, sta);
// Set point-to-point errors
gse->SetSysError(pp1, i, 0., gRandom->Uniform(0.1, 0.2));
gse->SetSysError(pp2, i, 0., 0.,
gRandom->Uniform(0.05, 0.1),
gRandom->Uniform(0.05, 0.1));
}
// Remove temporary histogram
delete h;
// Build our canvas
TCanvas* c = new TCanvas("c","c", 1400, 1000);
c->SetFillColor(0);
c->SetFillStyle(0);
c->SetTopMargin(0.01);
c->SetRightMargin(0.01);
// Draw or fit (and draw) a Guassian to the data
const char* option = "STACK stat axis quad split max west";
if (!fit)
gse->Draw(option);
else
gse->Fit("gaus", "SQ", option, -3, 3);
// Make a legend
TLegend* l = c->BuildLegend(0.7,0.7,0.97,0.97);
l->SetFillColor(0);
l->SetFillStyle(0);
l->SetBorderSize(0);
// update the canvas and print
c->Modified();
c->Update();
c->cd();
c->Print("Example.png");
}
void Interpolate(const TString& trigger="INEL")
{
if (gSystem->Getenv("FWD"))
fwd = gSystem->Getenv("FWD");
else
fwd = gSystem->ExpandPathName("$ALICE_PHYSICS/PWGLF/FORWARD/analysis2");
gROOT->SetMacroPath(Form("%s/dndeta:%s", gROOT->GetMacroPath(),fwd));
if (!gROOT->GetClass("Drawer")) gROOT->LoadMacro("Drawer.C+");
TH1* h0900 = GetOne( 900, trigger);
TH1* h2760 = GetOne(2760, trigger);
TH1* h7000 = GetOne(7000, trigger);
TH1* h8000 = GetOne(8000, trigger);
Info("","900: %p 2760: %p 7000: %p 8000: %p",
h0900, h2760, h7000, h8000);
Double_t e8000 = (trigger.EqualTo("INEL") ? 0.852 : 0.93);
h8000->Scale(e8000);
TFile* out = TFile::Open("trends.root", "RECREATE");
THStack* sOrig = new THStack("orig", Form("pp - %s", trigger.Data()));
sOrig->Add(h8000);
sOrig->Add(h7000);
sOrig->Add(h2760);
sOrig->Add(h0900);
TCanvas* cOrig = new TCanvas("cOrig", "Original", 1200, 1200);
cOrig->SetTopMargin(0.01);
cOrig->SetRightMargin(0.01);
sOrig->Draw("nostack");
sOrig->GetHistogram()->SetYTitle("1/#it{N} d#it{N}_{ch}/d#it{#eta}");
sOrig->GetHistogram()->SetXTitle("#it{#eta}");
sOrig->DrawClone("nostack");
sOrig->Write();
TLegend* l = cOrig->BuildLegend(.35, .2, .55, .6, "#sqrt{s}");
l->SetFillColor(0);
l->SetFillStyle(0);
l->SetBorderSize(0);
cOrig->Modified();
cOrig->Update();
cOrig->cd();
cOrig->Write();
Info("", "Wrote original");
TCanvas* cG = new TCanvas("cG", "one", 1200, 1200);
cG->SetTopMargin(0.01);
cG->SetRightMargin(0.01);
Info("","Creating tuple");
TNtuple* tuple = new TNtuple("tuple", "Tuple",
"eta:deta:"
"v0900:e0900:v2760:e2760:"
"v7000:e7000:v8000:e8000");
TMultiGraph* mg = new TMultiGraph;
Int_t n = h0900->GetNbinsX();
Info("","Loop over bins %d", n);
for (Int_t i = 1; i <= n; i++) {
Info("", "Getting one bin %d,%p,%p,%p,%p,%p,%p",
i, h0900,h2760,h7000,h8000,mg,tuple);
OneBin(i, h0900, h2760, h7000, h8000, mg, tuple);
}
mg->Draw("alp");
cG->Modified();
cG->Update();
cG->cd();
TPrincipal* p =tuple->Principal("v0900:v2760:v7000:v8000","eta<0", "npdhc");
}