/*
double residual_error( double error_data, double pdf )
{
double chi2 = 0.;
if ( pdf > 0 )
chi2 += 2. * ( pdf - error_data );
if ( error_data > 0 && pdf > 0 )
chi2=(error_data/pdf);
//chi2 += 2. * error_data * log( error_data / error_pdf );
// return ( ( error_data >= pdf ) ? sqrt( chi2 ) : -sqrt( chi2 ) );
// return ( ( error_data >= pdf ) ? chi2 : chi2 );
return ( chi2 );
}
*/
TH1D* residualHist( const RooHist* rhist, const RooCurve* curve )
{
double r = 0.2;
double sr = 1. / r;
// Grab info from the histogram.
int n = rhist->GetN();
double* x = rhist->GetX();
double* y = rhist->GetY();
//rhist->Sumw2();
// double e;
// Create residual histogram.
double xMin = x[ 0 ];
double xMax = x[ n - 1 ];
TH1D* residuals_temp = new TH1D( "r", "", n, xMin, xMax );
double datum = 0.;
double pdf = 0.;
double error_data = 0.;
// Fill the histogram.
if ( curve )
for ( int bin = 0; bin < n; bin++ )
{
datum = y[ bin ];
pdf = curve->Eval( x[ bin ] );
error_data = rhist->GetErrorY(bin);
// error_pdf = curve->Eval( x[ bin ] );
residuals_temp->SetBinContent( bin + 1, residual( datum, pdf ) );
// residuals_temp->SetBinError ( bin + 1, residual_error( error_data, pdf ) );
residuals_temp->SetBinError ( bin + 1, error_data / pdf );
}
residuals_temp->SetMinimum ( -2. );
residuals_temp->SetMaximum ( 2. );
residuals_temp->SetStats ( false );
residuals_temp->SetMarkerStyle( 8 );
residuals_temp->SetMarkerSize ( .8 );
TAxis* xAxis = residuals_temp->GetXaxis();
xAxis->SetTickLength ( sr * xAxis->GetTickLength() );
xAxis->SetLabelSize ( sr * xAxis->GetLabelSize() );
xAxis->SetTitleSize ( sr * xAxis->GetTitleSize() );
xAxis->SetLabelOffset( sr * xAxis->GetLabelOffset() );
TAxis* yAxis = residuals_temp->GetYaxis();
//yAxis->SetNdivisions ( 500 );
//yAxis->SetLabelSize ( 10*sr * yAxis->GetLabelSize() );
yAxis->SetLabelSize ( 2.5 * yAxis->GetLabelSize() );
yAxis->SetTitle(" (DATA - FIT) / FIT");
yAxis->SetTitleSize ( 0.09 );
yAxis->SetTitleOffset( 0.35 );
return residuals_temp;
}
THStack* DrawOne(TVirtualPad* p,
Double_t yr,
Bool_t top,
TDirectory* dir,
const char* name)
{
p->cd();
p->SetFillColor(0);
p->SetFillStyle(0);
p->SetLineColor(0);
p->SetRightMargin(0.01);
p->SetLeftMargin(0.12);
p->SetGridx();
if (top) p->SetBottomMargin(0.001);
else p->SetBottomMargin(0.2);
if (top) p->SetTopMargin(0.02);
else p->SetTopMargin(0.0001);
THStack* s = static_cast<THStack*>(dir->Get(name));
s->Draw("nostack");
Double_t sc = (top ? 1-yr : yr);
TAxis* ya = s->GetHistogram()->GetYaxis();
ya->SetLabelSize(1/sc*ya->GetLabelSize());
ya->SetTitleSize(1/sc*ya->GetTitleSize());
ya->SetTitleOffset(sc*(ya->GetTitleOffset()+.5));
ya->SetTitleFont(42);
ya->SetLabelFont(42);
TAxis* xa = s->GetHistogram()->GetXaxis();
xa->SetLabelSize(!top ? 1/yr*xa->GetLabelSize() : 0);
xa->SetTitleSize(!top ? 1/yr*xa->GetTitleSize() : 0);
xa->SetTitleOffset(yr*(xa->GetTitleOffset()+2));
xa->SetTitleFont(42);
xa->SetLabelFont(42);
p->Modified();
p->Update();
p->cd();
return s;
}
//using namespace std;
int main( int argc, char* argv[]) {
gROOT->ProcessLine("#include <vector>");
using namespace std;
int whichChan = 3; // which "FullCut" channel to look at -- 0 is MuMu, 1 is EE, 2 is EMu, 3 is all together
int whichNTuple = 1; //as with the plot making code, leave as 1 for now -- 0 is Oviedo, 1 is DESY
int whichTTbarGen = 0; // 0 is Madgraph, 1 is MC@NLO, 2 is Powheg
bool doExcSamps = 0; // For grabbing exclusive (DY + N Jets, TTBar Decay modes) or inclusive samples (As of 8/5/13, only applies to Oviedo)
bool calcTTBarNorm = 0; // calculate TTBar normalization by utilizing integral to data - (other backgrounds) for MT2ll < 80 in the "Full Cut region"
bool doNonSig = 0; // For whether or not to grab SM background and data
vector<int> * vecStopMassGrab = new vector<int>; // vector to hold the list of Stop masses to brab
vector<int> * vecChi0MassGrab = new vector<int>; // vector to hold the list of Chi0 masses to brab
vector<int> * vecCharginoMassGrab = new vector<int>; // vector to hold the list of Chargino masses to brab
bool doPURW = 0; // grab the nVtx reweighted MC files
bool doSyst = 1; // look at systematics plots
bool addThings = 1; // Add together similar kinds of events (for aesthetic reasons) like VV backgrounds -- (6/25/13) don't turn off for now haven't validated code fully when not adding
bool doReReco = 0;
bool doSymErr = 0;
bool saveDotCFile = 0; // If on, saves a .C version of every plot that is made
bool useDDEstimate = 0; // whether or not to use data-driven estimates for appropriate backgrounds -- as of right now it is just the TTBar norm to MT2ll < 80 GeV (7/22/13)
bool allMT2llSystematic = 0; // Whether or not to use the MT2ll systematic smearing for all MC or just TTBar
int versNumber = 1;
bool doVectorIndDists = 0;
bool makeRootCopy = 0;
float c_0d, c_0mc, c_1d, c_1mc;
for (int k = 0; k < argc; ++k) {
cout << "argv[k] for k = " << k << " is: " << argv[k] << endl;
if (strncmp (argv[k],"wChan", 5) == 0) {
whichChan = strtol(argv[k+1], NULL, 10 );
}
else if (strncmp (argv[k],"wNTuple", 7) == 0) {
whichNTuple = strtol(argv[k+1], NULL, 10 );
}
else if (strncmp (argv[k],"wTTbarGen", 9) == 0) {
whichTTbarGen = strtol(argv[k+1], NULL, 10 );
}
else if (strncmp (argv[k],"doExcSamps", 10) == 0) {
doExcSamps = 1;
}
else if (strncmp (argv[k],"versNum", 7) == 0) {
versNumber = strtol(argv[k+1], NULL, 10 );
}
else if (strncmp (argv[k],"doReReco", 8) == 0) {
doReReco = 1;
}
else if (strncmp (argv[k],"doNonSig", 8) == 0) {
doNonSig = 1;
}
else if (strncmp (argv[k],"sDCF", 4) == 0) {
saveDotCFile = 1;
}
else if (strncmp (argv[k],"doPURW", 6) == 0) {
doPURW = 1;
}
else if (strncmp (argv[k],"noSyst", 6) == 0) {
doSyst = 0;
}
else if (strncmp (argv[k],"noAdd", 5) == 0) {
addThings = 0;
}
else if (strncmp (argv[k],"calcTTBarNorm", 13) == 0) {
calcTTBarNorm = 1;
}
else if (strncmp (argv[k],"useDDEst", 8) == 0) {
useDDEstimate = 1;
}
else if (strncmp (argv[k],"allMT2ll", 8) == 0) {
allMT2llSystematic = 1;
}
}
TRint theApp("App", &argc, argv);
Bool_t retVal = kTRUE;
if (!doExcSamps && whichNTuple == 1 ) {
doExcSamps = true;
cout << "setting do Exclusive Samples to true because running on DESY" << endl;
}
//Set up the file input
// vector<TFile *> * inFiles = new vector<TFile*>;
vector<TString> * fileInNames = StopFileNames(whichNTuple, whichTTbarGen, doExcSamps, doReReco);
vector<TFile *> * inputFiles = StopFiles(whichNTuple, fileInNames, doExcSamps, whichTTbarGen, doPURW, doSyst, versNumber);
vector<TString> * sampleAddNames = new vector<TString>;
vector<int> * sampleStartPositions = new vector<int>;
sampleStartPositionsNames(whichNTuple, whichTTbarGen, sampleAddNames, sampleStartPositions, doExcSamps);
vector<TFile *> * inputFilesSignal;
vector<TString> * mcLegendsSignal;
vector<Color_t> * mcColorsSignal;
vector<Style_t> * mcStylesSignal;
vector<SampleT> * subSampVec = SubSampVec();
cout << "subsamp size " << subSampVec->size() << endl;
vector<SystT> * systVec = SystVec();
//some relevant things for saving names
TString TTBarGenName[3] = {"_madgraph", "_mcatnlo", "_powheg"};
TString nameNTuple = (whichNTuple == 0) ? "_Ovi" : "_DESY";
TString stringDDEstimate = (useDDEstimate) ? "_wDDEst" : "";
TString stringExcSamp = (doExcSamps && whichNTuple == 0) ? "_ExcSamps" : "";
TString stringSignal = "";
TString canvSuffixSaveName = TTBarGenName[whichTTbarGen];
canvSuffixSaveName += nameNTuple;
canvSuffixSaveName += stringDDEstimate;
canvSuffixSaveName += stringExcSamp;
canvSuffixSaveName += stringSignal;
if (doReReco) canvSuffixSaveName += "_ReReco";
if (versNumber == 2) canvSuffixSaveName += "_vers2";
cout << "canvSave name " << canvSuffixSaveName << endl;
TString saveNameAddition("../Plots/");
///Systematics stuff////
vector<TH1F *> * dataHist1DVec;
TH1F * h_DataComp, * h_MCComp;
vector<TH1 *> * dataHistTH1Vec;
vector<TH1 *> * mcHistTH1Vec;
vector<TH1 *> * mcHistSystTH1Vec;
vector<TH1F *> * mcIndHist1DCentValVec; //will contain central value histos for individual MC samples
vector<TH1F *> * mcCompHist1DCentValVec; //will contain the added histos for general categories
vector<TH1F *> * mcCompHist1DSystVec; //will contain the added histos across all MC for given systematic
TLegend * leg;
TLatex * tl = new TLatex();
tl->SetTextAlign(12);
tl->SetNDC();
tl->SetTextSize(0.03);
char buf[99];
TAxis * YAxis;
TAxis * XAxis;
Option_t * FitOption = "IS";
float FitLowRange = 2;
float FitHighRange = 25;
vector<float> * nVtxBackScaleVec = ScaleBackVecCalc(inputFiles);
vector<TGraphAsymmErrors *> * errCompSpecSource; // will contain just the systematic error for each specific source -- note, will contain errSystQuadSum as a final dude
vector<TGraphAsymmErrors *> * errCompSpecSource_pStat; // for each specific source, will contain Stat + respective systematic error -- note, will contain errSystQuadSum_pStat as a final dude
vector<TString> * systCanvNameVec;
vector<TGraphAsymmErrors *> * fracRatioSystVec;
TH1 * currSignalCentValTH1Hist;
vector<TH1 *> * vecCurrSignalSystTH1Hists;
TH1F * currSignal1DCentValHist;
vector<TH1F *> * vecCurrStop1DSystHists;
vector<TGraphAsymmErrors *> * vecCurrSigCompSpecSource, * vecCurrSigCompSpecSource_pStat;
///Data-Driven systematics stuff
float TTBarFullCutSFOviReReco[3] = {1.01276, 0.933961, 1.03732};
float TTBarFullCutSFOvi[3] = {0.946965, 0.873284, 0.969927};
float TTBarFullCutSFDESY[3] = {0.84936, 0.843207, 0.949907};
if (!doExcSamps) {
TTBarFullCutSFOvi[0] = 0.891653;
TTBarFullCutSFOviReReco[0] = 0.953711;
}
float TTBarSF, TTBarSF_Other;
if (whichNTuple == 0) {
if (doReReco) {
TTBarSF = TTBarFullCutSFOviReReco[whichTTbarGen];
}
else {
TTBarSF = TTBarFullCutSFOvi[whichTTbarGen];
}
}
else {
TTBarSF = TTBarFullCutSFDESY[whichTTbarGen];
}
if (useDDEstimate) {
cout << "TTBarSF used " << TTBarSF;
}
//plotting stuff
float intLumi;
float indLumiDESY[4] = {892, 4404, 7032, 7274};
float indLumiOvi[4] = {892, 4404, 7032, 7274};
// intLumi = 19602.901;
float indLumiOviReReco[4] = {876, 4404, 7016, 7360};
float nominalLumi = indLumiOviReReco[0] + indLumiOviReReco[1] + indLumiOviReReco[2] + indLumiOviReReco[3];
if (whichNTuple == 0) {
if (!doReReco) {
intLumi = indLumiOvi[0] + indLumiOvi[1] + indLumiOvi[2] + indLumiOvi[3];
}
else {
intLumi = indLumiOviReReco[0] + indLumiOviReReco[1] + indLumiOviReReco[2] + indLumiOviReReco[3];
}
}
else {
intLumi = indLumiDESY[0] + indLumiDESY[1] + indLumiDESY[2] + indLumiDESY[3];
}
float scaleLumi = intLumi / nominalLumi;
TString plotGrabBaseName = "h_PassMT2llCut";
TString plotGrabName;
TString plotSystGrabName;
TString plotVarName, subSampName;;
TString dataLegendComp = "Data";
float fracRatioYAxisRange = 0.21;
int grabChan[7] = {0, 17, 34, 1, 18, 35, 55};
TString canvNameBase = "h_METX_vs_nVtx_noPhiCorr", canvName;
TString canvNameAdd[7] = {"_mumu", "_ee", "_emu", "_mumuZVeto", "_eeZVeto", "_emuZVeto", "_inclusive"};
plotGrabBaseName = "h_METX_vs_nVtx_noPhiCorr";
TCanvas * c_Var;
TH2F * DataComp, * MCComp;
TH1F * DataMean, * MCMean;
TF1 * f1_resp_Lin = new TF1("fb_Lin","[0] + x*[1]",FitLowRange, FitHighRange);
TFitResultPtr fitres_Lin;
vector<TH1F *> * DataVec, * MCVec;
for (int iChan = 0; iChan < 7; ++iChan) {
subSampName = subSampVec->at(grabChan[iChan]).histNameSuffix;
plotGrabName = plotGrabBaseName;
plotSystGrabName = plotGrabName;
plotGrabName += subSampName;
dataHistTH1Vec = new vector<TH1 *>;
mcHistTH1Vec = new vector<TH1 *>;
mcHistSystTH1Vec = new vector<TH1 *>;
DataVec = new vector<TH1F *>;
MCVec = new vector<TH1F *>;
HistogramVecGrabberCentValGrab(inputFiles, true, dataHistTH1Vec, nVtxBackScaleVec, plotGrabName, subSampName, useDDEstimate, TTBarSF, scaleLumi);
HistogramVecGrabberCentValGrab(inputFiles, false, mcHistTH1Vec, nVtxBackScaleVec, plotGrabName, subSampName, useDDEstimate, TTBarSF, scaleLumi);
DataComp = HistogramAdderDataTwoDee(dataHistTH1Vec);
MCComp = HistogramAdderDataTwoDee(mcHistTH1Vec);
VectorDistMakerMean(DataMean, DataVec, DataComp, plotGrabName+TString("_mean"), plotGrabName + TString("_Vec"));
VectorDistMakerMean(MCMean, DataVec, MCComp, plotGrabName+TString("_MC_mean"), plotGrabName + TString("_MC_Vec"));
HistMainAttSet(DataMean, 0, 0, kBlue, DataMean->GetLineWidth(), kBlue, 20, DataMean->GetMarkerSize());
HistMainAttSet(MCMean, 0, 0, kRed, MCMean->GetLineWidth(), kRed, 24, MCMean->GetMarkerSize());
canvName = canvNameBase;
canvName += canvNameAdd[iChan];
canvName += canvSuffixSaveName;
c_Var = new TCanvas(canvName, canvName, 0, 0, 700, 700);
DataMean->Draw();
MCMean->Draw("same");
XAxis = DataMean->GetXaxis();
YAxis = DataMean->GetYaxis();
HistAxisAttSet(YAxis, "<E_{x}^{miss}> [GeV/c]", YAxis->GetTitleSize(), YAxis->GetTitleOffset(), YAxis->GetLabelSize(), YAxis->GetLabelOffset(), -30.0, 30.0);
leg= new TLegend(0.2,0.65,0.60,0.85);
f1_resp_Lin->SetLineColor(kBlue);
f1_resp_Lin->SetLineWidth(2);
f1_resp_Lin->SetLineStyle(1);
fitres_Lin = DataMean->Fit(f1_resp_Lin,FitOption,"axis same",FitLowRange, FitHighRange);
c_0d = fitres_Lin->Parameter(0);
c_1d = fitres_Lin->Parameter(1);
sprintf(buf,"data A+B+C+D c_{0} = %0.2f #pm %0.2f",fitres_Lin->Parameter(0),fitres_Lin->ParError(0));
leg->AddEntry(DataMean,buf,"p");
sprintf(buf,"data A+B+C+D c_{1} = %0.2f #pm %0.2f",fitres_Lin->Parameter(1),fitres_Lin->ParError(1));
leg->AddEntry(DataMean,buf,"p");
f1_resp_Lin->SetLineStyle(2);
f1_resp_Lin->SetLineColor(kRed);
fitres_Lin = MCMean->Fit(f1_resp_Lin,FitOption,"axis same",FitLowRange, FitHighRange);
c_0mc = fitres_Lin->Parameter(0);
c_1mc = fitres_Lin->Parameter(1);
sprintf(buf,"sim A+B+C+D c_{0} = %0.2f #pm %0.2f",fitres_Lin->Parameter(0),fitres_Lin->ParError(0));
leg->AddEntry(MCMean,buf,"p");
sprintf(buf,"sim A+B+C+D c_{1} = %0.2f #pm %0.2f",fitres_Lin->Parameter(1),fitres_Lin->ParError(1));
leg->AddEntry(MCMean,buf,"p");
leg->Draw("same");
c_Var->SaveAs(canvName + TString(".pdf"));
if (makeRootCopy) {
c_Var->SaveAs(canvName + TString(".root"));
}
cout << "{c_0 X data, c_1 X data, c_0 X MC, c_1 X MC} is: {" << c_0d << ", " << c_1d << ", " << c_0mc << ", " << c_1mc << "}" << endl;
}
canvNameBase = "h_METY_vs_nVtx_noPhiCorr";
plotGrabBaseName = "h_METY_vs_nVtx_noPhiCorr";
for (int iChan = 0; iChan < 7; ++iChan) {
subSampName = subSampVec->at(grabChan[iChan]).histNameSuffix;
plotGrabName = plotGrabBaseName;
plotSystGrabName = plotGrabName;
plotGrabName += subSampName;
dataHistTH1Vec = new vector<TH1 *>;
mcHistTH1Vec = new vector<TH1 *>;
mcHistSystTH1Vec = new vector<TH1 *>;
DataVec = new vector<TH1F *>;
MCVec = new vector<TH1F *>;
HistogramVecGrabberCentValGrab(inputFiles, true, dataHistTH1Vec, nVtxBackScaleVec, plotGrabName, subSampName, useDDEstimate, TTBarSF, scaleLumi);
HistogramVecGrabberCentValGrab(inputFiles, false, mcHistTH1Vec, nVtxBackScaleVec, plotGrabName, subSampName, useDDEstimate, TTBarSF, scaleLumi);
DataComp = HistogramAdderDataTwoDee(dataHistTH1Vec);
MCComp = HistogramAdderDataTwoDee(mcHistTH1Vec);
VectorDistMakerMean(DataMean, DataVec, DataComp, plotGrabName+TString("_mean"), plotGrabName + TString("_Vec"));
VectorDistMakerMean(MCMean, DataVec, MCComp, plotGrabName+TString("_MC_mean"), plotGrabName + TString("_MC_Vec"));
HistMainAttSet(DataMean, 0, 0, kBlue, DataMean->GetLineWidth(), kBlue, 20, DataMean->GetMarkerSize());
HistMainAttSet(MCMean, 0, 0, kRed, MCMean->GetLineWidth(), kRed, 24, MCMean->GetMarkerSize());
canvName = canvNameBase;
canvName += canvNameAdd[iChan];
canvName += canvSuffixSaveName;
c_Var = new TCanvas(canvName, canvName, 0, 0, 700, 700);
DataMean->Draw();
MCMean->Draw("same");
XAxis = DataMean->GetXaxis();
YAxis = DataMean->GetYaxis();
HistAxisAttSet(YAxis, "<E_{y}^{miss}> [GeV/c]", YAxis->GetTitleSize(), YAxis->GetTitleOffset(), YAxis->GetLabelSize(), YAxis->GetLabelOffset(), -30.0, 30.0);
leg= new TLegend(0.2,0.65,0.60,0.85);
f1_resp_Lin->SetLineColor(kBlue);
f1_resp_Lin->SetLineWidth(2);
f1_resp_Lin->SetLineStyle(1);
fitres_Lin = DataMean->Fit(f1_resp_Lin,FitOption,"axis same",FitLowRange, FitHighRange);
c_0d = fitres_Lin->Parameter(0);
c_1d = fitres_Lin->Parameter(1);
sprintf(buf,"data A+B+C+D c_{0} = %0.2f #pm %0.2f",fitres_Lin->Parameter(0),fitres_Lin->ParError(0));
leg->AddEntry(DataMean,buf,"p");
sprintf(buf,"data A+B+C+D c_{1} = %0.2f #pm %0.2f",fitres_Lin->Parameter(1),fitres_Lin->ParError(1));
leg->AddEntry(DataMean,buf,"p");
f1_resp_Lin->SetLineStyle(2);
f1_resp_Lin->SetLineColor(kRed);
fitres_Lin = MCMean->Fit(f1_resp_Lin,FitOption,"axis same",FitLowRange, FitHighRange);
c_0mc = fitres_Lin->Parameter(0);
c_1mc = fitres_Lin->Parameter(1);
sprintf(buf,"sim A+B+C+D c_{0} = %0.2f #pm %0.2f",fitres_Lin->Parameter(0),fitres_Lin->ParError(0));
leg->AddEntry(MCMean,buf,"p");
sprintf(buf,"sim A+B+C+D c_{1} = %0.2f #pm %0.2f",fitres_Lin->Parameter(1),fitres_Lin->ParError(1));
leg->AddEntry(MCMean,buf,"p");
leg->Draw("same");
c_Var->SaveAs(canvName + TString(".pdf"));
if (makeRootCopy) {
c_Var->SaveAs(canvName + TString(".root"));
}
cout << "{c_0 Y data, c_1 Y data, c_0 Y MC, c_1 Y MC} is: {" << c_0d << ", " << c_1d << ", " << c_0mc << ", " << c_1mc << "}" << endl;
}
theApp.Run(retVal);
// theApp.Terminate(0);
}
