void getPlotData() {
TH1 * h = (TH1*) m_file->Get(m_direc.c_str());
for (int i=0; i<h->GetXaxis()->GetNbins(); i++) {
m_xs.push_back(h->GetXaxis()->GetBinCenter(i));
m_ys.push_back(h->GetBinContent(i));
}
m_plot->m_xAxisTitle = std::string(h->GetXaxis()->GetTitle());
m_plot->m_yAxisTitle = std::string(h->GetYaxis()->GetTitle());
m_plot->m_title = std::string(h->GetTitle());
std::stringstream ssN, ssMu, ssSig, ssUF, ssOF;
ssN << std::setprecision(4) << h->GetEntries();
ssMu << std::setprecision(4) << h->GetMean();
ssSig << std::setprecision(4) << h->GetRMS();
ssUF << std::setprecision(4) << h->GetBinContent(0);
ssOF << std::setprecision(4) << h->GetBinContent(h->GetNbinsX() + 1);
m_statsTitles.push_back("N:");
m_statsTitles.push_back("mu:");
m_statsTitles.push_back("sig:");
m_statsTitles.push_back("UF:");
m_statsTitles.push_back("OF:");
m_statsValues.push_back(ssN.str());
m_statsValues.push_back(ssMu.str());
m_statsValues.push_back(ssSig.str());
m_statsValues.push_back(ssUF.str());
m_statsValues.push_back(ssOF.str());
}
void counts(int run, int lumistart, int lumiend, string type, map<string,vector<tripletI> > &cnt, vector<tripletD> &cntref, string hlttype, bool docnt, bool doref) {
TString filename = basedir + Form("/DQM_V0001_HLTpb_R000%i.root",run);
TFile *f = new TFile(filename);
if (!f->IsOpen()) {
cout << "Error, could not open " << filename << endl;
return;
}
TString tdirname = Form("DQMData/Run %i/HLT/Run summary/TriggerRates/",run) + TString(type);
f->cd(tdirname);
TProfile *hlumi = (TProfile*) f->Get(Form("DQMData/Run %i/HLT/Run summary/LumiMonitoring/lumiVsLS",run));
if (extrapol) extrapolate(hlumi);
// if HLT: accept, error, pass L1 seed, pass prescaler, reject
TIter next(gDirectory->GetListOfKeys());
TKey *key;
while ((key = (TKey*)next())) {
TClass *cl = gROOT->GetClass(key->GetClassName());
// it must be an histogram
if (!cl->InheritsFrom("TH1")) continue;
TH1 *h = (TH1*)key->ReadObj();
// the name must match one of the requested patterns
bool match=false; TString hname(h->GetName());
for (vector<TRegexp>::const_iterator it=patterns.begin(); it!=patterns.end(); it++) {
if (hname(*it).Length()!=0) {
match=true;
break;
}
}
if (!match) continue;
int nlumis = (lumiend+1-lumistart);
if (extrapol) extrapolate(h);
if (type != "HLT") fill(cnt[h->GetName()], h, run, lumistart, lumiend, docnt);
else {
string htitle(h->GetTitle());
if (htitle.find(hlttype) == string::npos) continue;
else {
TString thepath; Ssiz_t from=0; TString(htitle).Tokenize(thepath,from," ");
fill(cnt[thepath.Data()], h, run, lumistart, lumiend, docnt);
}
}
}
if (doref) {
fill(cntref, hlumi, run, lumistart, lumiend);
}
f->Close();
delete f;
}
/**
* Create ratios to other data
*
* @param ib Bin number
* @param res Result
* @param alice ALICE result if any
* @param cms CMS result if any
* @param all Stack to add ratio to
*/
void Ratio2Stack(Int_t ib, TH1* res, TGraph* alice, TGraph* cms, THStack* all)
{
if (!all || !res || !(alice || cms)) return;
Int_t off = 5*ib;
TGraph* gs[] = { (alice ? alice : cms), (alice ? cms : 0), 0 };
TGraph** pg = gs;
while (*pg) {
TGraph* g = *pg;
const char* n = (g == alice ? "ALICE" : "CMS");
TH1* r = static_cast<TH1*>(res->Clone(Form("ratio%s", n)));
TString tit(r->GetTitle());
tit.ReplaceAll("Corrected", Form("Ratio to %s", n));
r->SetTitle(tit);
r->SetMarkerColor(g->GetMarkerColor());
r->SetLineColor(g->GetLineColor());
TObject* tst = r->FindObject("legend");
if (tst) r->GetListOfFunctions()->Remove(tst);
for (Int_t i = 1; i <= r->GetNbinsX(); i++) {
Double_t c = r->GetBinContent(i);
Double_t e = r->GetBinError(i);
Double_t o = g->Eval(r->GetBinCenter(i));
if (o < 1e-12) {
r->SetBinContent(i, 0);
r->SetBinError(i, 0);
continue;
}
r->SetBinContent(i, (c - o) / o + off);
r->SetBinError(i, e / o);
}
all->Add(r);
pg++;
}
TLegend* leg = StackLegend(all);
if (!leg) return;
TString txt = res->GetTitle();
txt.ReplaceAll("Corrected P(#it{N}_{ch}) in ", "");
if (ib == 0) txt.Append(" "); // (#times1)");
// else if (ib == 1) txt.Append(" (#times10)");
else txt.Append(Form(" (+%d)", off));
TObject* dummy = 0;
TLegendEntry* e = leg->AddEntry(dummy, txt, "p");
e->SetMarkerStyle(res->GetMarkerStyle());
e->SetMarkerSize(res->GetMarkerSize());
e->SetMarkerColor(kBlack);
e->SetFillColor(0);
e->SetFillStyle(0);
e->SetLineColor(kBlack);
}
RooHistN::RooHistN(const TH1 &data1, const TH1 &data2, Double_t nominalBinWidth, Double_t nSigma, Double_t xErrorFrac) :
TGraphAsymmErrors(), _nominalBinWidth(nominalBinWidth), _nSigma(nSigma), _rawEntries(-1)
{
// Create a histogram from the asymmetry between the specified TH1 objects
// which may have fixed or variable bin widths, but which must both have
// the same binning. The asymmetry is calculated as (1-2)/(1+2). Error bars are
// calculated using Binomial statistics. Prints a warning and rounds
// any bins with non-integer contents. Use the optional parameter to
// specify the confidence level in units of sigma to use for
// calculating error bars. The nominal bin width specifies the
// default used by addAsymmetryBin(), and is used to set the relative
// normalization of bins with different widths. If not set, the
// nominal bin width is calculated as range/nbins.
initialize();
// copy the first input histogram's name and title
SetName(data1.GetName());
SetTitle(data1.GetTitle());
// calculate our nominal bin width if necessary
if(_nominalBinWidth == 0) {
const TAxis *axis= ((TH1&)data1).GetXaxis();
if(axis->GetNbins() > 0) _nominalBinWidth= (axis->GetXmax() - axis->GetXmin())/axis->GetNbins();
}
setYAxisLabel(Form("Asymmetry (%s - %s)/(%s + %s)",
data1.GetName(),data2.GetName(),data1.GetName(),data2.GetName()));
// initialize our contents from the input histogram contents
Int_t nbin= data1.GetNbinsX();
if(data2.GetNbinsX() != nbin) {
coutE(InputArguments) << "RooHistN::RooHistN: histograms have different number of bins" << endl;
return;
}
for(Int_t bin= 1; bin <= nbin; bin++) {
Axis_t x= data1.GetBinCenter(bin);
if(fabs(data2.GetBinCenter(bin)-x)>1e-10) {
coutW(InputArguments) << "RooHistN::RooHistN: histograms have different centers for bin " << bin << endl;
}
Stat_t y1= data1.GetBinContent(bin);
Stat_t y2= data2.GetBinContent(bin);
addAsymmetryBin(x,roundBin(y1),roundBin(y2),data1.GetBinWidth(bin),xErrorFrac);
}
// we do not have a meaningful number of entries
_entries= -1;
}
RooHistN::RooHistN(const TH1 &data, Double_t nominalBinWidth, Double_t nSigma, RooAbsData::ErrorType etype, Double_t xErrorFrac) :
TGraphAsymmErrors(), _nominalBinWidth(nominalBinWidth), _nSigma(nSigma), _rawEntries(-1)
{
// Create a histogram from the contents of the specified TH1 object
// which may have fixed or variable bin widths. Error bars are
// calculated using Poisson statistics. Prints a warning and rounds
// any bins with non-integer contents. Use the optional parameter to
// specify the confidence level in units of sigma to use for
// calculating error bars. The nominal bin width specifies the
// default used by addBin(), and is used to set the relative
// normalization of bins with different widths. If not set, the
// nominal bin width is calculated as range/nbins.
initialize();
// copy the input histogram's name and title
SetName(data.GetName());
SetTitle(data.GetTitle());
// calculate our nominal bin width if necessary
if(_nominalBinWidth == 0) {
const TAxis *axis= ((TH1&)data).GetXaxis();
if(axis->GetNbins() > 0) _nominalBinWidth= (axis->GetXmax() - axis->GetXmin())/axis->GetNbins();
}
// TH1::GetYaxis() is not const (why!?)
setYAxisLabel(const_cast<TH1&>(data).GetYaxis()->GetTitle());
// initialize our contents from the input histogram's contents
Int_t nbin= data.GetNbinsX();
for(Int_t bin= 1; bin <= nbin; bin++) {
Axis_t x= data.GetBinCenter(bin);
Stat_t y= data.GetBinContent(bin);
Stat_t dy = data.GetBinError(bin) ;
if (etype==RooAbsData::Poisson) {
addBin(x,roundBin(y),data.GetBinWidth(bin),xErrorFrac);
} else {
addBinWithError(x,y,dy,dy,data.GetBinWidth(bin),xErrorFrac);
}
}
// add over/underflow bins to our event count
_entries+= data.GetBinContent(0) + data.GetBinContent(nbin+1);
}
void writeFile(const char* inRootFile)
{
TFile inRoot(inRootFile);
if(!inRoot.IsOpen()){
cout << "Cannot open " << inRootFile << endl;
return;
}
TIterator* iterator = inRoot.GetListOfKeys()->MakeIterator();
TKey* key;
TString outText = inRootFile;
outText.Replace(0,outText.Last('/')+1,"");
ofstream os(outText.Data());
char buf[500];
int count(0);
while( (key=dynamic_cast<TKey*>(iterator->Next())) != 0){
cout << key->GetName() << endl;
TH1* h = (TH1*)inRoot.Get(key->GetName());
if(h->GetDimension()!=1) continue;
if(++count>1) break;
int nBin = h->GetNbinsX();
os << "name: " << h->GetName() << endl
<< "title: " << h->GetTitle() << endl
<< "bins: " << h->GetNbinsX() << endl
<< "min: " << h->GetXaxis()->GetBinLowEdge(1)
<< ", max: " << h->GetXaxis()->GetBinUpEdge(h->GetNbinsX()) << endl;
for(int i=1; i<=nBin; i++){
os << "bin: " << i << " value: " << (float)h->GetBinContent(i)
<< " error: " << (float)h->GetBinError(i) << endl;
}
}
}
TString* get_var_names( Int_t nVars )
{
const TString directories[6] = { "InputVariables_NoTransform",
"InputVariables_DecorrTransform",
"InputVariables_PCATransform",
"InputVariables_Id",
"InputVariables_Norm",
"InputVariables_Deco"};
TDirectory* dir = 0;
for (Int_t i=0; i<6; i++) {
dir = (TDirectory*)Network_GFile->Get( directories[i] );
if (dir != 0) break;
}
if (dir==0) {
cout << "*** Big troubles in macro \"network.C\": could not find directory for input variables, "
<< "and hence could not determine variable names --> abort" << endl;
return 0;
}
cout << "--> go into directory: " << dir->GetName() << endl;
dir->cd();
TString* vars = new TString[nVars];
Int_t ivar = 0;
// loop over all objects in directory
TIter next(dir->GetListOfKeys());
TKey* key = 0;
while ((key = (TKey*)next())) {
if (key->GetCycle() != 1) continue;
if(!TString(key->GetName()).Contains("__S") &&
!TString(key->GetName()).Contains("__r")) continue;
// make sure, that we only look at histograms
TClass *cl = gROOT->GetClass(key->GetClassName());
if (!cl->InheritsFrom("TH1")) continue;
TH1 *sig = (TH1*)key->ReadObj();
TString hname = sig->GetTitle();
vars[ivar] = hname; ivar++;
if (ivar > nVars-1) break;
}
if (ivar != nVars-1) { // bias layer is also in nVars counts
cout << "*** Troubles in \"network.C\": did not reproduce correct number of "
<< "input variables: " << ivar << " != " << nVars << endl;
}
return vars;
// ------------- old way (not good) -------------
// TString fname = "weights/TMVAnalysis_MLP.weights.txt";
// ifstream fin( fname );
// if (!fin.good( )) { // file not found --> Error
// cout << "Error opening " << fname << endl;
// exit(1);
// }
// Int_t idummy;
// Float_t fdummy;
// TString dummy = "";
// // file header with name
// while (!dummy.Contains("#VAR")) fin >> dummy;
// fin >> dummy >> dummy >> dummy; // the rest of header line
// // number of variables
// fin >> dummy >> idummy;
// // at this point, we should have idummy == nVars
// // variable mins and maxes
// TString* vars = new TString[nVars];
// for (Int_t i = 0; i < idummy; i++) fin >> vars[i] >> dummy >> dummy >> dummy;
// fin.close();
// return vars;
}
// input: - Input file (result from TMVA),
// - normal/decorrelated/PCA
// - use of TMVA plotting TStyle
void variables( TString fin = "TMVA.root", TString dirName = "InputVariables_Id", TString title = "TMVA Input Variables",
Bool_t isRegression = kFALSE, Bool_t useTMVAStyle = kTRUE )
{
TString outfname = dirName;
outfname.ToLower(); outfname.ReplaceAll( "input", "" );
// set style and remove existing canvas'
TMVAGlob::Initialize( useTMVAStyle );
// obtain shorter histogram title
TString htitle = title;
htitle.ReplaceAll("variables ","variable");
htitle.ReplaceAll("and target(s)","");
htitle.ReplaceAll("(training sample)","");
// checks if file with name "fin" is already open, and if not opens one
TFile* file = TMVAGlob::OpenFile( fin );
TDirectory* dir = (TDirectory*)file->Get( dirName );
if (dir==0) {
cout << "No information about " << title << " available in directory " << dirName << " of file " << fin << endl;
return;
}
dir->cd();
// how many plots are in the directory?
Int_t noPlots = TMVAGlob::GetNumberOfInputVariables( dir ) +
TMVAGlob::GetNumberOfTargets( dir );
// define Canvas layout here!
// default setting
Int_t xPad; // no of plots in x
Int_t yPad; // no of plots in y
Int_t width; // size of canvas
Int_t height;
switch (noPlots) {
case 1:
xPad = 1; yPad = 1; width = 550; height = 0.90*width; break;
case 2:
xPad = 2; yPad = 1; width = 600; height = 0.50*width; break;
case 3:
xPad = 3; yPad = 1; width = 900; height = 0.4*width; break;
case 4:
xPad = 2; yPad = 2; width = 600; height = width; break;
default:
// xPad = 3; yPad = 2; width = 800; height = 0.55*width; break;
xPad = 1; yPad = 1; width = 550; height = 0.90*width; break;
}
Int_t noPadPerCanv = xPad * yPad ;
// counter variables
Int_t countCanvas = 0;
Int_t countPad = 0;
// loop over all objects in directory
TCanvas* canv = 0;
TKey* key = 0;
Bool_t createNewFig = kFALSE;
TIter next(dir->GetListOfKeys());
while ((key = (TKey*)next())) {
if (key->GetCycle() != 1) continue;
if (!TString(key->GetName()).Contains("__Signal") &&
!(isRegression && TString(key->GetName()).Contains("__Regression"))) continue;
// make sure, that we only look at histograms
TClass *cl = gROOT->GetClass(key->GetClassName());
if (!cl->InheritsFrom("TH1")) continue;
TH1 *sig = (TH1*)key->ReadObj();
TString hname(sig->GetName());
//normalize to 1
NormalizeHist(sig);
// create new canvas
if (countPad%noPadPerCanv==0) {
++countCanvas;
canv = new TCanvas( Form("canvas%d", countCanvas), title,
countCanvas*50+50, countCanvas*20, width, height );
canv->Divide(xPad,yPad);
canv->SetFillColor(kWhite);
canv->Draw();
}
TPad* cPad = (TPad*)canv->cd(countPad++%noPadPerCanv+1);
cPad->SetFillColor(kWhite);
// find the corredponding backgrouns histo
TString bgname = hname;
bgname.ReplaceAll("__Signal","__Background");
TH1 *bgd = (TH1*)dir->Get(bgname);
if (bgd == NULL) {
cout << "ERROR!!! couldn't find background histo for" << hname << endl;
exit;
}
//normalize to 1
NormalizeHist(bgd);
// this is set but not stored during plot creation in MVA_Factory
TMVAGlob::SetSignalAndBackgroundStyle( sig, (isRegression ? 0 : bgd) );
sig->SetTitle( TString( htitle ) + ": " + sig->GetTitle() );
TMVAGlob::SetFrameStyle( sig, 1.2 );
// normalise both signal and background
// if (!isRegression) TMVAGlob::NormalizeHists( sig, bgd );
// else {
// // change histogram title for target
// TString nme = sig->GetName();
// if (nme.Contains( "_target" )) {
// TString tit = sig->GetTitle();
// sig->SetTitle( tit.ReplaceAll("Input variable", "Regression target" ) );
// }
// }
sig->SetTitle( "" );
// finally plot and overlay
Float_t sc = 1.1;
if (countPad == 1) sc = 1.3;
sig->SetMaximum( TMath::Max( sig->GetMaximum(), bgd->GetMaximum() )*sc );
sig->Draw( "hist" );
cPad->SetLeftMargin( 0.17 );
sig->GetYaxis()->SetTitleOffset( 1.50 );
if (!isRegression) {
bgd->Draw("histsame");
TString ytit = TString("(1/N) ") + sig->GetYaxis()->GetTitle();
ytit = TString("Fraction of Events");
sig->GetYaxis()->SetTitle( ytit ); // histograms are normalised
}
if (countPad == 1) sig->GetXaxis()->SetTitle("Leading Lepton p_{T} [GeV/c]");
if (countPad == 2) sig->GetXaxis()->SetTitle("Trailing Lepton p_{T} [GeV/c]");
if (countPad == 3) sig->GetXaxis()->SetTitle("#Delta#phi(l,l)");
if (countPad == 4) sig->GetXaxis()->SetTitle("#Delta R(l,l)");
if (countPad == 5) sig->GetXaxis()->SetTitle("Dilepton Mass [GeV/c^{2}]");
if (countPad == 6) sig->GetXaxis()->SetTitle("Dilepton Flavor Final State");
if (countPad == 7) sig->GetXaxis()->SetTitle("M_{T} (Higgs) [GeV/c^{2}]");
if (countPad == 8) sig->GetXaxis()->SetTitle("#Delta#phi(Dilepton System, MET)");
if (countPad == 9) sig->GetXaxis()->SetTitle("#Delta#phi(Dilepton System, Jet)");
// Draw legend
// if (countPad == 1 && !isRegression) {
TLegend *legend= new TLegend( cPad->GetLeftMargin(),
1-cPad->GetTopMargin()-.15,
cPad->GetLeftMargin()+.4,
1-cPad->GetTopMargin() );
if(countPad == 1 || countPad == 2 ||countPad == 3 ||countPad == 4 ||countPad == 5 ||countPad == 7 ) {
legend= new TLegend( 0.50,
1-cPad->GetTopMargin()-.15,
0.90,
1-cPad->GetTopMargin() );
}
legend->SetFillStyle(0);
legend->AddEntry(sig,"Signal","F");
legend->AddEntry(bgd,"Background","F");
legend->SetBorderSize(0);
legend->SetMargin( 0.3 );
legend->SetTextSize( 0.03 );
legend->Draw("same");
// }
// redraw axes
sig->Draw("sameaxis");
// text for overflows
Int_t nbin = sig->GetNbinsX();
Double_t dxu = sig->GetBinWidth(0);
Double_t dxo = sig->GetBinWidth(nbin+1);
TString uoflow = "";
if (isRegression) {
uoflow = Form( "U/O-flow: %.1f%% / %.1f%%",
sig->GetBinContent(0)*dxu*100, sig->GetBinContent(nbin+1)*dxo*100 );
}
else {
uoflow = Form( "U/O-flow (S,B): (%.1f, %.1f)%% / (%.1f, %.1f)%%",
sig->GetBinContent(0)*dxu*100, bgd->GetBinContent(0)*dxu*100,
sig->GetBinContent(nbin+1)*dxo*100, bgd->GetBinContent(nbin+1)*dxo*100 );
}
TText* t = new TText( 0.98, 0.14, uoflow );
t->SetNDC();
t->SetTextSize( 0.040 );
t->SetTextAngle( 90 );
// t->AppendPad();
// save canvas to file
if (countPad%noPadPerCanv==0) {
TString fname = Form( "plots/%s_c%i", outfname.Data(), countCanvas );
TMVAGlob::plot_logo();
TMVAGlob::imgconv( canv, fname );
createNewFig = kFALSE;
}
else {
createNewFig = kTRUE;
}
}
if (createNewFig) {
TString fname = Form( "plots/%s_c%i", outfname.Data(), countCanvas );
TMVAGlob::plot_logo();
TMVAGlob::imgconv( canv, fname );
createNewFig = kFALSE;
}
return;
}
TH1* GetCentK(TDirectory* top, Double_t c1, Double_t c2, Int_t s,
TLegend* l)
{
TString dname; dname.Form("cent%06.2f_%06.2f", c1, c2);
dname.ReplaceAll(".", "d");
TDirectory* d = top->GetDirectory(dname);
if (!d) {
Warning("GetCetnK", "Directory %s not found in %s",
dname.Data(), top->GetName());
return;
}
TDirectory* det = d->GetDirectory("details");
if (!det) {
Warning("GetCetnK", "Directory details not found in %s",
d->GetName());
d->ls();
return;
}
TObject* o = det->Get("scalar");
if (!o) {
Warning("GetCetnK", "Object scalar not found in %s",
det->GetName());
return;
}
if (!o->IsA()->InheritsFrom(TH1::Class())) {
Warning("GetCetnK", "Object %s is not a TH1, but a %s",
o->GetName(), o->ClassName());
return;
}
TH1* h = static_cast<TH1*>(o->Clone());
Color_t col = cc[(s-1)%10];
h->SetLineColor(col);
h->SetMarkerColor(col);
h->SetFillColor(col);
h->SetFillStyle(1001);
// h->SetTitle(Form("%5.2f-%5.2f%% #times %d", c1, c2, s));
h->SetTitle(Form("%2.0f-%2.0f%% + %d", c1, c2, s-1));
TF1* f = new TF1("", "[0]",-2.2,2.2);
f->SetParameter(0,s-1);
f->SetLineColor(col);
f->SetLineStyle(7);
f->SetLineWidth(1);
// h->Scale(s);
h->Add(f);
h->GetListOfFunctions()->Add(f);
f->SetParameter(0,s);
for (Int_t i = 1; i <= h->GetNbinsX(); i++) {
if (TMath::Abs(h->GetBinCenter(i)) > 2) {
h->SetBinContent(i,0);
h->SetBinError(i,0);
}
}
TLegendEntry* e = l->AddEntry(h, h->GetTitle(), "f");
e->SetFillColor(col);
e->SetFillStyle(1001);
e->SetLineColor(col);
return h;
}
void DrawTwoInPad(TVirtualPad* p,
Int_t sub,
TH1* h1,
TH1* h2,
Bool_t ratio,
Bool_t logy=false,
Bool_t legend=false)
{
TVirtualPad* pp = p->cd(sub);
pp->SetRightMargin(0.02);
pp->SetLeftMargin(0.10);
TVirtualPad* ppp = pp;
if (ratio) {
pp->Divide(1,2,0,0);
ppp = pp->cd(1);
ppp->SetRightMargin(0.02);
}
if (logy) ppp->SetLogy();
TH1* hs[] = { h1, h2, 0 };
if (h1->GetMaximum() < h2->GetMaximum()) {
hs[0] = h2;
hs[1] = h1;
}
TH1** ph = hs;
Double_t size = (ratio ? 0.1 : 0.05);
Double_t off = (ratio ? 0.6 : 0.5);
h1->SetFillStyle(3004);
h2->SetFillStyle(3005);
while (*ph) {
TString opt("hist");
if (ph != hs) opt.Append(" same");
TH1* copy = (*ph)->DrawCopy(opt);
copy->GetXaxis()->SetLabelSize(2*size);
copy->GetYaxis()->SetLabelSize(size);
copy->GetYaxis()->SetTitleSize(size);
copy->GetYaxis()->SetTitleOffset(off);
copy->SetYTitle(copy->GetTitle());
copy->SetTitle("");
copy->SetDirectory(0);
ph++;
}
TString s1 = h1->GetYaxis()->GetTitle();
TString s2 = h2->GetYaxis()->GetTitle();
if (legend) {
TLegend* l = new TLegend(0.6, 0.1, 0.9, 0.9);
l->SetBorderSize(0);
TLegendEntry* e = l->AddEntry("dummy", s1, "lf");
l->SetFillColor(kWhite);
e->SetFillColor(kBlack);
e->SetFillStyle(h1->GetFillStyle());
e = l->AddEntry("dummy", s2, "lf");
e->SetFillColor(kBlack);
e->SetFillStyle(h2->GetFillStyle());
l->Draw();
}
if (!ratio) return;
ppp = pp->cd(2);
ppp->SetRightMargin(0.02);
TH1* r = static_cast<TH1*>(h1->Clone(Form("ratio%s", h1->GetName())));
r->SetDirectory(0);
r->SetTitle("");
r->GetXaxis()->SetLabelSize(size);
r->GetYaxis()->SetLabelSize(size);
r->GetYaxis()->SetTitleSize(0.9*size);
r->GetYaxis()->SetTitleOffset(0.9*off);
r->SetMarkerStyle(20);
r->SetMarkerColor(h1->GetFillColor()+1);
r->SetFillStyle(3007);
r->SetYTitle(Form("#frac{%s}{%s}", s1.Data(), s2.Data()));
// r->Add(h2, -1);
// r->Divide(h1);
if (!r->IsA()->InheritsFrom(TProfile::Class())) {
r->GetSumw2()->Set(0); // r->Sumw2(false);
h2->GetSumw2()->Set(0); // h2->Sumw2(false);
}
r->Divide(h2);
Printf("%s", r->GetName());
for (UShort_t bin = 1; bin <= r->GetNbinsX(); bin++) {
Printf(" bin # %2d: Diff=%g+/-%g", bin, r->GetBinContent(bin),
r->GetBinError(bin));
r->SetBinError(bin, 0);
}
r->GetSumw2()->Set(0); //r->Sumw2(false);
r->SetMarkerSize(4);
r->SetMaximum(r->GetMaximum()*1.2);
r->SetMinimum(r->GetMinimum()*0.8);
r->Draw("hist text30");
p->Modified();
p->Update();
p->cd();
}
TObjArray* ProcessSummary(TObjArray* arrs, int icl, const char* pref)
{
// Process TObjArray (e.g. for set of pt bins) of TObjArray of KMCTrackSummary objects:
// pick the KMCTrackSummary for "summary class" icl (definition of acceptable track) and create
// graphs vs bin.
// These graphs are returned in new TObjArray
//
TString prefs = pref;
if (!gs) gs = new TF1("gs","gaus",-1,1);
//
int nb = arrs->GetEntriesFast();
TObjArray* sums = (TObjArray*) arrs->At(0);
int nclass = sums->GetEntriesFast();
if (icl>=nclass) {printf("summary set has %d classes only, %d requested\n",nclass,icl);return 0;}
//
KMCTrackSummary* sm = (KMCTrackSummary*)sums->At(icl);
//
TH1* h;
//
h = sm->GetHMCSigDCARPhi(); // MC resolution in transverse DCA
TGraphErrors * grSigD = 0;
if (h) {
grSigD = new TGraphErrors(nb);
grSigD->SetName(Form("%s%s",prefs.Data(),h->GetName()));
grSigD->SetTitle(Form("%s%s",prefs.Data(),h->GetTitle()));
}
//
TGraphErrors * grSigZ = 0;
h = sm->GetHMCSigDCAZ(); // MC resolution in Z DCA
if (h) {
grSigZ = new TGraphErrors(nb);
grSigZ->SetName(Form("%s%s",prefs.Data(),h->GetName()));
grSigZ->SetTitle(Form("%s%s",prefs.Data(),h->GetTitle()));
}
//
TGraphErrors * grSigAD = 0; // anaitical estimate for resolution in transverse DCA
{
grSigAD = new TGraphErrors(nb);
grSigAD->SetName(Form("%s%s",prefs.Data(),"sigmaDan"));
grSigAD->SetTitle(Form("%s%s",prefs.Data(),"#sigmaD an"));
}
//
TGraphErrors * grSigAZ = 0; // anaitical estimate for resolution in Z DCA
{
grSigAZ = new TGraphErrors(nb);
grSigAZ->SetName(Form("%s%s",prefs.Data(),"sigmaZan"));
grSigAZ->SetTitle(Form("%s%s",prefs.Data(),"#sigmaZ an"));
}
//
//
TGraphErrors * grSigPt = 0; // MC res. in pt
{
grSigPt = new TGraphErrors(nb);
grSigPt->SetName(Form("%s%s",prefs.Data(),"sigmaPt"));
grSigPt->SetTitle(Form("%s%s",prefs.Data(),"#sigmaPt"));
}
//
TGraphErrors * grSigAPt = 0; // analitycal res. in pt
{
grSigAPt = new TGraphErrors(nb);
grSigAPt->SetName(Form("%s%s",prefs.Data(),"sigmaPtan"));
grSigAPt->SetTitle(Form("%s%s",prefs.Data(),"#sigmaPt an"));
}
//
TGraphErrors * grEff = 0; // MC efficiency
{
grEff = new TGraphErrors(nb);
grEff->SetName(Form("%s_rate",prefs.Data()));
grEff->SetTitle(Form("%s Rate",prefs.Data()));
}
//
TGraphErrors * grUpd = 0; // number of Kalman track updates
{
grUpd = new TGraphErrors(nb);
grUpd->SetName(Form("%s_updCalls",prefs.Data()));
grUpd->SetTitle(Form("%s Updates",prefs.Data()));
}
//
for (int ib=0;ib<nb;ib++) {
sums = (TObjArray*) arrs->At(ib);
sm = (KMCTrackSummary*)sums->At(icl);
KMCProbe& prbRef = sm->GetRefProbe();
KMCProbe& prbAn = sm->GetAnProbe();
double pt = prbRef.Pt();
//
if (grSigAD) {
grSigAD->SetPoint(ib, pt,prbAn.GetSigmaY2()>0 ? TMath::Sqrt(prbAn.GetSigmaY2()) : 0.);
}
//
if (grSigAZ) {
grSigAZ->SetPoint(ib, pt,prbAn.GetSigmaZ2()>0 ? TMath::Sqrt(prbAn.GetSigmaZ2()) : 0.);
}
//
if (grSigAPt) {
double pts = TMath::Sqrt(prbAn.GetSigma1Pt2());
grSigAPt->SetPoint(ib, pt,pts>0 ? pts*pt : 0.);
}
//
if (grSigPt) {
h = sm->GetHMCSigPt();
h->Fit(gs,"0q");
grSigPt->SetPoint(ib, pt, gs->GetParameter(2));
grSigPt->SetPointError(ib, 0, gs->GetParError(2));
}
//
if (grSigD) {
h = sm->GetHMCSigDCARPhi();
h->Fit(gs,"0q");
grSigD->SetPoint(ib, pt,gs->GetParameter(2));
grSigD->SetPointError(ib, 0,gs->GetParError(2));
}
//
if (grSigZ) {
h = sm->GetHMCSigDCAZ();
h->Fit(gs,"0q");
grSigZ->SetPoint(ib, pt,gs->GetParameter(2));
grSigZ->SetPointError(ib, 0,gs->GetParError(2));
}
//
if (grEff) {
grEff->SetPoint(ib, pt,sm->GetEff());
grEff->SetPointError(ib, 0,sm->GetEffErr());
}
//
if (grUpd) {
grUpd->SetPoint(ib, pt,sm->GetUpdCalls());
grUpd->SetPointError(ib, 0, 0);
}
}
//
TObjArray* dest = new TObjArray();
dest->AddAtAndExpand(grSigAD,kSigAD);
dest->AddAtAndExpand(grSigAZ,kSigAZ);
dest->AddAtAndExpand(grSigAPt,kSigAPt);
dest->AddAtAndExpand(grSigD,kSigD);
dest->AddAtAndExpand(grSigZ,kSigZ);
dest->AddAtAndExpand(grSigPt,kSigPt);
dest->AddAtAndExpand(grEff,kEff);
dest->AddAtAndExpand(grUpd,kUpd);
//
if (!prefs.IsNull()) dest->SetName(pref);
return dest;
}
void comparisonJetMCData(string plot,int rebin){
string tmp;
string dir="/gpfs/cms/data/2011/Observables/Approval/";
if (isAngularAnalysis){
mcfile=dir+"MC_zjets"+version;
back_w=dir+"MC_wjets"+version;
back_ttbar=dir+"MC_ttbar"+version;
WW=dir+"MC_diW"+version;
ZZ=dir+"MC_siZ"+version;
WZ=dir+"MC_diWZ"+version;
datafile=dir+"DATA"+version;
mcfiletau=dir+"MC_zjetstau"+version;
}
// List of files
TFile *dataf = TFile::Open(datafile.c_str()); //data file
TFile *mcf = TFile::Open(mcfile.c_str()); //MC file
TFile *mcftau = TFile::Open(mcfiletau.c_str()); //MC file
TFile *ttbarf = TFile::Open(back_ttbar.c_str()); //MC background file
TFile *wf = TFile::Open(back_w.c_str());
TFile *qcd23emf = TFile::Open(qcd23em.c_str());
TFile *qcd38emf = TFile::Open(qcd38em.c_str());
TFile *qcd817emf = TFile::Open(qcd817em.c_str());
TFile *qcd23bcf = TFile::Open(qcd23bc.c_str());
TFile *qcd38bcf = TFile::Open(qcd38bc.c_str());
TFile *qcd817bcf = TFile::Open(qcd817bc.c_str());
TFile *WZf = TFile::Open(WZ.c_str());
TFile *ZZf = TFile::Open(ZZ.c_str());
TFile *WWf = TFile::Open(WW.c_str());
// Canvas
if (CanvPlot) delete CanvPlot;
CanvPlot = new TCanvas("CanvPlot","CanvPlot",0,0,800,600);
// Getting, defining ...
dataf->cd("validationJEC");
if (isMu && isAngularAnalysis) dataf->cd("validationJECmu");
TObject * obj;
gDirectory->GetObject(plot.c_str(),obj);
TH1 *data;
TH2F *data2;
TH1D *data3;
THStack *hs = new THStack("hs","Total MC");
int flag=-1;
if ((data = dynamic_cast<TH1F *>(obj)) ){
flag=1;
gROOT->Reset();
gROOT->ForceStyle();
gStyle->SetPadRightMargin(0.03);
gPad->SetLogy(1);
gPad->Modified();
gPad->Update();
}
if ((data2 = dynamic_cast<TH2F *>(obj)) ){
flag=2;
gStyle->SetPalette(1);
gStyle->SetPadRightMargin(0.15);
gPad->Modified();
}
//===================
// Dirty jobs :)
if (flag==1){
CanvPlot->cd();
TPad *pad1 = new TPad("pad1","pad1",0.01,0.33,0.99,0.99);
pad1->Draw();
pad1->cd();
pad1->SetTopMargin(0.1);
pad1->SetBottomMargin(0.01);
pad1->SetRightMargin(0.1);
pad1->SetFillStyle(0);
pad1->SetLogy(1);
TString str=data->GetTitle();
if (str.Contains("jet") && !str.Contains("zMass") && !str.Contains("Num") && !str.Contains("Eta") && !str.Contains("Phi") && !str.Contains("eld") && !str.Contains("meanPtZVsNjet")) {
if (!isAngularAnalysis) rebin=1;
}
//======================
// DATA
Double_t dataint = data->Integral();
data->SetLineColor(kBlack);
data->Rebin(rebin);
if(str.Contains("nJetVtx")) data->GetXaxis()->SetRangeUser(0,10);
if(str.Contains("zMass")) data->GetXaxis()->SetRangeUser(70,110);
data->SetMinimum(1.);
data->Sumw2();
//Canvas style copied from plotsHistsRatio.C
data->SetLabelSize(0.0);
data->GetXaxis()->SetTitleSize(0.00);
data->GetYaxis()->SetLabelSize(0.07);
data->GetYaxis()->SetTitleSize(0.08);
data->GetYaxis()->SetTitleOffset(0.76);
data->SetTitle("");
gStyle->SetOptStat(0);
data->GetYaxis()->SetLabelSize(0.06);
data->GetYaxis()->SetTitleSize(0.06);
data->GetYaxis()->SetTitleOffset(0.8);
data->Draw("E1");
TLegend* legend = new TLegend(0.725,0.27,0.85,0.72);
legend->SetFillColor(0);
legend->SetFillStyle(0);
legend->SetBorderSize(0);
legend->SetTextSize(0.060);
legend->AddEntry(data,"data","p");
// hack to calculate some yields in restricted regions...
int num1=0, num2=0, num3=0, num4=0, num5=0;
if(str.Contains("invMass") && !str.Contains("PF")){
for(int j=1;j<=data->GetNbinsX();j++){
num1 += data->GetBinContent(j); //conto quante Z ci sono tra 60 e 120 GeV
if(j>10&&j<=50) num2 += data->GetBinContent(j); // ... tra 70 e 110
if(j>15&&j<=45) num3 += data->GetBinContent(j); // ... tra 75 e 105
}
cout << "\n";
cout << data->GetNbinsX() <<" Number of bins of the invmass histo\n";
printf("Number of Z in 60-120 %i --- 70-110 %i --- 75-105 %i \n",num1,num2,num3);
cout << "\n";
}
if(str.Contains("zYieldVsjets") && !str.Contains("Vtx")){
for(int j=1;j<=data->GetNbinsX();j++){
num1 += data->GetBinContent(j); //conto quante Z
if(j>1) num2 += data->GetBinContent(j); // ... +1,2,3,4... jets
if(j>2) num3 += data->GetBinContent(j); // ... +2,3,4... jets
if(j>3) num4 += data->GetBinContent(j); // .. if(str=="jet_pT"){
if(j>4) num5 += data->GetBinContent(j); // ... +4... jets
}
cout << "\n";
cout << data->GetNbinsX() <<" Number of bins of the zYieldVsjets histo\n";
printf("Number of Z+n jet %i --- >1 %i --- >2 %i --- >3 %i --- >4 %i \n",num1,num2,num3,num4,num5);
cout << "\n";
}
//======================
// Z + jets signal
mcf->cd("validationJEC");
if (isMu) mcf->cd("validationJECmu/");
if (isAngularAnalysis) {
mcf->cd("validationJEC/");
if (isMu) mcf->cd("validationJECmu/");
}
TH1F* mc;
gDirectory->GetObject(plot.c_str(),mc);
TH1F * hsum;
if(mc){
hsum = (TH1F*) mc->Clone();
hsum->SetTitle("hsum");
hsum->SetName("hsum");
hsum->Reset();
Double_t mcint = mc->Integral();
mc->SetFillColor(kRed);
mc->Sumw2();
if(lumiweights==0) mc->Scale(dataint/mcint);
// Blocco da propagare negli altri MC
if(zNumEvents>0.){
if(lumiweights==1) {
if (WholeStat){
if (lumiPixel) mc->Scale( dataLumi2011pix / (zNumEvents / zjetsXsect));
else mc->Scale( dataLumi2011 / (zNumEvents / zjetsXsect));
}
else{
if (RunA){
if (lumiPixel) mc->Scale( dataLumi2011Apix / (zNumEvents / zjetsXsect));
else mc->Scale( dataLumi2011A / (zNumEvents / zjetsXsect));
}
if (!RunA){
if (lumiPixel) mc->Scale( dataLumi2011Bpix / (zNumEvents / zjetsXsect));
else mc->Scale( dataLumi2011B / (zNumEvents / zjetsXsect));
}
}
}
}
else {
if(lumiweights==1) mc->Scale(zjetsScale);
}
// fin qui
if(lumiweights==1) mc->Scale(1./zwemean); // perche' i Weights non fanno 1...
mc->Rebin(rebin);
if(lumiweights==0) mc->Draw("HISTO SAMES");
hsum->Rebin(rebin);
hsum->Add(mc);
legend->AddEntry(mc,"Z+jets","f");
}
//======================
// ttbar
ttbarf->cd("validationJEC");
if (isMu) ttbarf->cd("validationJECmu/");
if (isAngularAnalysis) {
ttbarf->cd("validationJEC/");
if (isMu) ttbarf->cd("validationJECmu/");
}
TH1F* ttbar;
gDirectory->GetObject(plot.c_str(),ttbar);
if(ttbar){
ttbar->SetFillColor(kBlue);
ttbar->Sumw2();
if(ttNumEvents>0.){
if(lumiweights==1) {
if (WholeStat){
if (lumiPixel) ttbar->Scale( dataLumi2011pix / (ttNumEvents / ttbarXsect));
else ttbar->Scale( dataLumi2011 / (ttNumEvents / ttbarXsect));
}
else{
if (RunA){
if (lumiPixel) ttbar->Scale( dataLumi2011Apix / (ttNumEvents / ttbarXsect));
else ttbar->Scale( dataLumi2011A / (ttNumEvents / ttbarXsect));
}
if (!RunA){
if (lumiPixel) ttbar->Scale( dataLumi2011Bpix / (ttNumEvents / ttbarXsect));
else ttbar->Scale( dataLumi2011B / (ttNumEvents / ttbarXsect));
}
}
}
}
else {
if(lumiweights==1) ttbar->Scale(ttwemean);
}
// fin qui
if(lumiweights==1) ttbar->Scale(1./ttwemean); // perche' i Weights non fanno 1...
ttbar->Rebin(rebin);
if(lumiweights==0) ttbar->Draw("HISTO SAMES");
hsum->Rebin(rebin);
hsum->Add(ttbar);
if(lumiweights==1)legend->AddEntry(ttbar,"ttbar","f");
//////////
//Storing the bckgrounds!
//////////
cout<<str<<endl;
if (isAngularAnalysis){
if(str=="jet_pT") evaluateAndFillBackgrounds(ttbar,"jet_pT");
if(str=="jet_pT2") evaluateAndFillBackgrounds(ttbar,"jet_pT2");
if(str=="jet_pT3") evaluateAndFillBackgrounds(ttbar,"jet_pT3");
if(str=="jet_pT4") evaluateAndFillBackgrounds(ttbar,"jet_pT4");
if(str=="Jet_multi") evaluateAndFillBackgrounds(ttbar,"jet_Multiplicity");
if(str=="jet_eta") evaluateAndFillBackgrounds(ttbar,"jet_eta");
if(str=="jet_eta2") evaluateAndFillBackgrounds(ttbar,"jet_eta2");
if(str=="jet_eta3") evaluateAndFillBackgrounds(ttbar,"jet_eta3");
if(str=="jet_eta4") evaluateAndFillBackgrounds(ttbar,"jet_eta4");
if(str=="HT") evaluateAndFillBackgrounds(ttbar,"HT");
if(str=="HT_1j") evaluateAndFillBackgrounds(ttbar,"HT1");
if(str=="HT_2j") evaluateAndFillBackgrounds(ttbar,"HT2");
if(str=="HT_3j") evaluateAndFillBackgrounds(ttbar,"HT3");
if(str=="HT_4j") evaluateAndFillBackgrounds(ttbar,"HT4");
if(str=="Phi_star") evaluateAndFillBackgrounds(ttbar,"PhiStar");
}
}
//======================
// w+jets
wf->cd("validationJEC");
if (isMu) wf->cd("validationJECmu/");
if (isAngularAnalysis) {
wf->cd("validationJEC/");
if (isMu) wf->cd("validationJECmu/");
}
TH1F* w;
gDirectory->GetObject(plot.c_str(),w);
if(w){
w->SetFillColor(kViolet+2);
w->Sumw2();
if(wNumEvents>0.){
if(lumiweights==1) {
if (WholeStat){
if (lumiPixel) w->Scale( dataLumi2011pix / (wNumEvents / wjetsXsect));
else w->Scale( dataLumi2011 / (wNumEvents / wjetsXsect));
}
else{
if (RunA){
if (lumiPixel) w->Scale( dataLumi2011Apix / (wNumEvents / wjetsXsect));
else w->Scale( dataLumi2011A / (wNumEvents / wjetsXsect));
}
if (!RunA){
if (lumiPixel) w->Scale( dataLumi2011Bpix / (wNumEvents / wjetsXsect));
else w->Scale( dataLumi2011B / (wNumEvents / wjetsXsect));
}
}
}
}
else {
if(lumiweights==1) w->Scale(wwemean);
}
// fin qui
if(lumiweights==1) w->Scale(1./wwemean); // perche' i Weights non fanno 1...
w->Rebin(rebin);
if(lumiweights==0) w->Draw("HISTO SAMES");
hsum->Rebin(rebin);
hsum->Add(w);
if(lumiweights==1)legend->AddEntry(w,"W+jets","f");
}
//======================
// wz+jets
WZf->cd("validationJEC");
if (isMu) WZf->cd("validationJECmu/");
if (isAngularAnalysis) {
WZf->cd("validationJEC/");
if (isMu) WZf->cd("validationJECmu/");
}
TH1F* wz;
gDirectory->GetObject(plot.c_str(),wz);
if(wz){
wz->SetFillColor(kYellow+2);
wz->Sumw2();
if(wzEvents>0.){
if(lumiweights==1) {
if (WholeStat){
if (lumiPixel) wz->Scale( dataLumi2011pix / (wzEvents / WZXsect));
else wz->Scale( dataLumi2011 / (wzEvents / WZXsect));
}
else{
if (RunA){
if (lumiPixel) wz->Scale( dataLumi2011Apix / (wzEvents / WZXsect));
else wz->Scale( dataLumi2011A / (wzEvents / WZXsect));
}
if (!RunA){
if (lumiPixel) wz->Scale( dataLumi2011Bpix / (wzEvents / WZXsect));
else wz->Scale( dataLumi2011B / (wzEvents / WZXsect));
}
}
}
}
else {
if(lumiweights==1) wz->Scale(wzjetsScale);
}
// fin qui
if(lumiweights==1) wz->Scale(1./wzwemean); // perche' i Weights non fanno 1...
wz->Rebin(rebin);
if(lumiweights==0) wz->Draw("HISTO SAMES");
hsum->Rebin(rebin);
hsum->Add(wz);
legend->AddEntry(wz,"WZ+jets","f");
//////////
//Storing the bckgrounds!
//////////
if (isAngularAnalysis){
if(str=="jet_pT") evaluateAndFillBackgrounds(wz,"jet_pT");
if(str=="jet_pT2") evaluateAndFillBackgrounds(wz,"jet_pT2");
if(str=="jet_pT3") evaluateAndFillBackgrounds(wz,"jet_pT3");
if(str=="jet_pT4") evaluateAndFillBackgrounds(wz,"jet_pT4");
if(str=="jet_eta") evaluateAndFillBackgrounds(wz,"jet_eta");
if(str=="jet_eta2") evaluateAndFillBackgrounds(wz,"jet_eta2");
if(str=="jet_eta3") evaluateAndFillBackgrounds(wz,"jet_eta3");
if(str=="jet_eta4") evaluateAndFillBackgrounds(wz,"jet_eta4");
if(str=="Jet_multi") evaluateAndFillBackgrounds(wz,"jet_Multiplicity");
if(str=="HT") evaluateAndFillBackgrounds(wz,"HT");
if(str=="HT_1j") evaluateAndFillBackgrounds(wz,"HT1");
if(str=="HT_2j") evaluateAndFillBackgrounds(wz,"HT2");
if(str=="HT_3j") evaluateAndFillBackgrounds(wz,"HT3");
if(str=="HT_4j") evaluateAndFillBackgrounds(wz,"HT4");
if(str=="Phi_star") evaluateAndFillBackgrounds(wz,"PhiStar");
}
}
//======================
// zz+jets
ZZf->cd("validationJEC");
if (isMu) ZZf->cd("validationJECmu/");
if (isAngularAnalysis) {
ZZf->cd("validationJEC/");
if (isMu) ZZf->cd("validationJECmu/");
}
TH1F* zz;
gDirectory->GetObject(plot.c_str(),zz);
if(zz){
zz->SetFillColor(kOrange+2);
zz->Sumw2();
if(zzEvents>0.){
if(lumiweights==1) {
if (WholeStat){
if (lumiPixel) zz->Scale( dataLumi2011pix / (zzEvents / ZZXsect));
else zz->Scale( dataLumi2011 / (zzEvents / ZZXsect));
}
else{
if (RunA){
if (lumiPixel) zz->Scale( dataLumi2011Apix / (zzEvents / ZZXsect));
else zz->Scale( dataLumi2011A / (zzEvents / ZZXsect));
}
if (!RunA){
if (lumiPixel) zz->Scale( dataLumi2011Bpix / (zzEvents / ZZXsect));
else zz->Scale( dataLumi2011B / (zzEvents / ZZXsect));
}
}
}
}
else {
if(lumiweights==1) zz->Scale(zzjetsScale);
}
// fin qui
if(lumiweights==1) zz->Scale(1./zzwemean); // perche' i Weights non fanno 1...
zz->Rebin(rebin);
if(lumiweights==0) zz->Draw("HISTO SAMES");
hsum->Rebin(rebin);
hsum->Add(zz);
legend->AddEntry(zz,"ZZ+jets","f");
//////////
//Storing the bckgrounds!
//////////
if (isAngularAnalysis){
if(str=="jet_pT") evaluateAndFillBackgrounds(zz,"jet_pT");
if(str=="jet_pT2") evaluateAndFillBackgrounds(zz,"jet_pT2");
if(str=="jet_pT3") evaluateAndFillBackgrounds(zz,"jet_pT3");
if(str=="jet_pT4") evaluateAndFillBackgrounds(zz,"jet_pT4");
if(str=="jet_eta") evaluateAndFillBackgrounds(zz,"jet_eta");
if(str=="jet_eta2") evaluateAndFillBackgrounds(zz,"jet_eta2");
if(str=="jet_eta3") evaluateAndFillBackgrounds(zz,"jet_eta3");
if(str=="jet_eta4") evaluateAndFillBackgrounds(zz,"jet_eta4");
if(str=="Jet_multi") evaluateAndFillBackgrounds(zz,"jet_Multiplicity");
if(str=="HT") evaluateAndFillBackgrounds(zz,"HT");
if(str=="HT_1j") evaluateAndFillBackgrounds(zz,"HT1");
if(str=="HT_2j") evaluateAndFillBackgrounds(zz,"HT2");
if(str=="HT_3j") evaluateAndFillBackgrounds(zz,"HT3");
if(str=="HT_4j") evaluateAndFillBackgrounds(zz,"HT4");
if(str=="Phi_star") evaluateAndFillBackgrounds(zz,"PhiStar");
}
}
//======================
// ww+jets
WWf->cd("validationJEC");
if (isMu) WWf->cd("validationJECmu/");
if (isAngularAnalysis) {
WWf->cd("validationJEC/");
if (isMu) WWf->cd("validationJECmu/");
}
TH1F* ww;
gDirectory->GetObject(plot.c_str(),ww);
if(ww){
ww->SetFillColor(kBlack);
ww->Sumw2();
if(wwEvents>0.){
if(lumiweights==1) {
if (WholeStat){
if (lumiPixel) ww->Scale( dataLumi2011pix / (wwEvents / WWXsect));
else ww->Scale( dataLumi2011 / (wwEvents / WWXsect));
}
else{
if (RunA){
if (lumiPixel) ww->Scale( dataLumi2011Apix / (wwEvents / WWXsect));
else ww->Scale( dataLumi2011A / (wwEvents / WWXsect));
}
if (!RunA){
if (lumiPixel) ww->Scale( dataLumi2011Bpix / (wwEvents / WWXsect));
else ww->Scale( dataLumi2011B / (wwEvents / WWXsect));
}
}
}
}
else {
if(lumiweights==1) ww->Scale(wwjetsScale);
}
// fin qui
if(lumiweights==1) ww->Scale(1./wwwemean); // perche' i Weights non fanno 1...
ww->Rebin(rebin);
if(lumiweights==0) ww->Draw("HISTO SAMES");
hsum->Rebin(rebin);
hsum->Add(ww);
legend->AddEntry(ww,"WW+jets","f");
//////////
//Storing the bckgrounds!
//////////
if (isAngularAnalysis){
if(str=="jet_pT") evaluateAndFillBackgrounds(ww,"jet_pT");
if(str=="jet_pT2") evaluateAndFillBackgrounds(ww,"jet_pT2");
if(str=="jet_pT3") evaluateAndFillBackgrounds(ww,"jet_pT3");
if(str=="jet_pT4") evaluateAndFillBackgrounds(ww,"jet_pT4");
if(str=="jet_eta") evaluateAndFillBackgrounds(ww,"jet_eta");
if(str=="jet_eta2") evaluateAndFillBackgrounds(ww,"jet_eta2");
if(str=="jet_eta3") evaluateAndFillBackgrounds(ww,"jet_eta3");
if(str=="jet_eta4") evaluateAndFillBackgrounds(ww,"jet_eta4");
if(str=="Jet_multi") evaluateAndFillBackgrounds(ww,"jet_Multiplicity");
if(str=="HT") evaluateAndFillBackgrounds(ww,"HT");
if(str=="HT_1j") evaluateAndFillBackgrounds(ww,"HT1");
if(str=="HT_2j") evaluateAndFillBackgrounds(ww,"HT2");
if(str=="HT_3j") evaluateAndFillBackgrounds(ww,"HT3");
if(str=="HT_4j") evaluateAndFillBackgrounds(ww,"HT4");
if(str=="Phi_star") evaluateAndFillBackgrounds(ww,"PhiStar");
}
}
/// Tau
//======================
mcftau->cd("validationJEC");
if (isMu) mcftau->cd("validationJECmu/");
if (isAngularAnalysis) {
mcftau->cd("validationJEC/");
if (isMu) mcftau->cd("validationJECmu/");
}
TH1F* tau;
gDirectory->GetObject(plot.c_str(),tau);
if(tau){
tau->SetFillColor(kGreen);
tau->Sumw2();
if(zNumEvents>0.){
if(lumiweights==1) {
if (WholeStat){
if (lumiPixel) tau->Scale( dataLumi2011pix / (zNumEvents / zjetsXsect));
else tau->Scale( dataLumi2011 / (zNumEvents / zjetsXsect));
}
else{
if (RunA){
if (lumiPixel) tau->Scale( dataLumi2011Apix / (zNumEvents / zjetsXsect));
else tau->Scale( dataLumi2011A / (zNumEvents / zjetsXsect));
}
if (!RunA){
if (lumiPixel) tau->Scale( dataLumi2011Bpix / (zNumEvents / zjetsXsect));
else tau->Scale( dataLumi2011B / (zNumEvents / zjetsXsect));
}
}
}
}
else {
if(lumiweights==1) tau->Scale(zjetsScale);
}
// fin qui
if(lumiweights==1) tau->Scale(1./zwemean); // perche' i Weights non fanno 1...
tau->Rebin(rebin);
if(lumiweights==0) tau->Draw("HISTO SAMES");
hsum->Rebin(rebin);
tau->Scale(1./1000.); //aaaaaaa
hsum->Add(tau);
legend->AddEntry(tau,"#tau#tau+jets","f");
//////////
//Storing the bckgrounds!
//////////
if (isAngularAnalysis){
if(str=="jet_pT") evaluateAndFillBackgrounds(tau,"jet_pT");
if(str=="jet_pT2") evaluateAndFillBackgrounds(tau,"jet_pT2");
if(str=="jet_pT3") evaluateAndFillBackgrounds(tau,"jet_pT3");
if(str=="jet_pT4") evaluateAndFillBackgrounds(tau,"jet_pT4");
if(str=="jet_eta") evaluateAndFillBackgrounds(tau,"jet_eta");
if(str=="jet_eta2") evaluateAndFillBackgrounds(tau,"jet_eta2");
if(str=="jet_eta3") evaluateAndFillBackgrounds(tau,"jet_eta3");
if(str=="jet_eta4") evaluateAndFillBackgrounds(tau,"jet_eta4");
if(str=="Jet_multi") evaluateAndFillBackgrounds(tau,"jet_Multiplicity");
if(str=="HT") evaluateAndFillBackgrounds(tau,"HT");
if(str=="HT_1j") evaluateAndFillBackgrounds(tau,"HT1");
if(str=="HT_2j") evaluateAndFillBackgrounds(tau,"HT2");
if(str=="HT_3j") evaluateAndFillBackgrounds(tau,"HT3");
if(str=="HT_4j") evaluateAndFillBackgrounds(tau,"HT4");
if(str=="Phi_star") evaluateAndFillBackgrounds(tau,"PhiStar");
}
}
/////////
// Print the bkg contributions
////////
for(int j=0;j<bckg_leadingJetPt.size();j++){
cout<<bckg_leadingJetPt[j]<<endl;
}
//======================
// QCD EM enriched
qcd23emf->cd("validationJEC");
TH1F* qcd23emp;
gDirectory->GetObject(plot.c_str(),qcd23emp);
if(qcd23emp){
TH1D * qcdTotEM = (TH1D*) qcd23emp->Clone();
qcdTotEM->SetTitle("qcd em");
qcdTotEM->SetName("qcd em");
qcdTotEM->Reset();
qcdTotEM->Rebin(rebin);
qcd38emf->cd("validationJEC");
TH1F* qcd38emp;
gDirectory->GetObject(plot.c_str(),qcd38emp);
qcd817emf->cd("validationJEC");
TH1F* qcd817emp;
gDirectory->GetObject(plot.c_str(),qcd817emp);
qcd23emp->Rebin(rebin);
qcd23emp->Sumw2();
qcd23emp->Scale(qcd23emScale);
qcd38emp->Rebin(rebin);
qcd38emp->Sumw2();
qcd38emp->Scale(qcd38emScale);
qcd817emp->Rebin(rebin);
qcd817emp->Sumw2();
qcd817emp->Scale(qcd817emScale);
qcdTotEM->SetFillColor(kOrange+1);
qcdTotEM->Add(qcd23emp);
qcdTotEM->Add(qcd38emp);
qcdTotEM->Add(qcd817emp);
hsum->Add(qcdTotEM);
//if(lumiweights==1)legend->AddEntry(qcdTotEM,"QCD em","f");
}
//======================
// QCD bc
qcd23bcf->cd("validationJEC");
TH1F* qcd23bcp;
TH1D * qcdTotBC;
bool qcdbcempty=true;
gDirectory->GetObject(plot.c_str(),qcd23bcp);
if(qcd23bcp){
qcdTotBC = (TH1D*) qcd23bcp->Clone();
qcdTotBC->SetTitle("qcd bc");
qcdTotBC->SetName("qcd bc");
qcdTotBC->Reset();
qcdTotBC->Rebin(rebin);
qcd38bcf->cd("validationJEC");
TH1F* qcd38bcp;
gDirectory->GetObject(plot.c_str(),qcd38bcp);
qcd817bcf->cd("validationJEC");
TH1F* qcd817bcp;
gDirectory->GetObject(plot.c_str(),qcd817bcp);
qcd23bcp->Rebin(rebin);
qcd23bcp->Sumw2();
qcd23bcp->Scale(qcd23bcScale);
qcd38bcp->Rebin(rebin);
qcd38bcp->Sumw2();
qcd38bcp->Scale(qcd38bcScale);
qcd817bcp->Rebin(rebin);
qcd817bcp->Sumw2();
qcd817bcp->Scale(qcd817bcScale);
qcdTotBC->SetFillColor(kGreen+2);
qcdTotBC->Add(qcd23bcp);
qcdTotBC->Add(qcd38bcp);
qcdTotBC->Add(qcd817bcp);
hsum->Add(qcdTotBC);
if (qcdTotBC->GetEntries()>0) qcdbcempty=false;
//if(lumiweights==1)legend->AddEntry(qcdTotBC,"QCD bc","f");
}
//======================
// Add here other backgrounds
//======================
// Stacked Histogram
//if(qcd23em) hs->Add(qcdTotEM);
if(!qcdbcempty) hs->Add(qcdTotBC);
if(w) hs->Add(w);
if (ww) hs->Add(ww);
if(tau) hs->Add(tau); //Z+Jets
if (zz) hs->Add(zz);
if (wz) hs->Add(wz);
if (ttbar) hs->Add(ttbar);
if(mc) hs->Add(mc); //Z+Jets
// per avere le statistiche
if(lumiweights==1) hsum->Draw("HISTO SAME");
//======================
// Setting the stats
//pad1->Update(); // altrimenti non becchi la stat
//TPaveStats *r2;
//if(lumiweights==0) r2 = (TPaveStats*)mc->FindObject("stats");
//if(lumiweights==1) r2 = (TPaveStats*)hsum->FindObject("stats");
//r2->SetY1NDC(0.875); //Uncomment if you wonna add your statistics in the top right corner
//r2->SetY2NDC(0.75);
//r2->SetTextColor(kRed);
if(lumiweights==1) hs->Draw("HISTO SAME");
gPad->RedrawAxis();
data->Draw("E1 SAME");
//r2->Draw(); //here to reactivate the stats
legend->Draw();
TLegend* lumi = new TLegend(0.45,0.3,0.75,0.2);
lumi->SetFillColor(0);
lumi->SetFillStyle(0);
lumi->SetBorderSize(0);
//lumi->AddEntry((TObject*)0,"#int L dt =4.9 1/fb","");
lumi->Draw();
string channel;
if (isMu) channel="Z#rightarrow#mu#mu";
if (!isMu) channel="Z#rightarrow ee";
TLatex *latexLabel=CMSPrel(4.890,channel,0.55,0.85); // make fancy label
latexLabel->Draw("same");
CanvPlot->Update();
//===============//
// RATIO DATA MC //
//===============//
CanvPlot->cd();
TPad *pad2 = new TPad("pad2","pad2",0.01,0.01,0.99,0.32);
pad2->Draw();
pad2->cd();
pad2->SetTopMargin(0.01);
pad2->SetBottomMargin(0.3);
pad2->SetRightMargin(0.1);
pad2->SetFillStyle(0);
TH1D * ratio = (TH1D*) data->Clone();
ratio->SetTitle("");
ratio->SetName("ratio");
ratio->Reset();
ratio->Sumw2();
//data->Sumw2();
hsum->Sumw2(); // FIXME controlla che sia corretto questo...
ratio->SetMarkerSize(.5);
ratio->SetLineColor(kBlack);
ratio->SetMarkerColor(kBlack);
//gStyle->SetOptStat("m");
TH1F* sumMC;
hs->Draw("nostack");
sumMC=(TH1F*) hs->GetHistogram();
cout<<sumMC->GetEntries()<<endl;
ratio->Divide(data,hsum,1.,1.);
ratio->GetYaxis()->SetRangeUser(0.5,1.5);
ratio->SetMarkerSize(0.8);
//pad2->SetTopMargin(1);
//Canvas style copied from plotsHistsRatio.C
ratio->GetYaxis()->SetNdivisions(5);
ratio->GetXaxis()->SetTitleSize(0.14);
ratio->GetXaxis()->SetLabelSize(0.14);
ratio->GetYaxis()->SetLabelSize(0.11);
ratio->GetYaxis()->SetTitleSize(0.11);
ratio->GetYaxis()->SetTitleOffset(0.43);
ratio->GetYaxis()->SetTitle("ratio data/MC");
ratio->Draw("E1");
TLine *OLine = new TLine(ratio->GetXaxis()->GetXmin(),1.,ratio->GetXaxis()->GetXmax(),1.);
OLine->SetLineColor(kBlack);
OLine->SetLineStyle(2);
OLine->Draw();
TLegend* label = new TLegend(0.60,0.9,0.50,0.95);
label->SetFillColor(0);
label->SetFillStyle(0);
label->SetBorderSize(0);
//horrible mess
double binContent = 0;
double binSum = 0;
double weightSum = 0;
double binError = 1;
double totalbins = ratio->GetSize() -2;
for(unsigned int bin=1;bin<=totalbins;bin++){
binContent = ratio->GetBinContent(bin);
binError = ratio->GetBinError(bin);
if(binError!=0){
binSum += binContent/binError;
weightSum += 1./binError;
}
}
double ymean = binSum / weightSum;
//double ymean = ratio->GetMean(2);
stringstream sYmean;
sYmean << ymean;
string labeltext=sYmean.str()+" mean Y";
//label->AddEntry((TObject*)0,labeltext.c_str(),""); // mean on Y
//label->Draw();
//TPaveStats *r3 = (TPaveStats*)ratio->FindObject("stats");
//r3->SetX1NDC(0.01);
//r3->SetX2NDC(0.10);
//r3->SetY1NDC(0.20);
//r3->SetY2NDC(0.50);
//gStyle->SetOptStat("mr");
//r3->SetTextColor(kWhite);
//r3->SetLineColor(kWhite);
//r3->Draw();
CanvPlot->Update();
tmp=plotpath+plot+".png";
CanvPlot->Print(tmp.c_str());
}
else if (flag==2){
//CanvPlot.Divide(2,1);
//CanvPlot.cd(1);
// data
dataf->cd("validationJEC");
if (isMu && isAngularAnalysis) dataf->cd("validationJECmu");
gDirectory->GetObject(plot.c_str(),data2);
data2->Draw("COLZ");
gPad->Update(); // altrimenti non becchi la stat
TPaveStats *r1 = (TPaveStats*)data2->FindObject("stats");
//r1->SetX1NDC(0.70); Uncomment if you wonna draw your stat in the top right corner
//r1->SetX2NDC(0.85);
//r1->Draw();
CanvPlot->Update();
tmp=plotpath+plot+"data.png";
CanvPlot->Print(tmp.c_str());
//CanvPlot.cd(2);
// montecarlo
mcf->cd("validationJEC");
if (isMu) mcf->cd("validationJECmu/");
if (isAngularAnalysis) {
mcf->cd("validationJEC/");
if (isMu) mcf->cd("validationJECmu/");
}
gDirectory->GetObject(plot.c_str(),data2);
data2->SetMinimum(1);
data2->Draw("COLZ");
gPad->Update(); // altrimenti non becchi la stat
//TPaveStats *r2 = (TPaveStats*)data2->FindObject("stats");
//r2->SetX1NDC(0.70);
//r2->SetX2NDC(0.85);
//r2->Draw();
CanvPlot->Update();
tmp=plotpath+plot+"mc.png";
CanvPlot->Print(tmp.c_str());
}
// else { cout << "You're getting an exception! Most likely there's no histogram here... \n"; }
delete data;
delete data2;
delete hs;
//delete CanvPlot;
dataf->Close();
mcf->Close();
ttbarf->Close();
wf->Close();
qcd23emf->Close();
qcd38emf->Close();
qcd817emf->Close();
qcd23bcf->Close();
qcd38bcf->Close();
qcd817bcf->Close();
WZf->Close();
ZZf->Close();
if (isAngularAnalysis){
if (bckg_leadingJetPt.size()>0 && bckg_2leadingJetPt.size()>0 && bckg_3leadingJetPt.size()>0 && bckg_4leadingJetPt.size()>0 && bckg_JetMultiplicity.size()>0 && bckg_HT.size()>0 && bckg_leadingJetEta.size()>0 && bckg_PhiStar.size()>0 && cold){
fzj->cd();
treeBKG_->Fill();
treeBKG_->Write();
TH1F *leadhisto=new TH1F("leadhisto","leading jet background contribution",bckg_leadingJetPt.size(),0,bckg_leadingJetPt.size());
TH1F *leadhisto2=new TH1F("leadhisto2","subleading jet background contribution",bckg_leadingJetPt.size(),0,bckg_leadingJetPt.size());
TH1F *leadhisto3=new TH1F("leadhisto3","subsubleading jet background contribution",bckg_leadingJetPt.size(),0,bckg_leadingJetPt.size());
TH1F *leadhisto4=new TH1F("leadhisto4","subsubsubleading jet background contribution",bckg_leadingJetPt.size(),0,bckg_leadingJetPt.size());
TH1F *multiphisto=new TH1F("multiphisto","jet multiplicity background contribution",bckg_JetMultiplicity.size(),0,bckg_JetMultiplicity.size());
TH1F *HT=new TH1F("HT","HT background contribution",bckg_HT.size(),0,bckg_HT.size());
TH1F *HT1=new TH1F("HT1","HT background contribution when >= 1 jet",bckg_HT1.size(),0,bckg_HT1.size());
TH1F *HT2=new TH1F("HT2","HT background contribution when >= 2 jets",bckg_HT2.size(),0,bckg_HT2.size());
TH1F *HT3=new TH1F("HT3","HT background contribution when >= 3 jets",bckg_HT3.size(),0,bckg_HT3.size());
TH1F *HT4=new TH1F("HT4","HT background contribution when >= 4 jets",bckg_HT4.size(),0,bckg_HT4.size());
TH1F *leadhistoeta=new TH1F("leadhistoeta","leading jet background contribution",bckg_leadingJetEta.size(),0,bckg_leadingJetEta.size());
TH1F *leadhistoeta2=new TH1F("leadhistoeta2","subleading jet background contribution",bckg_leadingJetEta.size(),0,bckg_leadingJetEta.size());
TH1F *leadhistoeta3=new TH1F("leadhistoeta3","subsubleading jet background contribution",bckg_leadingJetEta.size(),0,bckg_leadingJetEta.size());
TH1F *leadhistoeta4=new TH1F("leadhistoeta4","subsubsubleading jet background contribution",bckg_leadingJetEta.size(),0,bckg_leadingJetEta.size());
TH1F *PhiStar=new TH1F("PhiStar","PhiStar background contribution",bckg_PhiStar.size(),0,bckg_PhiStar.size());
for (int i=0; i< bckg_leadingJetPt.size(); i++){
leadhisto->Fill(i,bckg_leadingJetPt[i]);
leadhisto2->Fill(i,bckg_2leadingJetPt[i]);
leadhisto3->Fill(i,bckg_3leadingJetPt[i]);
leadhisto4->Fill(i,bckg_4leadingJetPt[i]);
}
leadhisto->Write();
leadhisto2->Write();
leadhisto3->Write();
leadhisto4->Write();
for (int i=0; i< bckg_leadingJetEta.size(); i++){
leadhistoeta->Fill(i,bckg_leadingJetEta[i]);
leadhistoeta2->Fill(i,bckg_2leadingJetEta[i]);
leadhistoeta3->Fill(i,bckg_3leadingJetEta[i]);
leadhistoeta4->Fill(i,bckg_4leadingJetEta[i]);
}
leadhistoeta->Write();
leadhistoeta2->Write();
leadhistoeta3->Write();
leadhistoeta4->Write();
//fzj->Close();
for (int i=0; i< bckg_JetMultiplicity.size(); i++){
multiphisto->Fill(i,bckg_JetMultiplicity[i]);
}
multiphisto->Write();
///////////////
for (int i=0; i< bckg_HT.size(); i++){
HT->Fill(i,bckg_HT[i]);
}
HT->Write();
for (int i=0; i< bckg_HT1.size(); i++){
HT1->Fill(i,bckg_HT1[i]);
}
HT1->Write();
for (int i=0; i< bckg_HT2.size(); i++){
HT2->Fill(i,bckg_HT2[i]);
}
HT2->Write();
for (int i=0; i< bckg_HT3.size(); i++){
HT3->Fill(i,bckg_HT3[i]);
}
HT3->Write();
for (int i=0; i< bckg_HT4.size(); i++){
HT4->Fill(i,bckg_HT4[i]);
}
HT4->Write();
//Phi star
for (int i=0; i< bckg_PhiStar.size(); i++){
PhiStar->Fill(i,bckg_PhiStar[i]);
}
PhiStar->Write();
cold=false;
}
}
return;
}
/********************************************************************************
* Copyright (C) 2014 GSI Helmholtzzentrum fuer Schwerionenforschung GmbH *
* *
* This software is distributed under the terms of the *
* GNU Lesser General Public Licence version 3 (LGPL) version 3, *
* copied verbatim in the file "LICENSE" *
********************************************************************************/
plots(Int_t nEvents = 1000, Int_t iout=1, TString mcEngine="TGeant3")
{
// Input data definitions
//-----User Settings:-----------------------------------------------
TString MCFile ="testrun_" + mcEngine + ".root";
TString ParFile ="testparams_" + mcEngine + ".root";
TString RecoFile ="testreco_"+ mcEngine + ".root";;
// ----- Reconstruction run -------------------------------------------
FairRunAna *fRun= new FairRunAna();
fRun->SetInputFile(MCFile.Data());
fRun->AddFriend(RecoFile.Data());
FairRuntimeDb* rtdb = fRun->GetRuntimeDb();
FairParRootFileIo* parInput1 = new FairParRootFileIo();
parInput1->open(ParFile.Data());
rtdb->setFirstInput(parInput1);
TFile *f1 = TFile::Open(MCFile);
TFile *f2 = TFile::Open(RecoFile);
TTree *t1 = f1->Get("cbmsim");
TTree *t2 = f2->Get("cbmsim");
FairMCEventHeader *MCEventHeader = new FairMCEventHeader();
TClonesArray *MCTracks = new TClonesArray("FairMCTrack");
TClonesArray *TutorialDetPoints = new TClonesArray("FairTutorialDet4Point");
TClonesArray *TutorialDetHits = new TClonesArray("FairTutorialDet4Hit");
t1->SetBranchAddress("MCEventHeader.",&MCEventHeader);
t1->SetBranchAddress("MCTrack", &MCTracks);
t1->SetBranchAddress("TutorialDetPoint", &TutorialDetPoints);
t2->SetBranchAddress("TutorialDetHit", &TutorialDetHits);
FairMCTrack *MCTrack;
FairTutorialDet4Point *Point;
FairTutorialDet4Hit *Hit;
//histograms
fRun->SetOutputFile("test.ana.root");
TFile *fHist = fRun->GetOutputFile();
Float_t xrange=80.;
Float_t yrange=80.;
TH2F* dxx = new TH2F("dxx","Hit; x; Delta x;",100,-xrange,xrange,50.,-10.,10.);
TH2F* dyy = new TH2F("dyy","Hit; y; Delta y;",100,-yrange,yrange,50.,-10.,10.);
TH1F* pullx = new TH1F("pullx","Hit; pullx;",100.,-5.,5.);
TH1F* pully = new TH1F("pully","Hit; pully;",100.,-5.,5.);
TH1F* pullz = new TH1F("pullz","Hit; pullz;",50.,-10.,10.);
TH1F* pointx = new TH1F("pointx","Hit; posx;",200.,-80.,80.);
TH1F* pointy = new TH1F("pointy","Hit; posy;",200.,-80.,80.);
Int_t nMCTracks, nPoints, nHits;
Float_t x_point, y_point, z_point, tof_point, SMtype_point, mod_point, cel_point, gap_point;
Float_t x_poi, y_poi, z_poi;
Float_t SMtype_poi, mod_poi, cel_poi, gap_poi;
Float_t p_MC, px_MC, py_MC, pz_MC;
Float_t x_hit, y_hit, z_hit, dy_hit;
Int_t nevent = t1->GetEntries();
if (nevent > nEvents) nevent=nEvents;
cout << "total number of events to process: " << nevent
<<endl;
// Event loop
for (Int_t iev=0; iev< nevent; iev++) {
// get entry
t1->GetEntry(iev);
t2->GetEntry(iev);
nMCTracks = MCTracks->GetEntriesFast();
nPoints = TutorialDetPoints->GetEntriesFast();
nHits = TutorialDetHits->GetEntriesFast();
cout << " Event" << iev << ":";
cout << nMCTracks << " MC tracks ";
cout << nPoints << " points ";
cout << nHits << " Hits "<<endl;
// Hit loop
for (Int_t j =0; j<nHits; j++) {
Hit = (FairTutorialDet4Hit*) TutorialDetHits->At(j);
Int_t l = Hit->GetRefIndex();
Point = (FairTutorialDet4Point*) TutorialDetPoints->At(l);
// Point info
x_poi = Point -> GetX();
y_poi = Point -> GetY();
z_poi = Point -> GetZ();
// Hit info
x_hit = Hit->GetX();
y_hit = Hit->GetY();
z_hit = Hit->GetZ();
dy_hit = Hit->GetDy();
// Int_t flg_hit = Hit->GetFlag();
Float_t delta_x = x_poi - x_hit;
Float_t delta_y = y_poi - y_hit;
Float_t delta_z = z_poi - z_hit;
dxx ->Fill(x_poi,delta_x);
dyy ->Fill(y_poi,delta_y);
pullx ->Fill(delta_x);
pully ->Fill(delta_y);
pullz ->Fill(delta_z);
pointx ->Fill(x_hit);
pointy ->Fill(y_hit);
} // Hit loop end
} // event loop end
// save histos to file
// TFile *fHist = TFile::Open("data/auaumbias.hst.root","RECREATE");
cout << "Processing done, outflag =" <<iout << endl;
if (iout==1){
fHist->Write();
if(0){ // explicit writing
TIter next(gDirectory->GetList());
TH1 *h;
TObject* obj;
while(obj= (TObject*)next()){
if(obj->InheritsFrom(TH1::Class())){
h = (TH1*)obj;
cout << "Write histo " << h->GetTitle() << endl;
h->Write();
}
}
}
fHist->ls();
fHist->Close();
}
// ----- Finish -------------------------------------------------------
cout << endl << endl;
// Extract the maximal used memory an add is as Dart measurement
// This line is filtered by CTest and the value send to CDash
FairSystemInfo sysInfo;
Float_t maxMemory=sysInfo.GetMaxMemory();
cout << "<DartMeasurement name=\"MaxMemory\" type=\"numeric/double\">";
cout << maxMemory;
cout << "</DartMeasurement>" << endl;
timer.Stop();
Double_t rtime = timer.RealTime();
Double_t ctime = timer.CpuTime();
Float_t cpuUsage=ctime/rtime;
cout << "<DartMeasurement name=\"CpuLoad\" type=\"numeric/double\">";
cout << cpuUsage;
cout << "</DartMeasurement>" << endl;
cout << endl << endl;
cout << "Output file is " << outFile << endl;
cout << "Parameter file is " << parFile << endl;
cout << "Real time " << rtime << " s, CPU time " << ctime
<< "s" << endl << endl;
cout << "Macro finished successfully." << endl;
// ------------------------------------------------------------------------
}
string FullTitle(const TH1 &h) {
return string(h.GetTitle())
+";"+h.GetXaxis()->GetTitle()
+";"+h.GetYaxis()->GetTitle();
}
/**
* Process a single eta bin
*
* @param measured Input collection of measured data
* @param corrections Input collection of correction data
* @param method Unfolding method to use
* @param regParam Regularisation parameter
* @param out Output directory.
*
* @return Stack of histograms or null
*/
THStack* ProcessBin(TCollection* measured,
TCollection* corrections,
UInt_t method,
Double_t regParam,
TDirectory* out)
{
Printf(" Processing %s ...", measured->GetName());
// Try to get the data
TH1* inRaw = GetH1(measured, "rawDist");
TH1* inTruth = GetH1(corrections, "truth");
TH1* inTruthA = GetH1(corrections, "truthAccepted");
TH1* inTrgVtx = GetH1(corrections, "triggerVertex");
TH2* inResp = GetH2(corrections, "response");
if (!inRaw || !inTruth || !inTruthA || !inTrgVtx || !inResp)
return 0;
// Make output directory
TDirectory* dir = out->mkdir(measured->GetName());
dir->cd();
// Copy the input to the output
TH1* outRaw = static_cast<TH1*>(inRaw ->Clone("measured"));
TH1* outTruth = static_cast<TH1*>(inTruth ->Clone("truth"));
TH1* outTruthA = static_cast<TH1*>(inTruthA ->Clone("truthAccepted"));
TH1* outTrgVtx = static_cast<TH1*>(inTrgVtx ->Clone("triggerVertex"));
TH2* outResp = static_cast<TH2*>(inResp ->Clone("response"));
// Make our response matrix
RooUnfoldResponse matrix(0, 0, inResp);
// Store regularization parameter
Double_t r = regParam;
RooUnfold::Algorithm algo = (RooUnfold::Algorithm)method;
RooUnfold* unfolder = RooUnfold::New(algo, &matrix, inRaw, r);
unfolder->SetVerbose(0);
// Do the unfolding and get the result
TH1* res = unfolder->Hreco();
res->SetDirectory(0);
// Make a copy to store on the output
TH1* outUnfold = static_cast<TH1*>(res->Clone("unfolded"));
TString tit(outUnfold->GetTitle());
tit.ReplaceAll("Unfold Reponse matrix", "Unfolded P(#it{N}_{ch})");
outUnfold->SetTitle(tit);
// Clone the unfolded results and divide by the trigger/vertex
// bias correction
TH1* outCorr = static_cast<TH1*>(outUnfold->Clone("corrected"));
outCorr->Divide(inTrgVtx);
tit.ReplaceAll("Unfolded", "Corrected");
outCorr->SetTitle(tit);
// Now normalize the output to integral=1
TH1* hists[] = { outRaw, outUnfold, outCorr, 0 };
TH1** phist = hists;
while (*phist) {
TH1* h = *phist;
if (h) {
Double_t intg = h->Integral(1, h->GetXaxis()->GetXmax());
h->Scale(1. / intg, "width");
}
phist++;
}
// And make ratios
TH1* ratioTrue = static_cast<TH1*>(outCorr->Clone("ratioCorrTruth"));
tit = ratioTrue->GetTitle();
tit.ReplaceAll("Corrected", "Corrected/MC 'truth'");
ratioTrue->SetTitle(tit);
ratioTrue->Divide(outTruth);
ratioTrue->SetYTitle("P_{corrected}(#it{N}_{ch})/P_{truth}(#it{N}_{ch})");
TH1* ratioAcc = static_cast<TH1*>(outUnfold->Clone("ratioUnfAcc"));
tit = ratioAcc->GetTitle();
tit.ReplaceAll("Unfolded", "Unfolded/MC selected");
ratioAcc->SetTitle(tit);
ratioAcc->Divide(outTruthA);
ratioAcc->SetYTitle("P_{unfolded}(#it{N}_{ch})/P_{MC}(#it{N}_{ch})");
// Make a stack
tit = measured->GetName();
tit.ReplaceAll("m", "-");
tit.ReplaceAll("p", "+");
tit.ReplaceAll("d", ".");
tit.ReplaceAll("_", "<#it{#eta}<");
THStack* stack = new THStack("all", tit);
stack->Add(outTruth, "E2");
stack->Add(outTruthA, "E2");
stack->Add(outRaw, "E1");
stack->Add(outUnfold, "E1");
stack->Add(outCorr, "E1");
dir->Add(stack);
// Rest of the function is devoted to making the output look nice
outRaw ->SetDirectory(dir);
outTruth ->SetDirectory(dir);
outTruthA->SetDirectory(dir);
outTrgVtx->SetDirectory(dir);
outResp ->SetDirectory(dir);
outUnfold->SetDirectory(dir);
outCorr ->SetDirectory(dir);
outRaw ->SetMarkerStyle(20); // Measured is closed
outTruth ->SetMarkerStyle(24); // MC is open
outTruthA->SetMarkerStyle(24); // MC is open
outTrgVtx->SetMarkerStyle(20); // Derived is closed
outUnfold->SetMarkerStyle(20); // Derived is closed
outCorr ->SetMarkerStyle(20); // Derived is closed
outRaw ->SetMarkerSize(0.9);
outTruth ->SetMarkerSize(1.6);
outTruthA->SetMarkerSize(1.4);
outTrgVtx->SetMarkerSize(1.0);
outUnfold->SetMarkerSize(0.9);
outCorr ->SetMarkerSize(1.0);
outRaw ->SetMarkerColor(kColorMeasured);
outTruth ->SetMarkerColor(kColorTruth);
outTruthA->SetMarkerColor(kColorAccepted);
outTrgVtx->SetMarkerColor(kColorTrgVtx);
outUnfold->SetMarkerColor(kColorUnfolded);
outCorr ->SetMarkerColor(kColorCorrected);
outRaw ->SetFillColor(kColorError);
outTruth ->SetFillColor(kColorError);
outTruthA->SetFillColor(kColorError);
outTrgVtx->SetFillColor(kColorError);
outUnfold->SetFillColor(kColorError);
outCorr ->SetFillColor(kColorError);
outRaw ->SetFillStyle(0);
outTruth ->SetFillStyle(1001);
outTruthA->SetFillStyle(1001);
outTrgVtx->SetFillStyle(0);
outUnfold->SetFillStyle(0);
outCorr ->SetFillStyle(0);
outRaw ->SetLineColor(kBlack);
outTruth ->SetLineColor(kBlack);
outTruthA->SetLineColor(kBlack);
outTrgVtx->SetLineColor(kBlack);
outUnfold->SetLineColor(kBlack);
outCorr ->SetLineColor(kBlack);
// Legend
TLegend* l = StackLegend(stack);
l->AddEntry(outRaw, "Raw", "lp");
l->AddEntry(outTruth, "MC 'truth'", "fp");
l->AddEntry(outTruthA, "MC 'truth' accepted", "fp");
l->AddEntry(outUnfold, "Unfolded", "lp");
l->AddEntry(outCorr, "Corrected", "lp");
return stack;
}
// input: - Input file (result from TMVA)
// - use of TMVA plotting TStyle
void mvas( TString fin = "TMVA.root", HistType htype = MVAType, Bool_t useTMVAStyle = kTRUE )
{
// set style and remove existing canvas'
TMVAGlob::Initialize( useTMVAStyle );
// switches
const Bool_t Save_Images = kTRUE;
// checks if file with name "fin" is already open, and if not opens one
TFile* file = TMVAGlob::OpenFile( fin );
// define Canvas layout here!
Int_t xPad = 1; // no of plots in x
Int_t yPad = 1; // no of plots in y
Int_t noPad = xPad * yPad ;
const Int_t width = 600; // size of canvas
// this defines how many canvases we need
TCanvas *c = 0;
// counter variables
Int_t countCanvas = 0;
// search for the right histograms in full list of keys
TIter next(file->GetListOfKeys());
TKey *key(0);
while ((key = (TKey*)next())) {
if (!TString(key->GetName()).BeginsWith("Method_")) continue;
if( ! gROOT->GetClass(key->GetClassName())->InheritsFrom("TDirectory") ) continue;
TString methodName;
TMVAGlob::GetMethodName(methodName,key);
TDirectory* mDir = (TDirectory*)key->ReadObj();
TIter keyIt(mDir->GetListOfKeys());
TKey *titkey;
while ((titkey = (TKey*)keyIt())) {
if (!gROOT->GetClass(titkey->GetClassName())->InheritsFrom("TDirectory")) continue;
TDirectory *titDir = (TDirectory *)titkey->ReadObj();
TString methodTitle;
TMVAGlob::GetMethodTitle(methodTitle,titDir);
cout << "--- Found directory for method: " << methodName << "::" << methodTitle << flush;
TString hname = "MVA_" + methodTitle;
if (htype == ProbaType ) hname += "_Proba";
else if (htype == RarityType ) hname += "_Rarity";
TH1* sig = dynamic_cast<TH1*>(titDir->Get( hname + "_S" ));
TH1* bgd = dynamic_cast<TH1*>(titDir->Get( hname + "_B" ));
if (sig==0 || bgd==0) {
if (htype == MVAType)
cout << "mva distribution not available (this is normal for Cut classifier)" << endl;
else if(htype == ProbaType)
cout << "probability distribution not available (this is normal for Cut classifier)" << endl;
else if(htype == RarityType)
cout << "rarity distribution not available (this is normal for Cut classifier)" << endl;
else if(htype == CompareType)
cout << "overtraining check not available (this is normal for Cut classifier)" << endl;
else cout << endl;
}
else {
cout << endl;
// chop off useless stuff
sig->SetTitle( Form("TMVA response for classifier: %s", methodTitle.Data()) );
if (htype == ProbaType)
sig->SetTitle( Form("TMVA probability for classifier: %s", methodTitle.Data()) );
else if (htype == RarityType)
sig->SetTitle( Form("TMVA Rarity for classifier: %s", methodTitle.Data()) );
else if (htype == CompareType)
sig->SetTitle( Form("TMVA overtraining check for classifier: %s", methodTitle.Data()) );
// create new canvas
TString ctitle = ((htype == MVAType) ?
Form("TMVA response %s",methodTitle.Data()) :
(htype == ProbaType) ?
Form("TMVA probability %s",methodTitle.Data()) :
(htype == CompareType) ?
Form("TMVA comparison %s",methodTitle.Data()) :
Form("TMVA Rarity %s",methodTitle.Data()));
TString cname = ((htype == MVAType) ?
Form("output_%s",methodTitle.Data()) :
(htype == ProbaType) ?
Form("probability_%s",methodTitle.Data()) :
(htype == CompareType) ?
Form("comparison_%s",methodTitle.Data()) :
Form("rarity_%s",methodTitle.Data()));
c = new TCanvas( Form("canvas%d", countCanvas+1), ctitle,
countCanvas*50+200, countCanvas*20, width, (Int_t)width*0.78 );
// set the histogram style
TMVAGlob::SetSignalAndBackgroundStyle( sig, bgd );
// normalise both signal and background
TMVAGlob::NormalizeHists( sig, bgd );
// frame limits (choose judicuous x range)
Float_t nrms = 4;
cout << "--- Mean and RMS (S): " << sig->GetMean() << ", " << sig->GetRMS() << endl;
cout << "--- Mean and RMS (B): " << bgd->GetMean() << ", " << bgd->GetRMS() << endl;
Float_t xmin = TMath::Max( TMath::Min(sig->GetMean() - nrms*sig->GetRMS(),
bgd->GetMean() - nrms*bgd->GetRMS() ),
sig->GetXaxis()->GetXmin() );
Float_t xmax = TMath::Min( TMath::Max(sig->GetMean() + nrms*sig->GetRMS(),
bgd->GetMean() + nrms*bgd->GetRMS() ),
sig->GetXaxis()->GetXmax() );
Float_t ymin = 0;
Float_t maxMult = (htype == CompareType) ? 1.3 : 1.2;
Float_t ymax = TMath::Max( sig->GetMaximum(), bgd->GetMaximum() )*maxMult;
// build a frame
Int_t nb = 500;
TString hFrameName(TString("frame") + methodTitle);
TObject *o = gROOT->FindObject(hFrameName);
if(o) delete o;
TH2F* frame = new TH2F( hFrameName, sig->GetTitle(),
nb, xmin, xmax, nb, ymin, ymax );
frame->GetXaxis()->SetTitle( methodTitle + ((htype == MVAType || htype == CompareType) ? " response" : "") );
if (htype == ProbaType ) frame->GetXaxis()->SetTitle( "Signal probability" );
else if (htype == RarityType ) frame->GetXaxis()->SetTitle( "Signal rarity" );
frame->GetYaxis()->SetTitle("Normalized");
TMVAGlob::SetFrameStyle( frame );
// eventually: draw the frame
frame->Draw();
c->GetPad(0)->SetLeftMargin( 0.105 );
frame->GetYaxis()->SetTitleOffset( 1.2 );
// Draw legend
TLegend *legend= new TLegend( c->GetLeftMargin(), 1 - c->GetTopMargin() - 0.12,
c->GetLeftMargin() + (htype == CompareType ? 0.40 : 0.3), 1 - c->GetTopMargin() );
legend->SetFillStyle( 1 );
legend->AddEntry(sig,TString("Signal") + ((htype == CompareType) ? " (test sample)" : ""), "F");
legend->AddEntry(bgd,TString("Background") + ((htype == CompareType) ? " (test sample)" : ""), "F");
legend->SetBorderSize(1);
legend->SetMargin( (htype == CompareType ? 0.2 : 0.3) );
legend->Draw("same");
// overlay signal and background histograms
sig->Draw("samehist");
bgd->Draw("samehist");
if (htype == CompareType) {
// if overtraining check, load additional histograms
TH1* sigOv = 0;
TH1* bgdOv = 0;
TString ovname = hname += "_Train";
sigOv = dynamic_cast<TH1*>(titDir->Get( ovname + "_S" ));
bgdOv = dynamic_cast<TH1*>(titDir->Get( ovname + "_B" ));
if (sigOv == 0 || bgdOv == 0) {
cout << "+++ Problem in \"mvas.C\": overtraining check histograms do not exist" << endl;
}
else {
cout << "--- Found comparison histograms for overtraining check" << endl;
TLegend *legend2= new TLegend( 1 - c->GetRightMargin() - 0.42, 1 - c->GetTopMargin() - 0.12,
1 - c->GetRightMargin(), 1 - c->GetTopMargin() );
legend2->SetFillStyle( 1 );
legend2->SetBorderSize(1);
legend2->AddEntry(sigOv,"Signal (training sample)","P");
legend2->AddEntry(bgdOv,"Background (training sample)","P");
legend2->SetMargin( 0.1 );
legend2->Draw("same");
}
Int_t col = sig->GetLineColor();
sigOv->SetMarkerColor( col );
sigOv->SetMarkerSize( 0.7 );
sigOv->SetMarkerStyle( 20 );
sigOv->SetLineWidth( 1 );
sigOv->SetLineColor( col );
sigOv->Draw("e1same");
col = bgd->GetLineColor();
bgdOv->SetMarkerColor( col );
bgdOv->SetMarkerSize( 0.7 );
bgdOv->SetMarkerStyle( 20 );
bgdOv->SetLineWidth( 1 );
bgdOv->SetLineColor( col );
bgdOv->Draw("e1same");
ymax = TMath::Max( ymax, TMath::Max( sigOv->GetMaximum(), bgdOv->GetMaximum() )*maxMult );
frame->GetYaxis()->SetLimits( 0, ymax );
// for better visibility, plot thinner lines
sig->SetLineWidth( 1 );
bgd->SetLineWidth( 1 );
// perform K-S test
cout << "--- Perform Kolmogorov-Smirnov tests" << endl;
Double_t kolS = sig->KolmogorovTest( sigOv );
Double_t kolB = bgd->KolmogorovTest( bgdOv );
cout << "--- Goodness of signal (background) consistency: " << kolS << " (" << kolB << ")" << endl;
TString probatext = Form( "Kolmogorov-Smirnov test: signal (background) probability = %5.3g (%5.3g)", kolS, kolB );
TText* tt = new TText( 0.12, 0.74, probatext );
tt->SetNDC(); tt->SetTextSize( 0.032 ); tt->AppendPad();
}
// redraw axes
frame->Draw("sameaxis");
// text for overflows
Int_t nbin = sig->GetNbinsX();
Double_t dxu = sig->GetBinWidth(0);
Double_t dxo = sig->GetBinWidth(nbin+1);
TString uoflow = Form( "U/O-flow (S,B): (%.1f, %.1f)%% / (%.1f, %.1f)%%",
sig->GetBinContent(0)*dxu*100, bgd->GetBinContent(0)*dxu*100,
sig->GetBinContent(nbin+1)*dxo*100, bgd->GetBinContent(nbin+1)*dxo*100 );
TText* t = new TText( 0.975, 0.115, uoflow );
t->SetNDC();
t->SetTextSize( 0.030 );
t->SetTextAngle( 90 );
t->AppendPad();
// update canvas
c->Update();
// save canvas to file
TMVAGlob::plot_logo(1.058);
if (Save_Images) {
if (htype == MVAType) TMVAGlob::imgconv( c, Form("plots/mva_%s", methodTitle.Data()) );
else if (htype == ProbaType) TMVAGlob::imgconv( c, Form("plots/proba_%s", methodTitle.Data()) );
else if (htype == CompareType) TMVAGlob::imgconv( c, Form("plots/overtrain_%s", methodTitle.Data()) );
else TMVAGlob::imgconv( c, Form("plots/rarity_%s", methodTitle.Data()) );
}
countCanvas++;
}
}
}
}
//____________________________________________________________________
void DrawResCollection(TCollection* top, const TString& name)
{
TCollection* c = GetCollection(top, name, false);
if (!c) return;
THStack* s = GetStack(c, "all");
s->SetTitle("");
DrawInPad(fBody, 0, s, "nostack", kLogy);
TLegend* l = new TLegend(.5, .75, .98, .98, "P(#it{N}_{ch})");
l->SetBorderSize(0);
// l->SetBorderMode(0);
l->SetFillColor(0);
l->SetFillStyle(0);
TIter next(s->GetHists());
TH1* h = 0;
Bool_t hasTrue = false;
while ((h = static_cast<TH1*>(next()))) {
TString n(h->GetTitle());
if (n.BeginsWith("True")) { hasTrue = true; continue; }
n.ReplaceAll("Raw P(#it{N}_{ch}) in ", "");
TLegendEntry* e = l->AddEntry("dummy", n, "p");
e->SetMarkerStyle(h->GetMarkerStyle());
}
if (hasTrue) {
TLegendEntry* e = l->AddEntry("dummy", "Raw", "p");
e->SetMarkerStyle(20);
e->SetMarkerColor(kRed+1);
e = l->AddEntry("dummy", "MC truth", "p");
e->SetMarkerStyle(24);
e->SetMarkerColor(kBlue+1);
e = l->AddEntry("dummy", "MC truth selected", "p");
e->SetMarkerStyle(24);
e->SetMarkerColor(kOrange+1);
}
fBody->cd();
l->Draw();
PrintCanvas(Form("%s results", name.Data()));
// return;
TIter nextO(c);
TObject* o = 0;
while ((o = nextO())) {
Double_t etaMin = 999;
Double_t etaMax = 999;
TCollection* bin = GetEtaBin(o, etaMin, etaMax);
if (!bin) continue;
fBody->Divide(2,3);
DrawInPad(fBody, 1, GetH1(bin, "rawDist"), "", kLogy);
DrawInPad(fBody, 1, GetH1(bin, "truthAccepted", false),
"same", kSilent);
DrawInPad(fBody, 1, GetH1(bin, "truth", false),"same", kSilent|kLegend);
DrawInPad(fBody, 2, GetH1(bin, "coverage"));
DrawInPad(fBody, 3, GetH2(bin, "corr"), "colz");
DrawInPad(fBody, 4, GetH2(bin, "response", false), "colz", kLogz|kSilent);
DrawInPad(fBody, 5, GetH1(bin, "triggerVertex", false), "", kSilent);
PrintCanvas(Form("%+5.1f < #eta < %+5.1f", etaMin, etaMax));
}
}
