void piechart()
{
Float_t vals[] = {.2,1.1,.6,.9,2.3};
Int_t colors[] = {2,3,4,5,6};
Int_t nvals = sizeof(vals)/sizeof(vals[0]);
TCanvas *cpie = new TCanvas("cpie","TPie test",700,700);
cpie->Divide(2,2);
TPie *pie1 = new TPie("pie1",
"Pie with offset and no colors",nvals,vals);
TPie *pie2 = new TPie("pie2",
"Pie with radial labels",nvals,vals,colors);
TPie *pie3 = new TPie("pie3",
"Pie with tangential labels",nvals,vals,colors);
TPie *pie4 = new TPie("pie4",
"Pie with verbose labels",nvals,vals,colors);
cpie->cd(1);
pie1->SetAngularOffset(30.);
pie1->SetEntryRadiusOffset( 4, 0.1);
pie1->SetRadius(.35);
pie1->Draw("3d");
cpie->cd(2);
pie2->SetEntryRadiusOffset(2,.05);
pie2->SetEntryLineColor(2,2);
pie2->SetEntryLineWidth(2,5);
pie2->SetEntryLineStyle(2,2);
pie2->SetEntryFillStyle(1,3030);
pie2->SetCircle(.5,.45,.3);
pie2->Draw("rsc");
cpie->cd(3);
pie3->SetY(.32);
pie3->GetSlice(0)->SetValue(.8);
pie3->GetSlice(1)->SetFillStyle(3031);
pie3->SetLabelsOffset(-.1);
pie3->Draw("3d t nol");
TLegend *pieleg = pie3->MakeLegend();
pieleg->SetY1(.56); pieleg->SetY2(.86);
cpie->cd(4);
pie4->SetRadius(.2);
pie4->SetLabelsOffset(.01);
pie4->SetLabelFormat("#splitline{%val (%perc)}{%txt}");
pie4->Draw("nol <");
}
void plot_efficiencies( TFile* file, Int_t type = 2, TDirectory* BinDir)
{
// input: - Input file (result from TMVA),
// - type = 1 --> plot efficiency(B) versus eff(S)
// = 2 --> plot rejection (B) versus efficiency (S)
Bool_t __PLOT_LOGO__ = kTRUE;
Bool_t __SAVE_IMAGE__ = kTRUE;
// the coordinates
Float_t x1 = 0;
Float_t x2 = 1;
Float_t y1 = 0;
Float_t y2 = 0.8;
// reverse order if "rejection"
if (type == 2) {
Float_t z = y1;
y1 = 1 - y2;
y2 = 1 - z;
// cout << "--- type==2: plot background rejection versus signal efficiency" << endl;
}
else {
// cout << "--- type==1: plot background efficiency versus signal efficiency" << endl;
}
// create canvas
TCanvas* c = new TCanvas( "c", "the canvas", 200, 0, 650, 500 );
// global style settings
c->SetGrid();
c->SetTicks();
// legend
Float_t x0L = 0.107, y0H = 0.899;
Float_t dxL = 0.457-x0L, dyH = 0.22;
if (type == 2) {
x0L = 0.15;
y0H = 1 - y0H + dyH + 0.07;
}
TLegend *legend = new TLegend( x0L, y0H-dyH, x0L+dxL, y0H );
legend->SetTextSize( 0.05 );
legend->SetHeader( "MVA Method:" );
legend->SetMargin( 0.4 );
TString xtit = "Signal efficiency";
TString ytit = "Background efficiency";
if (type == 2) ytit = "Background rejection";
TString ftit = ytit + " versus " + xtit;
if (TString(BinDir->GetName()).Contains("multicut")){
ftit += " Bin: ";
ftit += (BinDir->GetTitle());
}
// draw empty frame
if(gROOT->FindObject("frame")!=0) gROOT->FindObject("frame")->Delete();
TH2F* frame = new TH2F( "frame", ftit, 500, x1, x2, 500, y1, y2 );
frame->GetXaxis()->SetTitle( xtit );
frame->GetYaxis()->SetTitle( ytit );
TMVAGlob::SetFrameStyle( frame, 1.0 );
frame->Draw();
Int_t color = 1;
Int_t nmva = 0;
TKey *key, *hkey;
TString hNameRef = "effBvsS";
if (type == 2) hNameRef = "rejBvsS";
TList hists;
TList methods;
UInt_t nm = TMVAGlob::GetListOfMethods( methods );
// TIter next(file->GetListOfKeys());
TIter next(&methods);
// loop over all methods
while (key = (TKey*)next()) {
TDirectory * mDir = (TDirectory*)key->ReadObj();
TList titles;
UInt_t ninst = TMVAGlob::GetListOfTitles(mDir,titles);
TIter nextTitle(&titles);
TKey *titkey;
TDirectory *titDir;
while ((titkey = TMVAGlob::NextKey(nextTitle,"TDirectory"))) {
titDir = (TDirectory *)titkey->ReadObj();
TString methodTitle;
TMVAGlob::GetMethodTitle(methodTitle,titDir);
TIter nextKey( titDir->GetListOfKeys() );
while ((hkey = TMVAGlob::NextKey(nextKey,"TH1"))) {
TH1 *h = (TH1*)hkey->ReadObj();
TString hname = h->GetName();
if (hname.Contains( hNameRef ) && hname.BeginsWith( "MVA_" )) {
h->SetLineWidth(3);
h->SetLineColor(color);
color++; if (color == 5 || color == 10 || color == 11) color++;
h->Draw("csame");
hists.Add(h);
nmva++;
}
}
}
}
while (hists.GetSize()) {
TListIter hIt(&hists);
TH1* hist(0);
Double_t largestInt=-1;
TH1* histWithLargestInt(0);
while ((hist = (TH1*)hIt())!=0) {
Double_t integral = hist->Integral(1,hist->FindBin(0.9999));
if (integral>largestInt) {
largestInt = integral;
histWithLargestInt = hist;
}
}
if (histWithLargestInt == 0) {
cout << "ERROR - unknown hist \"histWithLargestInt\" --> serious problem in ROOT file" << endl;
break;
}
legend->AddEntry(histWithLargestInt,TString(histWithLargestInt->GetTitle()).ReplaceAll("MVA_",""),"l");
hists.Remove(histWithLargestInt);
}
// rescale legend box size
// current box size has been tuned for 3 MVAs + 1 title
if (type == 1) {
dyH *= (1.0 + Float_t(nmva - 3.0)/4.0);
legend->SetY1( y0H - dyH );
}
else {
dyH *= (Float_t(nmva - 3.0)/4.0);
legend->SetY2( y0H + dyH);
}
// redraw axes
frame->Draw("sameaxis");
legend->Draw("same");
// ============================================================
if (__PLOT_LOGO__) TMVAGlob::plot_logo();
// ============================================================
c->Update();
TString fname = "plots/" + hNameRef;
if (TString(BinDir->GetName()).Contains("multicut")){
TString fprepend(BinDir->GetName());
fprepend.ReplaceAll("multicutMVA_","");
fname = "plots/" + fprepend + "_" + hNameRef;
}
if (__SAVE_IMAGE__) TMVAGlob::imgconv( c, fname );
return;
}
void NLSimpleGuiWindow::drawClarkAnalysis( const ConsentrationGraph &xGraph,
const ConsentrationGraph &yGraph,
bool isCgmsVMeter )
{
ui->tabWidget->setCurrentWidget(ui->clarkeGridTab);
cleanupClarkAnalysis();
TimeDuration cmgsDelay(0,0,0,0);
if( isCgmsVMeter )
{
TCanvas *can = ui->clarkResultsWidget->GetCanvas();
can->cd();
can->SetEditable( kTRUE );
TPaveText *delayErrorEqnPt = new TPaveText(0, 0, 1.0, 1.0, "NDC");
delayErrorEqnPt->SetBorderSize(0);
delayErrorEqnPt->SetTextAlign(12);
cmgsDelay = m_model->findCgmsDelayFromFingerStick();
double sigma = 1000.0 * m_model->findCgmsErrorFromFingerStick(cmgsDelay);
sigma = static_cast<int>(sigma + 0.5) / 10.0; //nearest tenth of a percent
string delayStr = "Delay=";
delayStr += boost::posix_time::to_simple_string(cmgsDelay).substr(3,5);
delayStr += " ";
ostringstream uncertDescript;
uncertDescript << "#sigma_{cgms}^{finger}=" << sigma << "%";
delayErrorEqnPt->AddText( uncertDescript.str().c_str() );
delayErrorEqnPt->AddText( delayStr.c_str() );
delayErrorEqnPt->Draw();
can->SetEditable( kFALSE );
can->Update();
}//if( isCgmsVMeter )
TCanvas *can = ui->clarkeErrorGridWidget->GetCanvas();
can->cd();
can->SetEditable( kTRUE );
vector<TObject *> clarkesObj;
clarkesObj = getClarkeErrorGridObjs( yGraph, xGraph, cmgsDelay, true );
assert( dynamic_cast<TH1 *>(clarkesObj[0]) );
dynamic_cast<TH1 *>(clarkesObj[0])->GetYaxis()->SetTitleOffset(1.3);
clarkesObj[0]->Draw("SCAT");
clarkesObj[1]->Draw("SCAT SAME");
clarkesObj[2]->Draw("SCAT SAME");
clarkesObj[3]->Draw("SCAT SAME");
clarkesObj[4]->Draw("SCAT SAME");
TLegend *leg = dynamic_cast<TLegend *>( clarkesObj[5] );
assert( leg );
//Now draw all the boundry lines
for( size_t i=6; i < clarkesObj.size(); ++i ) clarkesObj[i]->Draw();
can->SetEditable( kFALSE );
can->Update();
// can->ResizePad();
// ui->clarkeErrorGridWidget->Refresh();
can = ui->clarkeLegendWidget->GetCanvas();
can->cd();
leg->SetX1(-0.1);
leg->SetX2(1.1);
leg->SetY1(0.0);
leg->SetY2(1.0);
leg->Draw();
can->SetEditable( kFALSE );
can->Update();
}// void NLSimpleGuiWindow::drawPredictedClarkAnalysis()
//--------------------------------------------------------------------------------------------------
void plot(long int xStart, long int xEnd, TString text, TString pngFileName)
{
// Make sure we have the right styles
MitRootStyle::Init();
MitRootStyle::SetStyleWide();
gStyle->SetPadRightMargin(0.07); // to make sure the exponent is on the picture
// will execute a shell command to get the data
TString timeSeriesFile("timeSeriesOfRates.txt");
// Now open our database output
ifstream input;
input.open(timeSeriesFile.Data());
Int_t time=0, nConn=0, nLines=0;
Double_t rate=0, xMin=double(xStart), xMax=double(xEnd), maxRate=1.0;
// First loop to determine the boundaries (could be done in one round, dynamically)
//---------------------------------------------------------------------------------
while (1) {
// read in
input >> time >> rate >> nConn;
// check it worked
if (! input.good())
break;
//printf(" Min / Time / Max: %d %d %d\n",xStart,time,xEnd);
// check whether in our requested time window
if (xStart>0 && xStart>time)
continue;
if (xEnd>0 && xEnd<time)
continue;
// Show what we are reading
if (nLines < 5)
printf(" time=%d, rate=%8f nConnections=%d\n",time, rate, nConn);
// Determine plot maximum
if (rate > maxRate)
maxRate = rate;
if (nConn > maxRate)
maxRate = double(nConn);
nLines++;
}
input.close();
printf(" \n");
printf(" Found %d measurements.\n",nLines);
printf(" Maximum tranfer rate at: %6.2f MB/sec\n",maxRate);
printf(" \n");
// Open a canvas
TCanvas *cv = new TCanvas();
cv->Draw();
if (nLines<1) {
printf(" WARNING - no measurements selected.\n");
plotFrame(double(xStart),double(xEnd));
double dX = double(xEnd)-double(xStart);
TText *plotText = new TText(xMin-dX*0.14,0.-(maxRate*1.2*0.14),text.Data());
printf("Text size: %f\n",plotText->GetTextSize());
plotText->SetTextSize(0.04);
plotText->SetTextColor(kBlue);
plotText->Draw();
cv->SaveAs(pngFileName.Data());
return;
}
const int numVals = nLines;
double xVals[numVals];
double y1Vals[numVals];
double y2Vals[numVals];
input.open(timeSeriesFile.Data());
// Second loop to register the measured values
//--------------------------------------------
Int_t i = 0;
while (1) {
// read in
input >> time >> rate >> nConn;
// check it worked
if (!input.good())
break;
// check whether in our requested time window
if (xStart>0 && xStart>time)
continue;
if (xEnd>0 && xEnd<time)
continue;
xVals[i] = time;
y1Vals[i] = rate;
y2Vals[i] = nConn;
i++;
}
input.close();
// Make a good frame
plotFrame(xMin,xMax,maxRate);
double dX = double(xEnd)-double(xStart);
TText *plotText = new TText(xMin-dX*0.14,0.-(maxRate*1.2*0.14),text.Data());
plotText->SetTextSize(0.04);
plotText->SetTextColor(kBlue);
plotText->Draw();
// Prepare our graphs
TGraph* graph1 = new TGraph(numVals, xVals, y1Vals);
graph1->SetLineColor(2);
graph1->SetLineWidth(2);
graph1->SetMarkerColor(4);
graph1->SetMarkerStyle(21);
graph1->SetMarkerSize(0.4);
TGraph* graph2 = new TGraph(numVals, xVals, y2Vals);
graph2->SetLineColor(3);
graph2->SetLineWidth(2);
graph2->SetMarkerColor(4);
graph2->SetMarkerStyle(20);
graph2->SetMarkerSize(0.4);
// Through them into the multigraph
TMultiGraph *mg = new TMultiGraph();
mg->Add(graph1,"lp");
mg->Add(graph2,"lp");
// Draw the graphs
mg->Draw("CP");
// Add a nice legend to the picture
TLegend *leg = new TLegend(0.4,0.6,0.89,0.89);
//leg->SetTextSize(0.036);
leg->SetX1(0.15);
leg->SetX2(0.30);
leg->SetY1(0.95);
leg->SetY2(0.85);
leg->SetBorderSize(0);
leg->SetFillStyle(0);
leg->AddEntry(graph2,"number of tranfers","lp");
leg->AddEntry(graph1,"data tranfer rate","lp");
leg->Draw();
cv->SaveAs(pngFileName);
}
//--------------------------------------------------------------------------------------------------
void plot(long int xStart, long int xEnd, TString text, TString pngFileName)
{
// Make sure we have the right styles
MitStyle::Init();
MitStyle::SetStyleWide();
gStyle->SetPadRightMargin(0.07); // to make sure the exponent is on the picture
// will execute a shell command to get the data
TString timeSeriesFile("timeSeriesOfFailures.txt");
// Now open our database output
ifstream input;
input.open(timeSeriesFile.Data());
Int_t time=0, nFail=0, nLines=0;
Double_t xMin=double(xStart), xMax=double(xEnd), max=1.0;
// First loop to determine the boundaries (could be done in one round, dynamically)
//---------------------------------------------------------------------------------
while (1) {
// read in
input >> time >> nFail;
// check it worked
if (! input.good())
break;
//printf(" Min / Time / Max: %d %d %d\n",xStart,time,xEnd);
// check whether in our requested time window
if (xStart>0 && xStart>time)
continue;
if (xEnd>0 && xEnd<time)
continue;
// Show what we are reading
if (nLines < 5)
printf(" time=%d, nFails=%d\n",time, nFail);
// Determine plot maximum
if (nFail > max)
max = nFail;
nLines++;
}
input.close();
printf(" \n");
printf(" Found %d measurements.\n",nLines);
printf(" Maximum failures at: %6.2f in 90 sec\n",max);
printf(" \n");
// Open a canvas
TCanvas *cv = new TCanvas();
cv->SetLogy(kTRUE);
cv->Draw();
if (nLines<1) {
printf(" WARNING - no measurements selected.\n");
plotFrame(double(xStart),double(xEnd));
overlayFrame(text);
cv->SaveAs(pngFileName.Data());
return;
}
const int numVals = nLines;
double xVals[numVals];
double yVals[numVals];
input.open(timeSeriesFile.Data());
// Second loop to register the measured values
//--------------------------------------------
Int_t i = 0;
while (1) {
// read in
input >> time >> nFail;
// check it worked
if (!input.good())
break;
// check whether in our requested time window
if (xStart>0 && xStart>time)
continue;
if (xEnd>0 && xEnd<time)
continue;
xVals[i] = time;
yVals[i] = nFail;
i++;
}
input.close();
// Make a good frame
plotFrame(xMin,xMax,max);
// Prepare our graphs
TGraph* graph1 = new TGraph(numVals, xVals, yVals);
graph1->SetLineColor(2);
graph1->SetLineWidth(2);
graph1->SetMarkerColor(4);
graph1->SetMarkerStyle(21);
graph1->SetMarkerSize(0.4);
// Through them into the multigraph
TMultiGraph *mg = new TMultiGraph();
mg->Add(graph1,"lp");
// Draw the graphs
mg->Draw("CP");
// Add a nice legend to the picture
TLegend *leg = new TLegend(0.4,0.6,0.89,0.89);
leg->SetX1(0.15);
leg->SetX2(0.30);
leg->SetY1(0.95);
leg->SetY2(0.85);
leg->SetBorderSize(0);
leg->SetFillStyle(0);
leg->AddEntry(graph1,"number of failures","lp");
leg->Draw();
overlayFrame(text);
cv->SaveAs(pngFileName);
}
void EstimateBg_76X(bool save=0, std::string in = "",
std::string out = "/afs/cern.ch/user/j/jkarancs/public/NOTES/notes/AN-14-290/trunk/Plots/v1.0/", std::string ext="png") {
gStyle->SetOptTitle(0);
gStyle->SetOptStat(0);
bool latex = save;
bool ABCD_prime = 0;
bool TT_only = 0;
std::stringstream ss, ss2;
ss<<DPHI_CUT; ss2<<R_CUT;
std::string dphi_cut = ss.str().replace(ss.str().find("."),1,"p");
std::string r_cut = ss2.str().replace(ss2.str().find("."),1,"p");
std::string filename = in.size() ? in :
//"results/Plotter_out_2016_05_31_08h48m57_replot.root";
"results/Plotter_out_2016_06_24_14h28m51.root";
std::vector<std::string> samples[4];
//samples[0].push_back("TTJetsMGHT");
//samples[0].push_back("TTJetsMG");
//samples[0].push_back("TTJetsNLOFXFX");
//samples[0].push_back("TTNLO");
//samples[0].push_back("TTNLOHerwig");
//samples[0].push_back("TTPowheg");
//samples[0].push_back("TTPowhegmpiOff");
//samples[0].push_back("TTPowhegnoCR");
//samples[0].push_back("TTPowhegHerwig");
//+data+ samples[1].push_back("SingleElectron");
//+data+ samples[1].push_back("SingleMuon");
if (TT_only) {
samples[1].push_back("TTJetsMGHT");
samples[1].push_back("TTJetsMG");
samples[1].push_back("TTJetsNLOFXFX");
samples[1].push_back("TTNLO");
samples[1].push_back("TTNLOHerwig");
samples[1].push_back("TTPowheg");
samples[1].push_back("TTPowhegmpiOFF");
samples[1].push_back("TTPowhegnoCR");
samples[1].push_back("TTPowhegHerwig");
} else {
samples[1].push_back("TTJetsMGHT");
//samples[1].push_back("TTJetsMG");
//samples[1].push_back("TTJetsNLOFXFX");
//samples[1].push_back("TTNLO");
//samples[1].push_back("TTNLOHerwig");
//samples[1].push_back("TTPowheg");
//samples[1].push_back("TTPowhegmpiOff");
//samples[1].push_back("TTPowhegnoCR");
//samples[1].push_back("TTPowhegHerwig");
samples[1].push_back("ZJets");
samples[1].push_back("TTX");
samples[1].push_back("WJets");
samples[1].push_back("Diboson");
samples[1].push_back("Top");
samples[1].push_back("QCD");
//ZERO samples[1].push_back("TZQ");
//ZERO samples[1].push_back("ZJetsToQQ"); // Also WJetsToQQ
//ZERO samples[1].push_back("GJets");
}
//samples[1].push_back("Data");
// NTop Sideband All background summed
samples[2].push_back("All Bkg.");
// Signal in NTop bins
samples[3].push_back("T1tttt");
bool baderror = false;
double weight[] = { 0.32686, 0.0505037, 0.00921411, 6.80717, 0.354934, 0.00484915 };
int rebin = /*(R_CUT*10-int(R_CUT*10))==0 ? 10 :*/ (R_CUT*20-int(R_CUT*20))==0 ? 5 : (R_CUT*50-int(R_CUT*50))==0 ? 2 : 1;
double sideband_fit_low_range[] = { 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15, 0.15 };
int i_h_side[] = { 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 };
int i_h_signal[] = { 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
double scale_factors[] = { 1, 1, 1, 1, 1, 1, 1}; // All normal
//double scale_factors[] = { /* TT */ 1, /* W */ 1, /* Z */ 1, /* T */ 1, /* TTV */ 1, /* QCD */ 2, /* VV */ 1 }; // QCD high
//double scale_factors[] = { /* TT */ 5, /* W */ 1, /* Z */ 1, /* T */ 1, /* TTV */ 5, /* QCD */ 1, /* VV */ 1 }; // TT/TTV high
//double scale_factors[] = { /* TT */ 1, /* W */ 2, /* Z */ 2, /* T */ 2, /* TTV */ 1, /* QCD */ 1, /* VV */ 2 }; // T/V/VV high
Double_t Rranges_ABCD[][4] =
{ { DPHI_CUT, 3.2, 0.0, DPHI_CUT },
{ R_CUT_LOW-1e-10, R_CUT, R_CUT-1e-10, 1.20 },
{ R_CUT_LOW-1e-10, R_CUT, R_CUT-1e-10, 1.20 },
{ R_CUT_LOW-1e-10, R_CUT, R_CUT-1e-10, 1.20 } };
bool doFitting = false;
double sum_a = 0, sum_b = 0, sum_c = 0, sum_d = 0, sum_d_abcd = 0, sum_d_nevt = 0;
double sum_a_err = 0, sum_b_err = 0, sum_c_err = 0, sum_d_err = 0, sum_d_abcd_err = 0;
double sum_b_fit = 0, sum_d_fit = 0, sum_d_fit_comb = 0;
double sum_b_fit_err = 0, sum_d_fit_err = 0, sum_d_fit_comb_err = 0;
double comb_d = 0, comb_d_err = 0, comb_d_abcd = 0, comb_d_abcd_err = 0;
if (latex) {
printf("\\begin{table*}[htbH]\n");
printf("\\small\n");
printf("\\begin{center}\n");
printf("\\topcaption{Estimated Standard Model background yields in ABCD regions. A, B is in the sideband, C and D is the signal band, D is the signal region.\\label{tab:SMBkgEstimate}}\n");
printf("\\begin{tabular}{lrrrrrrrr}\n");
}
TFile *f = TFile::Open(filename.c_str());
for (size_t iMethod = 0; iMethod<4; ++iMethod) if (!(iMethod==0&&samples[0].size()==0)){
// Print Top row for each method
if (latex) {
if (iMethod==0) {
printf("\\hline\n");
printf("Method 2 & A & B & C & D = B*C/A & D obs. & Ratio pred./obs. & Pull & KS test\\\\\n");
} else if (iMethod==1){
printf("\\hline\n");
printf("Method 1 & A & B & C & D = B*C/A & D obs. & Ratio pred./obs. & Pull & KS test\\\\\n");
}
printf("\\hline\n");
} else {
std::stringstream r_sb_cut;
if (R_CUT_LOW==0) r_sb_cut<<"R<"<<R_CUT;
else r_sb_cut<<R_CUT_LOW<<"<R<"<<R_CUT;
const char* prime = ABCD_prime ? "'" : "";
//if (iMethod==0) printf("| *Sample* | *A (DPhi>2.8, SB)* | *B (DPhi<2.8, SB)* | *C (DPhi>2.8, Sig.B.)* | - | *D = B*C/A pred.* | *D (DPhi<2.8, Sig.B.) obs.* | *Ratio pred./obs.* |\n");
//else if (iMethod==1) printf("| *Sample* | *A (R<%1.1f, SB)* | *B (R>%1.1f, SB)* | *C (R<%1.1f, Sig.B.)* | *D = B (R fit, SB) * C/A pred.* | *D = B*C/A pred.* | *D (R>%1.1f, Sig.B.) obs.* | *Ratio pred./obs.* | \n", R_CUT, R_CUT, R_CUT, R_CUT);
if (iMethod==0) printf("| *Sample* | *A (DPhi>%1.1f, %s)* | *B (DPhi<%1.1f, %s)* | *C (DPhi>%1.1f, R>0.4)* | *D = B*C/A pred.* | *D (DPhi<%1.1f, R>0.4) obs.* | *Ratio pred./obs.* | *Pull (pred-obs)/error* | *KS test* |\n", DPHI_CUT, r_sb_cut.str().c_str(), DPHI_CUT, r_sb_cut.str().c_str(), DPHI_CUT, DPHI_CUT);
else if (iMethod==1) printf("| *Sample* | *A%s (%s, <2 tag)* | *B%s (R>%1.1f, <2 tag)* | *C%s (%s, 2 tag)* | *D%s = B%s*C%s/A%s pred.* | *D%s (R>%1.1f, 2 tag) obs.* | *Ratio pred./obs.* | *Pull (pred-obs)/error* | *KS test* |\n", prime, r_sb_cut.str().c_str(), prime, R_CUT, prime, r_sb_cut.str().c_str(), prime, prime, prime, prime, prime, R_CUT);
}
TH1D *h_side_sum, *h_signal_sum;
for (size_t iSample = 0; iSample<samples[iMethod].size(); ++iSample) {
std::string canname =
iMethod==0 ? std::string("DPhiBins")+(ABCD_prime ? "/RBins_0To1HadTop_" : "/RBins_2HadTop_")+samples[iMethod][iSample] :
iMethod==1 ? std::string("RFine/Tau32Cuts_")+(ABCD_prime ? "Fail" : "Pass")+"DPhiCut_"+samples[iMethod][iSample] :
iMethod==2 ? std::string("RFine/Tau32Cuts_")+(ABCD_prime ? "Fail" : "Pass")+"DPhiCut_Background" :
iMethod==3 ? std::string("RFine/Tau32Cuts_")+(ABCD_prime ? "Fail" : "Pass")+"DPhiCut_"+samples[iMethod][iSample] : "";
TCanvas *can = (TCanvas*)(f->Get(canname.c_str()));
can = (TCanvas*)can->Clone();
can->Draw();
TH1D *h_side = (TH1D*)can->GetListOfPrimitives()->At(i_h_side[iMethod]);
TH1D *h_signal = (TH1D*)can->GetListOfPrimitives()->At(i_h_signal[iMethod]);
// Simulate different cross section by scaling a certain background
if (iMethod==1) {
TH1D *h_side_temp_scaled = (TH1D*)h_side->Clone(); h_side_temp_scaled->Scale(scale_factors[iSample]);
TH1D *h_signal_temp_scaled = (TH1D*)h_signal->Clone(); h_signal_temp_scaled->Scale(scale_factors[iSample]);
if (iSample==0) {
h_side_sum = h_side_temp_scaled;
h_signal_sum = h_signal_temp_scaled;
} else {
h_side_sum->Add(h_side_temp_scaled);
h_signal_sum->Add(h_signal_temp_scaled);
}
} else if (iMethod==2) {
h_side = h_side_sum;
h_signal = h_signal_sum;
}
TH1D *h_pred =(TH1D*)h_side->Clone();
if (iMethod!=0&&rebin>1) { h_side->Rebin(rebin); h_signal->Rebin(rebin); h_pred->Rebin(rebin); }
TLegend *leg = (TLegend*)can->GetListOfPrimitives()->At(can->GetListOfPrimitives()->GetEntries()-1);
leg->SetX1(0.35); leg->SetX2(0.65); leg->SetY1(0.6);
// Add ratio plot
int y1 = 350;
int y2 = 150;
int mid2 = 10;
can->Divide(1,2);
// Pad 1 (80+500+20 x 40+500)
TVirtualPad* p = can->cd(1);
p->SetPad(0,(y2+60+mid2)/(y1+y2+100.0+mid2),1,1);
p->SetTopMargin(40.0/(y1+40));
p->SetBottomMargin(0);
p->SetRightMargin(0.05);
p->SetLogy(1);
h_side->GetYaxis()->SetRangeUser(1.00001e-4,1e4);
h_side->Draw("HIST");
h_signal->Draw("SAMEHISTE1");
leg->Draw();
// Pad 2 (80+500+20 x 200+60)
p = can->cd(2);
p->SetGrid(0,1);
p->SetPad(0,0,1,(y2+60+mid2)/(y1+y2+100.0+mid2));
p->SetTopMargin(((float)mid2)/(y2+60+mid2));
p->SetBottomMargin(60.0/(y2+60+mid2));
p->SetRightMargin(0.05);
TH1D* ratio = (TH1D*)h_signal->Clone();
TH1D* div = (TH1D*)h_side->Clone();
//ratio->Scale(1/ratio->GetSumOfWeights());
double sum_bins_ratio = iMethod==0 ? ratio->Integral():
ratio->Integral(ratio->FindBin(R_CUT_LOW),ratio->FindBin(Rranges_ABCD[iMethod][3]));
ratio->Scale(1/sum_bins_ratio);
ratio->SetTitleSize(32.0/(y2+60+mid2),"xyz");
ratio->SetLabelSize(20.0/(y2+60+mid2),"xyz");
//ratio->Scale(1/div->GetSumOfWeights());
double sum_bins_div = iMethod==0 ? div->Integral():
div->Integral(div->FindBin(R_CUT_LOW),div->FindBin(Rranges_ABCD[iMethod][3]));
div->Scale(1/sum_bins_div);
ratio->Divide(div);
//ratio->GetYaxis()->SetRangeUser(0,2);
ratio->GetXaxis()->SetTitleOffset(0.7);
ratio->GetYaxis()->SetNdivisions(305);
ratio->GetYaxis()->SetTitle("Ratio (Norm.)");
ratio->GetYaxis()->SetTitleOffset(0.4);
ratio->SetTitleSize(24.0/(y2+60+mid2),"y");
ratio->SetTitle("");
ratio->SetMarkerStyle(20);
ratio->SetMarkerColor(1);
ratio->SetLineColor(1);
ratio->GetYaxis()->SetRangeUser(0,4);
ratio->Draw("PE1");
TLine* l = new TLine(ratio->GetXaxis()->GetXmin(), 1, ratio->GetXaxis()->GetXmax(), 1);
l->SetLineWidth(2);
//l->SetLineColor(2);
l->SetLineStyle(2);
l->Draw();
gPad->Update();
// Fit ratio
//TF1 *fit_ratio;
//if (iMethod==1) {
// fit_ratio = new TF1("fit_ratio","pol0", Rranges_ABCD[iMethod][0], Rranges_ABCD[iMethod][1]);
// fit_ratio->SetLineColor(1);
// ratio->Fit("fit_ratio","RE");
// fit_ratio->SetRange(Rranges_ABCD[iMethod][0], Rranges_ABCD[iMethod][2]);
// fit_ratio->Draw("SAME");
//}
p = can->cd(1);
// calculate integrals
double integral[2][2] = { { 0, 0 }, { 0, 0 } };
double integral_error[2][2] = { { 0, 0 }, { 0, 0 } };
double nevt[2][2] = { { 0, 0 }, { 0, 0 } };
//std::cout<<samples[iMethod][iSample]<<":"<<std::endl;
for (int i=0; i<2; ++i) {
for (int bin=1; bin<=h_side->GetNbinsX(); ++bin) {
if (h_signal->GetXaxis()->GetBinLowEdge(bin)>=Rranges_ABCD[iMethod][i*2] &&
h_signal->GetXaxis()->GetBinUpEdge(bin)<=Rranges_ABCD[iMethod][i*2+1]) {
//std::cout<<bin<<"="<<h_side->GetBinCenter(bin);
//if (i==0) std::cout<<" in, ";
//else std::cout<<" out, ";
double c0 = h_side->GetBinContent(bin), c1 = h_signal->GetBinContent(bin);
double e0 = h_side->GetBinError(bin), e1 = h_signal->GetBinError(bin);
//std::cout<<h_signal->GetBinError(bin)<<" "<<sqrt(c1*weight[iSample])<<std::endl;
if (baderror&&iMethod==1) {
e0 = sqrt(c0*weight[iSample]);
e1 = sqrt(c1*weight[iSample]);
}
nevt[0][i] += (int)(c0*c0/(e0*e0) + 0.5);
nevt[1][i] += (int)(c1*c1/(e1*e1) + 0.5);
integral[0][i] += c0;
integral[1][i] += c1;
//if (iMethod==1) { // weight bin by projected ratio (correction)
// double bincent = h_signal->GetXaxis()->GetBinLowEdge(bin);
// integral[0][1] *= fit_ratio->Eval(bincent);
//}
integral_error[0][i] += e0*e0;
integral_error[1][i] += e1*e1;
//if (iSample==0&&e1>0) std::cout<<bin<<" "<<c1<<" +- "<<e1*e1<<" nevt = "<<((int)(c1*c1/(e1*e1) + 0.5))<<std::endl;
}
}
//if (iSample==1&&i==1) std::cout<<integral[1][i]<<" +- "<<integral_error[1][i]<<std::endl;
integral_error[0][i] = sqrt(integral_error[0][i]);
integral_error[1][i] = sqrt(integral_error[1][i]);
}
//std::cout<<nevt[1][1]<<std::endl;
// predict yields using 2 methods (ABCD and constrained R-shape fit method combined)
// ABCD method
double a = integral[0][0], b = integral[0][1], c = integral[1][0], d = integral[1][1];
double a_err = integral_error[0][0], b_err = integral_error[0][1], c_err = integral_error[1][0], d_err = integral_error[1][1];
// Calculate error
// z = x / y -> z_err = sqrt( (x*x*y_err*y_err + y*y*x_err*x_err)/(y*y*y*y) )
// z = x * y -> z_err = sqrt ( x*x*y_err*y_err + y*y*x_err*x_err )
double c_per_a_err = sqrt((c*c*a_err*a_err + a*a*c_err*c_err)/(a*a*a*a));
double d_abcd = b * (c/a), d_abcd_err = sqrt(b*b*c_per_a_err*c_per_a_err + (c/a)*(c/a)*b_err*b_err);
double d_nevt = nevt[1][1];
double d_ratio = d_abcd / d;
double d_ratio_err = sqrt((d_err/d)*(d_err/d) + (d_abcd_err/d_abcd)*(d_abcd_err/d_abcd))*d_ratio;
double d_pull = (d_abcd-d)/sqrt(d_abcd_err*d_abcd_err + d_err*d_err);
// Scaled plot
h_pred->Scale(c/a);
h_pred->SetLineColor(1);
h_pred->SetLineStyle(2);
h_pred->Draw("SAMEHIST");
leg->AddEntry(h_pred, "Prediction (ABCD)", "l");
double fit_integral[2][2], fit_integral_error[2][2], d_fit_comb = 0, d_fit_comb_err = 0;
if (iMethod==1) {
// Fit in the full range of NTop Sideband
// Do fitting and calculate integrals
TF1 *fit_side = new TF1("NTopSide_fit","exp([0]+[1]*x)", iMethod==2 ? 0.2 : sideband_fit_low_range[iSample], Rranges_ABCD[iMethod][3]);
fit_side->SetLineColor(h_side->GetLineColor());
h_side->Fit("NTopSide_fit","QRE");
//fit_side->Draw("SAME");
double Rranges_ACfit[3] = { sideband_fit_low_range[iSample], Rranges_ABCD[iMethod][2], Rranges_ABCD[iMethod][3] };
for (int i=0; i<2; ++i) {
fit_integral[0][i] = fit_side->Integral(Rranges_ACfit[i], Rranges_ACfit[i+1])/h_signal->GetXaxis()->GetBinWidth(1);
fit_integral_error[0][i] = fit_side->IntegralError(Rranges_ACfit[i], Rranges_ACfit[i+1])/h_signal->GetXaxis()->GetBinWidth(1);
}
double par0 = fit_side->GetParameter(0), par0_error = fit_side->GetParError(0);
double par1 = fit_side->GetParameter(1), par1_error = fit_side->GetParError(1);
double par1min, par1max; fit_side->GetParLimits(1, par1min, par1max);
// Fit in the Signal region
// Fitting in sideband, get B area under curve and scale by C/A
TF1 *fit_signal = new TF1("NTopSignal_RSide_fit","exp([0]+[1]*x)", Rranges_ACfit[0], Rranges_ABCD[iMethod][3]);
fit_signal->SetLineColor(h_signal->GetLineColor());
//fit_signal->SetParameter(1, par1);
//fit_signal->SetParLimits(1, par1min, par1max);
h_signal->Fit("NTopSignal_RSide_fit","QREB");
//fit_signal->Draw("SAME");
for (int i=0; i<2; ++i) {
fit_integral[1][i] = fit_signal->Integral(Rranges_ACfit[i], Rranges_ACfit[i+1])/h_signal->GetXaxis()->GetBinWidth(1);
fit_integral_error[1][i] = fit_signal->IntegralError(Rranges_ACfit[i], Rranges_ACfit[i+1])/h_signal->GetXaxis()->GetBinWidth(1);
}
d_fit_comb = fit_integral[0][1] * (c/a);
d_fit_comb_err = sqrt(fit_integral[0][1]*fit_integral[0][1]*c_per_a_err*c_per_a_err + (c/a)*(c/a)*fit_integral_error[0][1]*fit_integral_error[0][1]);
TF1 *fit_pred = new TF1("Predicted_fit","exp([0]+[1]*x)", Rranges_ACfit[0], Rranges_ACfit[2]);
fit_pred->SetLineColor(1);
fit_pred->SetLineStyle(2);
fit_pred->FixParameter(0, par0+std::log(c/a));
fit_pred->FixParameter(1, par1);
h_signal->Fit("Predicted_fit","QREB+");
//fit_pred->Draw("SAME");
}
// Save plot
if (iMethod==3) samples[iMethod][iSample] = "T1tttt";
std::string name = samples[iMethod][iSample];
if (iMethod==2) name = "AllBkg";
if (save) can->SaveAs((out+"BkgEst/ABCD_closure_"+name+"."+ext).c_str());
// Check compatibility of prediction to observed distribution
double ks_test = h_pred->KolmogorovTest(h_signal);
if (iMethod==1) {
sum_a += a; sum_b += b; sum_c += c; sum_d += d;
sum_a_err += a_err*a_err; sum_b_err += b_err*b_err; sum_c_err += c_err*c_err; sum_d_err += d_err*d_err;
sum_d_abcd += d_abcd; sum_d_abcd_err += d_abcd_err*d_abcd_err;
sum_b_fit += fit_integral[0][1]; sum_b_fit_err += fit_integral_error[0][1]*fit_integral_error[0][1];
sum_d_fit += fit_integral[1][1]; sum_d_fit_err += fit_integral_error[1][1]*fit_integral_error[1][1];
sum_d_fit_comb += d_fit_comb; sum_d_fit_comb_err += d_fit_comb_err*d_fit_comb_err;
sum_d_nevt += d_nevt;
//printf(" %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f |\n", d_fit_comb, d_fit_comb_err, d_abcd, d_abcd_err, d, d_err, d_ratio, d_ratio_err);
}
if (latex) {
printf("%s & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ &", samples[iMethod][iSample].c_str(), a, a_err, b, b_err, c, c_err);
printf(" $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & %.2f & %.2f \\\\\n", d_abcd, d_abcd_err, d, d_err, d_ratio, d_ratio_err, d_pull, ks_test);
} else {
printf("| %s | %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f |", samples[iMethod][iSample].c_str(), a, a_err, b, b_err, c, c_err);
printf(" %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f | %.2f |\n", d_abcd, d_abcd_err, d, d_err, d_ratio, d_ratio_err, d_pull, ks_test);
}
// Combining best methods
if ((iMethod==0&&iSample==0)||(iMethod==1&&iSample!=0)) {
comb_d_abcd += d_abcd; comb_d += d; comb_d_abcd_err += d_abcd_err*d_abcd_err; comb_d_err += d_err*d_err;
}
}
if (iMethod==1) {
sum_a_err = sqrt(sum_a_err); sum_b_err = sqrt(sum_b_err); sum_c_err = sqrt(sum_c_err); sum_d_err = sqrt(sum_d_err);
sum_b_fit_err = sqrt(sum_b_fit_err); sum_d_fit_err = sqrt(sum_d_fit_err); sum_d_fit_comb_err = sqrt(sum_d_fit_comb_err);
double sum_d_ratio = sum_d_abcd / sum_d;
double sum_d_ratio_err = sqrt((sum_d_err/sum_d)*(sum_d_err/sum_d) + (sum_d_abcd_err/sum_d_abcd)*(sum_d_abcd_err/sum_d_abcd))*sum_d_ratio;
double sum_d_pull = (sum_d_abcd-sum_d)/sqrt(sum_d_abcd_err*sum_d_abcd_err + sum_d_err*sum_d_err);
if (latex) {
printf("\\hline\n");
printf("Sum Bkg. & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ &", sum_a, sum_a_err, sum_b, sum_b_err, sum_c, sum_c_err);
printf(" $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & %.2f & \\\\\n", sum_d_abcd, sum_d_abcd_err, sum_d, sum_d_err, sum_d_ratio, sum_d_ratio_err, sum_d_pull);
} else {
//printf("| Sum Bkg.| %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f |", sum_a, sum_a_err, sum_b_fit, sum_b_fit_err, sum_b, sum_b_err, sum_c, sum_c_err);
printf("| Sum Bkg.| %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f |", sum_a, sum_a_err, sum_b, sum_b_err, sum_c, sum_c_err);
//printf(" %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f |\n", sum_d_fit_comb, sum_d_fit_comb_err, sum_d_abcd, sum_d_abcd_err, sum_d, sum_d_err, sum_d_ratio, sum_d_ratio_err);
printf(" %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f | - |\n", sum_d_abcd, sum_d_abcd_err, sum_d, sum_d_err, sum_d_ratio, sum_d_ratio_err, sum_d_pull);
}
} else if (iMethod==2&&samples[0].size()) {
double comb_d_ratio = comb_d_abcd / comb_d;
double comb_d_ratio_err = sqrt((comb_d_err/comb_d)*(comb_d_err/comb_d) + (comb_d_abcd_err/comb_d_abcd)*(comb_d_abcd_err/comb_d_abcd))*comb_d_ratio;
double comb_d_pull = (comb_d_abcd-comb_d)/sqrt(comb_d_abcd_err*comb_d_abcd_err + comb_d_err*comb_d_err);
if (latex) {
printf("\\hline\n");
printf("\\hline\n");
printf("Combined Bkg. & & & & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & $%.2f \\pm %.2f$ & %.2f & \\\\\n", comb_d_abcd, comb_d_abcd_err, comb_d, comb_d_err, comb_d_ratio, comb_d_ratio_err, comb_d_pull);
printf("\\hline\n");
} else {
printf("| Combined Bkg.| | | | %.2f +- %.2f | %.2f +- %.2f | %.2f +- %.2f | %.2f | - |\n", comb_d_abcd, comb_d_abcd_err, comb_d, comb_d_err, comb_d_ratio, comb_d_ratio_err, comb_d_pull);
}
}
}
if (latex) {
printf("\\hline\n");
printf("\\end{tabular}\n");
printf("\\end{center}\n");
printf("\\end{table*}\n");
}
if (save) gApplication->Terminate();
}
void ptBestFit(float BIN_SIZE=5.0,bool BLIND=false,TString MASS,TString NAME)
{
gROOT->ProcessLine(".x ../../common/styleCMSTDR.C");
gSystem->Load("libHiggsAnalysisCombinedLimit.so");
gROOT->ForceStyle();
gStyle->SetOptStat(0);
gStyle->SetOptTitle(0);
gROOT->SetBatch(1);
gStyle->SetPadRightMargin(0.04);
gStyle->SetPadLeftMargin(0.16);
gStyle->SetPadTopMargin(0.06);
gStyle->SetPadBottomMargin(0.10);
gStyle->SetTitleFont(42,"XY");
gStyle->SetTitleSize(0.0475,"XY");
gStyle->SetTitleOffset(0.9,"X");
gStyle->SetTitleOffset(1.5,"Y");
gStyle->SetLabelSize(0.0375,"XY");
RooMsgService::instance().setSilentMode(kTRUE);
for(int i=0;i<2;i++) {
RooMsgService::instance().setStreamStatus(i,kFALSE);
}
float XMIN = 80;
float XMAX = 200;
TFile *f1 = TFile::Open("datacards/datacard_m"+MASS+"_"+NAME+".root");
TFile *f2 = TFile::Open("combine/mlfit.vbfHbb_"+NAME+"_mH"+MASS+".root");
TFile *f3 = TFile::Open("root/sig_shapes_workspace_B80-200.root");
TFile *f4 = TFile::Open("root/data_shapes_workspace_"+NAME+".root");
RooWorkspace *w = (RooWorkspace*)f1->Get("w");
//w->Print();
RooAbsPdf *bkg_model = (RooAbsPdf*)w->pdf("model_s");
RooFitResult *res_s = (RooFitResult*)f2->Get("fit_s");
RooFitResult *res_b = (RooFitResult*)f2->Get("fit_b");
RooRealVar *rFit = dynamic_cast<RooRealVar *>(res_s->floatParsFinal()).find("r");
RooDataSet *data = (RooDataSet*)w->data("data_obs");
int nparS=0,nparB=0;
cout << res_s->floatParsFinal().getSize() << endl;
cout << res_b->floatParsFinal().getSize() << endl;
nparS = res_s->floatParsFinal().getSize();
nparB = res_b->floatParsFinal().getSize();
float chi2sumS = 0.;
float chi2sumB = 0.;
int nparsum = 0;
// if (BLIND) {
// res_b->Print();
// }
// else {
// res_s->Print();
// }
w->allVars().assignValueOnly(res_s->floatParsFinal());
// w->Print();
// w->allVars()->Print();
RooWorkspace *wSig = (RooWorkspace*)f3->Get("w");
RooWorkspace *wDat = (RooWorkspace*)f4->Get("w");
const RooSimultaneous *sim = dynamic_cast<const RooSimultaneous *> (bkg_model);
const RooAbsCategoryLValue &cat = (RooAbsCategoryLValue &) sim->indexCat();
TList *datasets = data->split(cat,true);
TIter next(datasets);
//int count = 0;
for(RooAbsData *ds = (RooAbsData*)next();ds != 0; ds = (RooAbsData*)next()) {
//if (count > 0) return 0;
//count++;
RooAbsPdf *pdfi = sim->getPdf(ds->GetName());
RooArgSet *obs = (RooArgSet*)pdfi->getObservables(ds);
RooRealVar *x = dynamic_cast<RooRealVar *>(obs->first());
RooRealVar *yield_vbf = (RooRealVar*)wSig->var("yield_signalVBF_mass"+MASS+"_"+TString(ds->GetName()));
RooRealVar *yield_gf = (RooRealVar*)wSig->var("yield_signalGF_mass"+MASS+"_"+TString(ds->GetName()));
TString ds_name(ds->GetName());
//----- get the QCD normalization -----------
RooRealVar *qcd_norm_final = dynamic_cast<RooRealVar *>(res_s->floatParsFinal()).find("CMS_vbfbb_qcd_norm_"+ds_name);
RooRealVar *qcd_yield = (RooRealVar*)wDat->var("yield_data_"+ds_name);
float Nqcd = exp(log(1.5)*qcd_norm_final->getVal())*qcd_yield->getVal();
float eNqcd = log(1.5)*qcd_norm_final->getError()*Nqcd;
cout<<"QCD normalization = "<<Nqcd<<" +/- "<<eNqcd<<endl;
TH1 *hCoarse = (TH1*)ds->createHistogram("coarseHisto_"+ds_name,*x);
float norm = hCoarse->Integral();
int rebin = BIN_SIZE/hCoarse->GetBinWidth(1);
hCoarse->Rebin(rebin);
float MIN_VAL = TMath::Max(0.9*hCoarse->GetBinContent(hCoarse->GetMinimumBin()),1.0);
float MAX_VAL = 1.3*hCoarse->GetBinContent(hCoarse->GetMaximumBin());
RooDataHist ds_coarse("ds_coarse_"+ds_name,"ds_coarse_"+ds_name,*x,hCoarse);
TH1F *hBlind = (TH1F*)hCoarse->Clone("blindHisto_"+ds_name);
for(int i=0;i<hBlind->GetNbinsX();i++) {
double x0 = hBlind->GetBinCenter(i+1);
if (x0 > 100 && x0 < 150) {
hBlind->SetBinContent(i+1,0);
hBlind->SetBinError(i+1,0);
}
}
RooDataHist ds_blind("ds_blind_"+ds_name,"ds_blind_"+ds_name,*x,hBlind);
RooHist *hresid,*hresid0;
RooPlot *frame1 = x->frame();
RooPlot *frame2 = x->frame();
if (BLIND) {
//cout << "Blind case: " << ds_coarse.GetName() << endl;
ds_coarse.plotOn(frame1,LineColor(0),MarkerColor(0));
pdfi->plotOn(frame1,Components("shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name),VisualizeError(*res_s,1,kTRUE),FillColor(0),MoveToBack());
pdfi->plotOn(frame1,Components("shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name),LineWidth(2),LineStyle(3));
ds_blind.plotOn(frame1);
hresid = frame1->residHist();
frame2->addPlotable(hresid,"pE1");
}
else {
//cout << "Non-blind case: " << ds_coarse.GetName() << endl;
ds_coarse.plotOn(frame1);
pdfi->plotOn(frame1);
//cout << pdfi->getParameters(ds_coarse)->selectByAttrib("Constant",kFALSE)->getSize() << endl;
cout<<"chi2/ndof (bkg+sig) = "<<frame1->chiSquare()<<endl;
cout << ds_coarse.numEntries() << endl;
chi2sumS += frame1->chiSquare()*ds_coarse.numEntries();
nparsum += ds_coarse.numEntries();
//hresid0 = frame1->residHist();
//pdfi->plotOn(frame1,VisualizeError(*res_s,1,kTRUE),FillColor(0),MoveToBack());
pdfi->plotOn(frame1,Components("shapeBkg_qcd_"+ds_name),LineWidth(2),LineStyle(5),LineColor(kGreen+2));
pdfi->plotOn(frame1,Components("shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name),LineWidth(2),LineStyle(2),LineColor(kBlack));
cout<<"chi2/ndof (bkg) = "<<frame1->chiSquare()<<endl;
chi2sumB += frame1->chiSquare()*ds_coarse.numEntries();
pdfi->plotOn(frame1,Components("shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name),LineWidth(2),LineStyle(2),LineColor(kBlack),VisualizeError(*res_s,1,kTRUE),FillColor(0),MoveToBack());
hresid = frame1->residHist();
frame2->addPlotable(hresid,"pE1");
float yield_sig = rFit->getValV()*(yield_vbf->getValV()+yield_gf->getValV());
RooAbsPdf *signal_pdf = (RooAbsPdf*)w->pdf("shapeSig_qqH_"+ds_name);
signal_pdf->plotOn(frame2,LineWidth(2),LineColor(kRed),Normalization(yield_sig,RooAbsReal::NumEvent),MoveToBack());
}
// hresid0->Print();
// hresid->Print();
// double x2,y2;
// for (int i=0; i<3; ++i) {
// hresid0->GetPoint(i,x2,y2);
// cout << "BKG+SIG\t" << x2 << "\t" << y2 << endl;
// hresid->GetPoint(i,x2,y2);
// cout << "BKG\t" << x2 << "\t" << y2 << endl;
// ds_coarse.get(i);
// cout << ds_coarse.weightError(RooAbsData::SumW2) << endl;
// cout << endl;
// }
TCanvas* canFit = new TCanvas("Higgs_fit_"+ds_name,"Higgs_fit_"+ds_name,900,750);
canFit->cd(1)->SetBottomMargin(0.4);
frame1->SetMinimum(MIN_VAL);
frame1->SetMaximum(MAX_VAL);
frame1->GetYaxis()->SetNdivisions(510);
frame1->GetXaxis()->SetTitleSize(0);
frame1->GetXaxis()->SetLabelSize(0);
frame1->GetYaxis()->SetTitle(TString::Format("Events / %1.1f GeV",BIN_SIZE));
frame1->Draw();
gPad->Update();
TList *list = (TList*)gPad->GetListOfPrimitives();
//list->Print();
TH1F *hUncH = new TH1F("hUncH"+ds_name,"hUncH"+ds_name,(XMAX-XMIN)/BIN_SIZE,XMIN,XMAX);
TH1F *hUncL = new TH1F("hUncL"+ds_name,"hUncL"+ds_name,(XMAX-XMIN)/BIN_SIZE,XMIN,XMAX);
TH1F *hUnc2H = new TH1F("hUnc2H"+ds_name,"hUnc2H"+ds_name,(XMAX-XMIN)/BIN_SIZE,XMIN,XMAX);
TH1F *hUnc2L = new TH1F("hUnc2L"+ds_name,"hUnc2L"+ds_name,(XMAX-XMIN)/BIN_SIZE,XMIN,XMAX);
TH1F *hUncC = new TH1F("hUncC"+ds_name,"hUncC"+ds_name,(XMAX-XMIN)/BIN_SIZE,XMIN,XMAX);
RooCurve *errorBand,*gFit,*gQCDFit,*gBkgFit;
//list->Print();
if (BLIND) {
errorBand = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]_errorband_Comp[shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name+"]");
gFit = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]"+"_Comp[shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name+"]");
}
else {
//errorBand = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]_errorband");
errorBand = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]_errorband_Comp[shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name+"]");
gFit = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]");
}
gQCDFit = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]"+"_Comp[shapeBkg_qcd_"+ds_name+"]");
gBkgFit = (RooCurve*)list->FindObject("pdf_bin"+ds_name+"_Norm[mbbReg_"+ds_name+"]"+"_Comp[shapeBkg_qcd_"+ds_name+",shapeBkg_top_"+ds_name+",shapeBkg_zjets_"+ds_name+"]");
for(int i=0;i<hUncH->GetNbinsX();i++) {
double x0 = hUncH->GetBinCenter(i+1);
double e1 = fabs(errorBand->Eval(x0)-gBkgFit->Eval(x0));
//double e1 = fabs(errorBand->Eval(x0)-gFit->Eval(x0));
double e2 = eNqcd/hUncH->GetNbinsX();
hUncH->SetBinContent(i+1,sqrt(pow(e2,2)+pow(e1,2)));
hUnc2H->SetBinContent(i+1,2*sqrt(pow(e2,2)+pow(e1,2)));
hUncL->SetBinContent(i+1,-sqrt(pow(e2,2)+pow(e1,2)));
hUnc2L->SetBinContent(i+1,-2*sqrt(pow(e2,2)+pow(e1,2)));
hUncC->SetBinContent(i+1,0.);
}
TPad* pad = new TPad("pad", "pad", 0., 0., 1., 1.);
pad->SetTopMargin(0.63);
pad->SetFillColor(0);
pad->SetFillStyle(0);
pad->Draw();
pad->cd(0);
hUnc2H->GetXaxis()->SetTitle("m_{bb} (GeV)");
hUnc2H->GetYaxis()->SetTitle("Data - Bkg");
//hUnc2H->GetYaxis()->SetTitle("Data - Fit");
double YMAX = 1.1*frame2->GetMaximum();
double YMIN = -1.1*frame2->GetMaximum();
hUnc2H->GetYaxis()->SetRangeUser(YMIN,YMAX);
hUnc2H->GetYaxis()->SetNdivisions(507);
// hUnc2H->GetXaxis()->SetTitleOffset(0.9);
// hUnc2H->GetYaxis()->SetTitleOffset(1.0);
hUnc2H->GetYaxis()->SetTickLength(0.0);
// hUnc2H->GetYaxis()->SetTitleSize(0.05);
// hUnc2H->GetYaxis()->SetLabelSize(0.04);
hUnc2H->GetYaxis()->CenterTitle(kTRUE);
hUnc2H->SetFillColor(kGreen);
hUnc2L->SetFillColor(kGreen);
hUncH->SetFillColor(kYellow);
hUncL->SetFillColor(kYellow);
hUncC->SetLineColor(kBlack);
hUncC->SetLineStyle(7);
hUnc2H->Draw("HIST");
hUnc2L->Draw("same HIST");
hUncH->Draw("same HIST");
hUncL->Draw("same HIST");
hUncC->Draw("same HIST");
frame2->GetYaxis()->SetTickLength(0.03/0.4);
frame2->Draw("same");
TList *list1 = (TList*)gPad->GetListOfPrimitives();
//list1->Print();
RooCurve *gSigFit = (RooCurve*)list1->FindObject("shapeSig_qqH_"+ds_name+"_Norm[mbbReg_"+ds_name+"]");
TLegend *leg = new TLegend(0.70,0.61,0.94,1.-gStyle->GetPadTopMargin()-0.01);
leg->SetTextFont(42);
leg->SetFillStyle(-1);
//leg->SetHeader(ds_name+" (m_{H}="+MASS+")");
leg->SetHeader(TString::Format("Category %d",atoi(ds_name(3,1).Data())+1));
leg->AddEntry(hBlind,"Data","P");
if (!BLIND) {
leg->AddEntry(gSigFit,"Fitted signal","L");
}
TLine *gEmpty = new TLine(0.0,0.0,0.0,0.0);
gEmpty->SetLineWidth(0);
TLegendEntry *l1 = leg->AddEntry(gEmpty,"(m_{H} = "+MASS+" GeV)","");
l1->SetTextSize(0.038*0.97*0.85);
leg->AddEntry(gFit,"Bkg. + signal","L");
leg->AddEntry(gBkgFit,"Bkg.","L");
leg->AddEntry(gQCDFit,"QCD","L");
leg->AddEntry(hUnc2H,"2#sigma bkg. unc.","F");
leg->AddEntry(hUncH,"1#sigma bkg. unc.","F");
leg->SetFillColor(0);
leg->SetBorderSize(0);
leg->SetTextFont(42);
leg->SetTextSize(0.038*0.98);
leg->Draw();
leg->SetY1(leg->GetY2()-leg->GetNRows()*0.045*0.96);
TPaveText *paveCMS = new TPaveText(gStyle->GetPadLeftMargin()+0.02,0.7,gStyle->GetPadLeftMargin()+0.15,1.-gStyle->GetPadTopMargin()-0.01,"NDC");
paveCMS->SetTextFont(62);
paveCMS->SetTextSize(gStyle->GetPadTopMargin()*3./4.);
paveCMS->SetBorderSize(0);
paveCMS->SetFillStyle(-1);
paveCMS->SetTextAlign(12);
paveCMS->AddText("CMS");
paveCMS->Draw();
gPad->Update();
paveCMS->SetY1NDC(paveCMS->GetY2NDC()-paveCMS->GetListOfLines()->GetSize()*gStyle->GetPadTopMargin());
TPaveText *paveLumi = new TPaveText(0.5,1.-gStyle->GetPadTopMargin(),0.98,1.00,"NDC");
paveLumi->SetTextFont(42);
paveLumi->SetTextSize(gStyle->GetPadTopMargin()*3./4.);
paveLumi->SetBorderSize(0);
paveLumi->SetFillStyle(-1);
paveLumi->SetTextAlign(32);
paveLumi->AddText(TString::Format("%.1f fb^{-1} (8TeV)",(atoi(ds_name(3,1).Data())<4 ? 19.8 : 18.3)).Data());//+ 18.2 ;
paveLumi->Draw();
TString path=".";
//TString path="BiasV10_limit_BRN5p4_dX0p1_B80-200_CAT0-6/output/";
system(TString::Format("[ ! -d %s/plot ] && mkdir %s/plot",path.Data(),path.Data()).Data());
system(TString::Format("[ ! -d %s/plot/fits ] && mkdir %s/plot/fits",path.Data(),path.Data()).Data());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s.pdf",path.Data(),MASS.Data(),ds_name.Data()).Data());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s.png",path.Data(),MASS.Data(),ds_name.Data()).Data());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s.eps",path.Data(),MASS.Data(),ds_name.Data()).Data());
TText *l = (TText*)paveCMS->AddText("Preliminary");
l->SetTextFont(52);
paveCMS->Draw();
gPad->Update();
paveCMS->SetY1NDC(paveCMS->GetY2NDC()-paveCMS->GetListOfLines()->GetSize()*gStyle->GetPadTopMargin());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s_prelim.pdf",path.Data(),MASS.Data(),ds_name.Data()).Data());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s_prelim.png",path.Data(),MASS.Data(),ds_name.Data()).Data());
canFit->SaveAs(TString::Format("%s/plot/fits/Fit_mH%s_%s_prelim.eps",path.Data(),MASS.Data(),ds_name.Data()).Data());
delete ds;
}
cout << "chi2sumS: " << chi2sumS << endl;
cout << "chi2sumB: " << chi2sumB << endl;
cout << "nparS: " << nparS << endl;
cout << "nparB: " << nparB << endl;
cout << "nbinsum: " << nparsum << endl;
cout << "chi2sumS/(nbinsum - nparS): " << chi2sumS / (float)(nparsum - nparS) << endl;
cout << "chi2sumB/(nbinsum - nparB): " << chi2sumB / (float)(nparsum - nparB) << endl;
delete datasets;
}
