TGraph *MarcosExclusionLine(TH2F *exclusionshape, int scantype) {
// write_warning(__FUNCTION__,"USING MARIAS ALGORITHM...");
// return get_exclusion_line(exclusionshape);
TH2F *fakehisto = flipth2f(exclusionshape);
TGraph *fakegraph = get_mSUGRA_exclusion_line(fakehisto, scantype);
TGraph *realgraph = new TGraph(fakegraph->GetN());
double x,y;
float last_x=0;
float last_y=0;
int counter=0;
for(int i=0;i<fakegraph->GetN();i++) {
fakegraph->GetPoint(i,x,y);
if(scantype==PlottingSetup::SMS) {
if(y-x<75) {
realgraph->SetPoint(counter,last_x,last_y);
counter++;
continue;
}
}
realgraph->SetPoint(counter,y,x);
last_x=y;
last_y=x;
counter++;
}
realgraph->SetLineColor(TColor::GetColor("#151515")); //nice black
realgraph->SetLineWidth(2);
//realgraph->SetLineWidth(4);//paper style
delete fakegraph;
return realgraph;
}
void ButkevichDrawer::adjust_graph(TGraph& graph) {
for (int iPoint=0;iPoint<graph.GetN();iPoint++) {
double x,y;
graph.GetPoint(iPoint,x,y);
graph.SetPoint(iPoint,x,y*1.0e-38);
}
}
std::vector<double> GetCrossings(TGraph const& g, double cross) {
std::vector<double> result;
unsigned n = g.GetN();
double x1 = 0;
double y1 = 0;
double x2 = 0;
double y2 = 0;
for (unsigned i = 0; i < (n-1); ++i) {
g.GetPoint(i, x1, y1);
g.GetPoint(i+1, x2, y2);
if ( (y2-cross)*(y1-cross) < 0.0 ) {
double m = (y2-y1)/(x2-x1);
double c = (y1 - m * x1);
double xc = (cross - c) / m;
result.push_back(xc);
std::cout << "Crossing at " << xc << std::endl;
}
}
return result;
}
void KVIDentifier::CopyGraph(const TGraph& graph)
{
// Copy coordinates of points from the TGraph
Double_t x, y;
//change number of points
Set(graph.GetN());
for (int i = 0; i < GetN(); i++) {
graph.GetPoint(i, x, y);
SetPoint(i, x, y);
}
}
TGraph* ContourGraph( TH2F* hist,double xmin=16, double xmax=90) {
//temporary canvas
TCanvas* MOO = new TCanvas( TString::Format("dummy_canvas_%s", hist->GetName()), "A scan of m_{0} versus m_{12}", 0, 0, 650,640);
MOO->cd();
TGraph* gr0 = new TGraph();
TH2F* h = (TH2F*)hist->Clone();
TGraph* gr = (TGraph*)gr0->Clone(TString::Format("gr_%s", h->GetName()));
cout << "==> Will dumb histogram: " << h->GetName() << " into a graph" <<endl;
h->SetContour( 1 );
//h->GetXaxis()->SetRangeUser(250,1200);
h->GetXaxis()->SetRangeUser(xmin, xmax);
//h->GetYaxis()->SetRangeUser(2,50);
double pval = CombinationGlob::cl_percent[1];
std::cout << pval << std::endl;
double signif = TMath::NormQuantile(1-pval);
h->SetContourLevel( 0, signif );
h->Draw("CONT LIST");
h->SetDirectory(0);
gPad->Update();
TObjArray *contours = (TObjArray*) gROOT->GetListOfSpecials()->FindObject("contours");
Int_t ncontours = contours->GetSize();
cout << "Found " << ncontours << " contours " << endl;
TList *list = (TList*)contours->At(0);
contours->Print("v");
if(!list) return NULL;
gr = (TGraph*)list->First();
if(!gr) return NULL;
gr->SetName(TString::Format("gr_%s", hist->GetName()));
//gr->SetName(hist->GetName());
int N = gr->GetN();
double x0, y0;
for(int j=0; j<N; j++) {
gr->GetPoint(j,x0,y0);
cout << j << " : " << x0 << " : "<<y0 << endl;
}
// // gr->SetMarkerSize(2.0);
//gr->Draw("ALP");
delete MOO;
cout << "Generated graph " << gr << " with name " << gr->GetName() << endl;
return gr;
}
void drawtext()
{
Int_t i,n;
Double_t x,y;
TLatex *l;
TGraph *g = (TGraph*)gPad->GetListOfPrimitives()->FindObject("Graph");
n = g->GetN();
for (i=1; i<n; i++) {
g->GetPoint(i,x,y);
l = new TLatex(x,y+0.2,Form("%4.2f",y));
l->SetTextSize(0.025);
l->SetTextFont(42);
l->SetTextAlign(21);
l->Paint();
}
}
vector< pair <double,double> > getMinMaxOfGraphs (vector<GraphInfo> inputGraphs) {
cout << "-----------------Inside minMax -------------------" << endl;
pair<double,double> yValMinMax;
pair<double,double> xValMinMax;
yValMinMax.first = 1000.0; //min
yValMinMax.second = -1000.0; //max
xValMinMax.first = 1000.0; //min
xValMinMax.second = -1000.0; //max
for (unsigned iGraph =0; iGraph < inputGraphs.size(); iGraph++){
TGraph * thisGraph = inputGraphs[iGraph].theGraph;
double iMinY = 1000.0;
double iMaxY = -1000.0;
double iMinX = 1000.0;
double iMaxX = -1000.0;
for (int iPoint =0; iPoint < thisGraph->GetN(); iPoint++){
double xVal, yVal;
thisGraph->GetPoint(iPoint, xVal, yVal);
cout <<"n = " << iPoint << "x= " << xVal << "y = " << yVal << endl;
if (yVal < iMinY )
iMinY = yVal;
if (yVal > iMaxY)
iMaxY = yVal;
if (xVal < iMinX )
iMinX = xVal;
if (xVal > iMaxX)
iMaxX = xVal;
}
cout << "New plot minY = " << iMinY << ", maxY = " << iMaxY << endl
<< " minX = " << iMinX << ", maxX = " << iMaxX << endl ;
if (iMinY < yValMinMax.first)
yValMinMax.first = iMinY;
if (iMaxY > yValMinMax.second)
yValMinMax.second = iMaxY;
if (iMinX < xValMinMax.first)
xValMinMax.first = iMinX;
if (iMaxX > xValMinMax.second)
xValMinMax.second = iMaxX;
}
//------------------------
cout << "found min = " << yValMinMax.first
<< " found max = " << yValMinMax.second
<< endl;
if (yValMinMax.first > 0 )
yValMinMax.first = 0;
vector<pair<double,double> > returnValMinMax;
returnValMinMax.push_back(xValMinMax);
returnValMinMax.push_back(yValMinMax);
return returnValMinMax;
}
void draw_mSUGRA_exclusion(TH2F *ocrosssection, TH2F *oFilterEfficiency, TH2F *oabsXS, TH2F *limitmap, TH2F *expmap, TH2F *expplusmap, TH2F *expminusmap, TH2F *exp2plusmap, TH2F *exp2minusmap, bool isobserved) {
TH2F *crosssection = (TH2F*)ocrosssection->Clone("crosssection");
// TH2F *limitmap = (TH2F*)olimitmap->Clone(((string)olimitmap->GetName()+"clone").c_str());
TH2F *cleanhisto = (TH2F*)limitmap->Clone("clean");
for(int ix=1;ix<=cleanhisto->GetNbinsX();ix++) {
for(int iy=1;iy<=cleanhisto->GetNbinsY();iy++) {
cleanhisto->SetBinContent(ix,iy,0);
}
}
TH2F *FilterEfficiency;
TH2F *absXS;
write_warning(__FUNCTION__,"You'll want to switch off 'wrongwaytodothis')");
if(wrongwaytodothis) {
//this part is the one you want to remove.
TFile *Efficiencies = new TFile("FilterEfficiencyv3.root");
FilterEfficiency = cast_into_shape((TH2F*) Efficiencies->Get("FilterEfficiency"),limitmap);
assert(FilterEfficiency);
assert(crosssection);
absXS=(TH2F*)crosssection->Clone("absXS");
crosssection->Multiply(FilterEfficiency);
} else {
//this part is the one you want to keep!
FilterEfficiency=(TH2F*)oFilterEfficiency->Clone("FilterEfficiency");
absXS=(TH2F*)oabsXS->Clone("absXS");
}
TH2F *limits = (TH2F*)limitmap->Clone("limits");
set_range(limits,true,false);
limitmap->Divide(crosssection);
expminusmap->Divide(crosssection);
expplusmap->Divide(crosssection);
exp2minusmap->Divide(crosssection);
exp2plusmap->Divide(crosssection);
expmap->Divide(crosssection);
TGraph *observed = get_mSUGRA_exclusion_line(limitmap, PlottingSetup::mSUGRA);
observed->SetLineColor(kRed);
TGraph *expminus = get_mSUGRA_exclusion_line(expminusmap, PlottingSetup::mSUGRA);
TGraph *expplus = get_mSUGRA_exclusion_line(expplusmap, PlottingSetup::mSUGRA);
TGraph *exp2minus;
if(draw2sigma) exp2minus = get_mSUGRA_exclusion_line(exp2minusmap, PlottingSetup::mSUGRA);
TGraph *exp2plus;
if(draw2sigma) exp2plus = get_mSUGRA_exclusion_line(exp2plusmap, PlottingSetup::mSUGRA);
TGraph *expected = new TGraph(expminus->GetN()+expplus->GetN());
TGraph *expected2;
if(draw2sigma) expected2 = new TGraph(exp2minus->GetN()+exp2plus->GetN());
for(int i=0;i<=expminus->GetN();i++) {
Double_t x,y;
expminus->GetPoint(i,x,y);
expected->SetPoint(i,x,y);
}
for(int i=0;i<=exp2minus->GetN();i++) {
Double_t x,y;
exp2minus->GetPoint(i,x,y);
expected2->SetPoint(i,x,y);
}
for(int i=exp2plus->GetN()-1;i>=0;i--) {
Double_t x,y;
exp2plus->GetPoint(i,x,y);
expected2->SetPoint(exp2minus->GetN()+(exp2plus->GetN()-i),x,y);
}
for(int i=expplus->GetN()-1;i>=0;i--) {
Double_t x,y;
expplus->GetPoint(i,x,y);
expected->SetPoint(expminus->GetN()+(expplus->GetN()-i),x,y);
}
expected->SetFillColor(TColor::GetColor("#9FF781"));
if(draw2sigma) expected2->SetFillColor(TColor::GetColor("#F3F781"));
smooth_line(observed);
smooth_line(expected);
if(draw2sigma) smooth_line(expected2);
TCanvas *te = new TCanvas("te","te");
te->SetRightMargin(standardmargin);
// decorate_mSUGRA(cleanhisto,te,expected,expected2,observed);
TH2F *noh = new TH2F("noh","noh",1,1,2,1,1,2);
SugarCoatThis(te,10,noh,observed);
// expected->Draw("c");
// observed->Draw("c");
stringstream saveas;
if((int)((string)limitmap->GetName()).find("limitmap")>0) {
saveas << "Limits/";
if(!isobserved) saveas << "expected/expected_";
saveas << "final_exclusion_for_JZB_geq_" << ((string)limitmap->GetName()).substr(((string)limitmap->GetName()).find("limitmap")+8,10);
} else {
saveas << "Limits/";
if(!isobserved) saveas << "expected/expected";
saveas << "final_exclusion_for_bestlimits";
}
CompleteSave(te,saveas.str());
delete te;
TCanvas *overview = new TCanvas("overview","overview",1500,1000);
set_range(crosssection,true,false);
set_range(limits,true,false);
set_range(limitmap,true,false);
overview->Divide(3,2);
overview->cd(1);
overview->cd(1)->SetLogz(1);
absXS->GetZaxis()->SetRangeUser(0.0001,100);
absXS->Draw("COLZ");
TText *title0 = write_title("Cross Section");
title0->Draw("same");
overview->cd(2);
FilterEfficiency->GetZaxis()->SetRangeUser(0.01,0.7);
FilterEfficiency->Draw("COLZ");
TText *title0aa = write_title("Filter #epsilon");
title0aa->Draw("same");
overview->cd(3);
overview->cd(3)->SetLogz(1);
crosssection->GetZaxis()->SetRangeUser(0.0001,100);
crosssection->Draw("COLZ");
TText *title0a = write_title("Filter #epsilon x Cross Section");
title0a->Draw("same");
overview->cd(4);
overview->cd(4)->SetLogz(1);
limits->GetZaxis()->SetRangeUser(0.01,100);
limits->Draw("COLZ");
TText *title1 = write_title("Cross Section Upper Limit");
title1->Draw("same");
overview->cd(5);
limitmap->Draw("COLZ");
TText *title2 = write_title("UL/XS");
title2->Draw("same");
observed->Draw("c");
overview->cd(6);
overview->cd(6)->SetRightMargin(standardmargin);
// decorate_mSUGRA(cleanhisto,overview->cd(4),expected,expected2,observed);
SugarCoatThis(overview->cd(6),10,noh,observed);
// observed->Draw("c");
stringstream saveas2;
if((int)((string)limitmap->GetName()).find("limitmap")>0) {
saveas2 << "Limits/";
if(!isobserved) saveas << "expected/expected_";
saveas2 << "exclusion_overview_for_JZB_geq_" << ((string)limitmap->GetName()).substr(((string)limitmap->GetName()).find("limitmap")+8,10);
} else {
saveas2 << "Limits/";
if(!isobserved) saveas << "expected/expected_";
saveas2 << "exclusion_overview_for_bestlimits";
}
CompleteSave(overview,saveas2.str());
delete overview;
delete noh;
delete crosssection;
delete absXS;
delete FilterEfficiency;
}
void slopetest(){
string dist = "maos210";
double nevts = 2*50000.0;
string dim = "mt";
double p1=0, p2=0, p3=0;
double dx = 0;
double eps = 0.2;
if( dim == "mt" ){
p1 = 172.0; p2 = 172.5, p3 = 173.0;
//p1 = 172.5; p2 = 173, p3 = 173.5;
//p1 = 166.0; p2 = 166.5, p3 = 167.0;
//p1 = 178.0; p2 = 178.5, p3 = 179.0;
}
if( dim == "jes" ){
p1 = 0.999; p2 = 1.000, p3 = 1.001;
}
if( dist == "mbl" ){
dx = 2.8;
}
if( dist == "mt2_221" ){
dx = 1.9;
}
TFile *f = new TFile("../results/plotsTemplates.root");
TDirectory *d = (TDirectory*)f->Get((dim+"shape_"+dist+"_gp").c_str());
/*
TCanvas *ctemp = (TCanvas*)f->Get(("c_"+dist+"_gp_signal_JSF1000").c_str());
TH1 *h = (TH1*)(ctemp->GetListOfPrimitives()->At(1));
dx = h->GetBinWidth(1);
delete ctemp;
*/
dx = 10;
TGraph *gslope = new TGraph();
TGraph *gint = new TGraph();
double sig = 0;
double d2sig = 0;
TIter nextkey(d->GetListOfKeys());
TKey *key;
while( (key = (TKey*)nextkey()) ){
string name = key->GetName();
string classname = key->GetClassName();
TCanvas *c = (TCanvas*)d->Get(name.c_str());
TGraph *g = (TGraph*)(c->GetListOfPrimitives()->At(1));
double y1=0, y2=0;
double ycent = 0;
for(int i=0; i < g->GetN(); i++){
double x=0, y=0;
g->GetPoint(i, x, y);
if( x == p1 ) y1 = y;
if( x == p2 ) ycent = y;
if( x == p3 ) y2 = y;
}
double slope = y2-y1;
string sbin = name;
string ntemp = "c"+dist+"_gp";
sbin.erase(sbin.begin(), sbin.begin()+ntemp.length());
if( dist == "mt2_221" ) sbin.erase(sbin.end(), sbin.end()+1);
double dbin = atof(sbin.c_str());
double integrand = slope*slope/ycent;
gint->SetPoint(gint->GetN(), dbin, integrand);
gslope->SetPoint(gslope->GetN(), dbin, slope);
sig += slope*slope*eps*eps*-0.5*dx/ycent;
d2sig += integrand*dx;
}
cout << "Projected S(" << eps << ") = " << sig-2.0*nevts << endl;
cout << "Projected sigma = " << sqrt(1.0/(d2sig*nevts)) << endl;
TCanvas *c1 = new TCanvas();
gslope->SetLineWidth(2);
gslope->GetXaxis()->SetTitle("(GeV)");
gslope->GetXaxis()->SetTitleSize(0.05);
gslope->GetXaxis()->SetTitleOffset(0.8);
gslope->Draw("AC");
TCanvas *c2 = new TCanvas();
gint->SetLineWidth(2);
gint->GetXaxis()->SetTitle("(GeV)");
gint->GetXaxis()->SetTitleSize(0.05);
gint->GetXaxis()->SetTitleOffset(0.8);
gint->Draw("AC");
return;
}
void alicePlots(){
TFile* alice = new TFile("~/Downloads/HEPData-ins1288320-v1-root.root");
alice->cd("Table 16");
TGraph* aliceData = Graph1D_y1;
TH1F* hist = Hist1D_y1;
TH1F* stat = Hist1D_y1_e1;
TH1F* syst = Hist1D_y1_e2;
TGraphAsymmErrors* graph2 = (TGraphAsymmErrors*)aliceData->Clone("graph2");
Int_t numPts = aliceData->GetN();
Double_t x, y;
for(int i = 0; i<numPts; i++){
aliceData->GetPoint(i, x, y);
aliceData->SetPoint(i, x, (y - 0.89581));
graph2->SetPoint(i, x, (y- 0.89581));
hist->SetBinContent(i+1, hist->GetBinContent(i+1) - 0.89581);
hist->SetBinError(i+1, stat->GetBinContent(i+1));
graph2->SetPointEXhigh(i, 0.1);
graph2->SetPointEXlow(i, 0.1);
}
graph2->SetLineColor(kBlue-10);
graph2->SetLineWidth(2);
graph2->SetMarkerColor(kBlue-10);
graph2->SetFillColor(kBlue-10);
hist->SetLineColor(kBlue-2);
hist->SetLineWidth(2);
aliceData->SetTitle("");
aliceData->GetYaxis()->SetTitle("Mass - Vacuum Mass (GeV/c^{2})");
aliceData->GetYaxis()->SetTitleSize(0.06);
aliceData->GetYaxis()->SetLabelSize(0.04);
aliceData->GetYaxis()->SetTitleOffset(1.65);
aliceData->GetYaxis()->SetTitleFont(42);
aliceData->GetYaxis()->SetLabelFont(42);
aliceData->GetXaxis()->SetTitle("p_{T} (GeV/c)");
aliceData->GetXaxis()->SetTitleSize(0.06);
aliceData->GetXaxis()->SetLabelSize(0.05);
aliceData->GetXaxis()->SetTitleFont(42);
aliceData->GetXaxis()->SetLabelFont(42);
aliceData->SetMarkerStyle(29);
aliceData->SetMarkerSize(2.5);
aliceData->SetMarkerColor(kBlue-2);
aliceData->SetLineColor(kBlue-2);
aliceData->GetYaxis()->SetRangeUser(-0.02, 0.015);
aliceData->GetXaxis()->SetRangeUser(0, 5);
TFile* phsd = new TFile("~/utaustin/resonancefits/finalplotting/20170721_KKbarAdded2_fixedwidth42_recon_pf100_scaled_error05.root");
TH1D* mass = phsd->Get("kstar0mass");
mass->SetName("mass");
mass->SetMarkerStyle(26);
mass->SetMarkerSize(2.5);
mass->SetMarkerColor(2);
mass->SetLineColor(2);
TF1* line = new TF1("line", "[0]", 0.0, 5.0);
line->SetParameter(0, 0.0);
line->SetLineColor(1);
line->SetLineStyle(7);
line->SetLineWidth(3);
for(int j = 0; j<mass->GetNbinsX(); j++){
mass->SetBinContent(j+1, (mass->GetBinContent(j+1) - 0.892));
}
TFile* phsd2 = new TFile("~/utaustin/resonancefits/finalplotting/20170616_KKbarAdded2_fixedwidth_recon_pf100_scaled_error05.root");
TH1D* mass2 = phsd2->Get("kstar0mass");
mass2->SetName("mass2");
mass2->SetMarkerStyle(22);
mass2->SetMarkerSize(2.5);
mass2->SetMarkerColor(2);
mass2->SetLineColor(2);
for(int j = 0; j<mass2->GetNbinsX(); j++){
mass2->SetBinContent(j+1, (mass2->GetBinContent(j+1) - 0.892));
}
TExec *exec1 = new TExec("exec1", "gStyle->SetErrorX(0.1)");
TExec *exec2 = new TExec("exec2", "gStyle->SetErrorX(0.5)");
TCanvas *c = new TCanvas ("c", "c", 50, 50, 650, 600);
c->cd()->SetMargin(0.1997, 0.0369, 0.1396, 0.0681);
aliceData->Draw("APX");
//exec1->Draw();
graph2->Draw("SAME P2");
//exec2->Draw();
hist->Draw("SAME E1");
line->Draw("SAME");
mass2->Draw("SAME P E1");
mass->Draw("SAME P E1");
aliceData->Draw("SAME PX");
TLegend* legend = new TLegend(0.5836, 0.1815, 0.9489, 0.3438);
legend->SetMargin(0.2);
legend->SetTextSizePixels(20);
legend->AddEntry(aliceData, "ALICE data, 0-20%", "p");
legend->AddEntry(mass2, "Fit IV to PHSD: w in-med", "p");
legend->AddEntry(mass, "Fit IV to PHSD: w/o in-med", "p");
legend->Draw("SAME");
TPaveText* text = new TPaveText(0.2554, 0.7243, 0.6006, 0.9162, "NDC");
text->AddText("(K*^{0} + #bar{K}*^{0})");
text->AddText("Pb-Pb #sqrt{s_{NN}} = 2.76 TeV");
text->GetLine(0)->SetTextSizePixels(36);
text->GetLine(1)->SetTextSizePixels(24);
text->SetTextFont(42);
text->SetBorderSize(0);
text->SetFillStyle(0);
text->Draw();
}
void makePlots( const char * modelA,
const char * modelB,
const char * modelC,
const char * src,
const char * config,
const char * infileA,
const char * infileB,
const char * infileC,
const char * infileD )
{
bool use_color = true;
int color[3] = {1, 4, 2}; //black, blue, red
int lineStyle[3] = { 1 , 2 , 3};
int lineWidth = 2;
//Output path
TString path("./paper01-plots/ratio/");
TFile * f1 = new TFile(infileA);
TFile * f2 = new TFile(infileB);
TFile * f3 = new TFile(infileC);
TFile * f4 = new TFile(infileD); // This is the Vacuum model inside Earth
TList * v_Data = new TList();
TObjString *data;
//Vaccum
data = new TObjString( TString( "ZeroPt" ) + TString("_") + TString( src ) + TString("_Pee/data") );
v_Data->Add( data );
//A
data = new TObjString( TString( modelA ) + TString("_") + TString( src ) + TString("_Pee/data") );
v_Data->Add( data );
//B
data = new TObjString( TString( modelB ) + TString("_") + TString( src ) + TString("_Pee/data") );
v_Data->Add( data );
//anti A
data = new TObjString( TString( modelC ) + TString("_") + TString( src ) + TString("_Pee/data") );
v_Data->Add( data );
TList * v_Labels = new TList();
TObjString *label;
label = new TObjString( "#phi ( E_{#nu} )" );
v_Labels->Add( label );
label = new TObjString( "#phi ( E_{#nu} )" );
v_Labels->Add( label );
label = new TObjString( "#phi ( E_{#nu} ) " );
v_Labels->Add( label );
label = new TObjString( "#phi ( E_{#nu} ) " );
v_Labels->Add( label );
TList * v_Title = new TList();
label = new TObjString( "(0) Vacuum" );
v_Title->Add( label );
label = new TObjString( "(a) Model A" );
v_Title->Add( label );
label = new TObjString( "(b) Model B" );
v_Title->Add( label );
label = new TObjString( "(c) Model C" );
v_Title->Add( label );
TList * PeeTree = new TList();
TList * PhiGraphs = new TList();
TList * RatioGraphs = new TList();
TList * VacuumGraphs = new TList();
TLegend * leg = new TLegend(0.14,0.69,0.24,0.85);
TString treeName = ((TObjString*)v_Data->At(0))->GetString();
f4->cd();
PeeTree->Add( (TTree*)gDirectory->Get( treeName.Data() ) );
std::cout << treeName << " " << (TTree*)gDirectory->Get( treeName.Data() ) << std::endl;
treeName = ((TObjString*)v_Data->At(1))->GetString();
f1->cd(); //ModelA
PeeTree->Add( (TTree*)gDirectory->Get( treeName.Data() ) );
std::cout << treeName << " " << (TTree*)gDirectory->Get( treeName.Data() ) << std::endl;
treeName = ((TObjString*)v_Data->At(2))->GetString();
f2->cd(); //ModelB
PeeTree->Add( (TTree*)gDirectory->Get( treeName.Data() ) );
std::cout << treeName << " " << (TTree*)gDirectory->Get( treeName.Data() ) << std::endl;
treeName = ((TObjString*)v_Data->At(3))->GetString();
f3->cd(); //ModelC
PeeTree->Add( (TTree*)gDirectory->Get( treeName.Data() ) );
std::cout << treeName << " " << (TTree*)gDirectory->Get( treeName.Data() ) << std::endl;
for( int k = 0; k < 4; ++k )
{
//Branches
double xx = 0.0;
double phi_e = 0.0;
double phi_m = 0.0;
double phi_t = 0.0;
TTree * currentTree = (TTree*)PeeTree->At(k);
currentTree->SetBranchAddress("Ex",&xx);
currentTree->SetBranchAddress("Phi_e",&phi_e);
currentTree->SetBranchAddress("Phi_m",&phi_m);
currentTree->SetBranchAddress("Phi_t",&phi_t);
Long64_t nentries = currentTree->GetEntries();
TGraph * g1 = new TGraph();
TGraph * g2 = new TGraph();
TGraph * g3 = new TGraph();
int np = 0;
for (Long64_t i=0;i<nentries;i++) {
currentTree->GetEntry(i);
g1->SetPoint( np, xx, phi_e);
g2->SetPoint( np, xx, phi_m);
g3->SetPoint( np, xx, phi_t);
np++;
}
PhiGraphs->Add( g1 );
PhiGraphs->Add( g2 );
PhiGraphs->Add( g3 );
std::cout << " * " << g1 << " " << g2 << " " << g3 << std::endl;
}
int idx = 1;
int idxc = 1;
int nGraphs = PhiGraphs->GetSize();
//..................................................................................................
TCanvas * c1 = new TCanvas(modelA, "Oscillation probabilities", 184, 60, 861, 670);
c1->Divide(1,4);
c1->Draw();
for( int k=0; k < nGraphs; ++k)
{
if ( idx >= 4 ) idx = 1;
TGraph * g1 = (TGraph*)PhiGraphs->At(k);
g1->SetLineWidth(2);
if ( idx == 1 )
{
std::cout << idxc << " " << idx << std::endl;
c1->cd( idxc );
gPad->SetGridx();
gPad->SetGridy();
gPad->SetLogx();
//gPad->SetLogy();
g1->SetMarkerStyle(1);
g1->SetFillColor(10);
g1->SetMaximum(1.04);
g1->SetMinimum(-0.05);
g1->GetYaxis()->SetNdivisions(504);
TString yaxis = ((TObjString*)v_Labels->At( idxc-1))->GetString();
g1->GetYaxis()->SetTitle( yaxis.Data() );
g1->GetXaxis()->SetTitle("E_{#nu} (eV)");
g1->GetYaxis()->CenterTitle(true);
g1->GetXaxis()->CenterTitle(true);
g1->GetXaxis()->SetLabelOffset(0.007);
g1->GetXaxis()->SetLabelSize(0.10);
g1->GetXaxis()->SetTitleSize(0.11);
g1->GetXaxis()->SetTitleOffset(0.5);
g1->GetXaxis()->SetLabelFont(22);
g1->GetXaxis()->SetTitleFont(22);
g1->GetYaxis()->SetLabelOffset(0.007);
g1->GetYaxis()->SetLabelSize(0.10);
g1->GetYaxis()->SetTitleSize(0.16);
g1->GetYaxis()->SetTitleOffset(0.25);
g1->GetYaxis()->SetTitleFont(22);
g1->GetYaxis()->SetLabelFont(22);
g1->SetLineStyle( lineStyle[idx-1] );
g1->SetLineColor( 1 );
if( use_color ) g1->SetLineColor( color[idx-1] );
g1->Draw("AL");
TString title = ((TObjString*)v_Title->At(idxc-1))->GetString();
topTitle(title.Data());
//
if ( idxc == 1 )
{
char HistoName[20];
sprintf(HistoName,"H1_%d", k);
TGraph * h1 = g1->Clone(HistoName);
VacuumGraphs->Add( h1 );
std::cout << " graph " << k << " == in vacuum" << h1 << " " << std::string(HistoName) << std::endl;
}
}
else if ( idx == 2 ) {
std::cout << " - " << idxc << " " << idx << std::endl;
g1->SetLineColor( 1 );
if( use_color ) g1->SetLineColor( color[idx-1] );
g1->SetLineStyle( lineStyle[idx-1] );
g1->Draw("L");
if ( idxc == 1 )
{
char HistoName[20];
sprintf(HistoName,"H1_%d", k);
TGraph * h1 = g1->Clone(HistoName);
VacuumGraphs->Add( h1 );
std::cout << " graph " << k << " == in vacuum" << h1 << " " << std::string(HistoName) << std::endl;
}
} else if ( idx == 3 ) {
std::cout << " -- "<< idxc << " " << idx << std::endl;
g1->SetLineColor( 1 );
if( use_color ) g1->SetLineColor( color[idx-1]);
g1->SetLineStyle( lineStyle[idx-1] );
g1->Draw("L");
if ( idxc == 1 )
{
char HistoName[20];
sprintf(HistoName,"H1_%d", k);
TGraph * h1 = g1->Clone(HistoName);
VacuumGraphs->Add( h1 );
std::cout << " graph " << k << " == in vacuum" << h1 << " " << std::string(HistoName) << std::endl;
}
idxc += 1;
} else { }
TLine *line = new TLine(7.9e+10,0.333,2.25e+14,0.333);
line->SetLineColor(3);
line->SetLineStyle(2);
line->SetLineWidth(2);
line->Draw("same");
idx += 1;
}
c1->cd();
//..................................................................................................
idx = 1;
double xp1 = 0.0;
double xp2 = 0.0;
for( int k = 3; k < nGraphs; ++k)
{
if ( idx >= 4 ) idx = 1;
TGraph * g1 = (TGraph*)PhiGraphs->At(k);
int maxpts = g1->GetN();
xx = 0.0;
double y1 = 0.0;
double y2 = 0.0;
double ratio = 1.0;
TGraph * r1 = new TGraph();
int np = 0;
if( idx == 1 )
{
TGraph * denom = (TGraph*)VacuumGraphs->At(0);
np = 0;
for( int j = 0; j < maxpts; ++j)
{
g1->GetPoint(j, xp1, y1);
denom->GetPoint(j, xp2, y2);
if ( y2 <= 1.0e-3 ) continue;
ratio = y1/y2;
if (ratio > 5 ) std::cout << " nu_e> x1= " << xp1 << " x2= " << xp2 << " num= "
<< y1 << " den= " << y2 << " num/den= " << ratio << std::endl;
r1->SetPoint( np, xp1, ratio );
++np;
}
RatioGraphs->Add(r1);
std::cout << " ratio added " << std::endl;
} else if ( idx == 2 )
{
TGraph * denom = (TGraph*)VacuumGraphs->At(1);
np = 0;
for( int j = 0; j < maxpts; ++j)
{
g1->GetPoint(j, xp1, y1);
denom->GetPoint(j, xp2, y2);
if ( y2 <= 1.0e-3 ) continue;
ratio = y1/y2;
if (ratio > 5 ) std::cout << " nu_e> x1= " << xp1 << " x2= " << xp2 << " num= "
<< y1 << " den= " << y2 << " num/den= " << ratio << std::endl;
r1->SetPoint( np, xp1, ratio );
++np;
}
RatioGraphs->Add(r1);
std::cout << " ratio added " << std::endl;
} else if ( idx == 3 )
{
TGraph * denom = (TGraph*)VacuumGraphs->At(2);
np = 0;
for( int j = 0; j < maxpts; ++j)
{
g1->GetPoint(j, xp1, y1);
denom->GetPoint(j, xp2, y2);
if ( y2 <= 1.0e-3 ) continue;
ratio = y1/y2;
if (ratio > 5 ) std::cout << " nu_e> x1= " << xp1 << " x2= " << xp2 << " num= "
<< y1 << " den= " << y2 << " num/den= " << ratio << std::endl;
r1->SetPoint( np, xp1, ratio );
++np;
}
RatioGraphs->Add(r1);
std::cout << " ratio added " << std::endl;
} else {}
idx += 1;
}
c1->cd(1);
TGraph * g1 = (TGraph*)PhiGraphs->At(0);
g1->Draw("L");
c1->cd(2);
g1 = (TGraph*)PhiGraphs->At(3);
g1->Draw("L");
c1->cd(3);
g1 = (TGraph*)PhiGraphs->At(6);
g1->Draw("L");
c1->cd(4);
g1 = (TGraph*)PhiGraphs->At(9);
g1->Draw("L");
c1->cd();
std::stringstream saveAs;
saveAs.str("");
saveAs << path << modelA << "/pdf/" << "nueosc_flux_" << config << "_Models_ABC_Vac" << ".pdf";
c1->SaveAs( saveAs.str().c_str() );
saveAs.str("");
saveAs << path << modelA << "/png/" << "nueosc_flux_" << config << "_Models_ABC_Vac" << ".png";
c1->SaveAs( saveAs.str().c_str() );
saveAs.str("");
saveAs << path << modelA << "/eps/" << "nueosc_flux_" << config << "_Models_ABC_Vac" << ".eps";
c1->SaveAs( saveAs.str().c_str() );
//..................................................................................................
Float_t small = 1e-5; //Referee request
TCanvas * c2 = new TCanvas("Ratios", "Oscillation probabilities - Ratios", 184, 60, 861, 670);
c2->Divide(1,3,small,small);
c2->Draw();
c2->cd();
//
idx = 1;
idxc = 1;
nGraphs = RatioGraphs->GetSize();
for( int k=0; k < nGraphs; ++k)
{
if ( idx >= 4 ) idx = 1;
TGraph * g1 = (TGraph*)RatioGraphs->At(k);
g1->SetLineWidth(lineWidth);
std::cout << " g1 " << g1 << std::endl;
if ( idx == 1 )
{
std::cout << idxc << " " << idx << std::endl;
c2->cd( idxc );
//Referee request
if ( idxc == 1 )
gPad->SetBottomMargin(small);
else if ( idxc == 3)
gPad->SetTopMargin(small);
else { }
if ( idxc == 2 )
{
gPad->SetBottomMargin(small);
gPad->SetTopMargin(small);
}
// ......................
gPad->SetGridx();
gPad->SetGridy();
gPad->SetLogx();
//gPad->SetLogy();
g1->SetMarkerStyle(1);
g1->SetFillColor(10);
g1->SetMaximum(21.00);
g1->SetMinimum(-1.05);
g1->GetYaxis()->SetNdivisions(504);
TString yaxis = ((TObjString*)v_Labels->At( idxc-1))->GetString();
g1->GetYaxis()->SetTitle( "#phi/#phi_{vac}" );
g1->GetXaxis()->SetTitle("E_{#nu} (eV) ");
g1->GetXaxis()->CenterTitle(true);
g1->GetXaxis()->SetLabelOffset(0.007);
g1->GetXaxis()->SetLabelSize(0.10);
g1->GetXaxis()->SetTitleSize(0.11);
g1->GetXaxis()->SetTitleOffset(0.5);
g1->GetXaxis()->SetLabelFont(22);
g1->GetXaxis()->SetTitleFont(22);
g1->GetXaxis()->SetTickLength(0.05);
g1->GetYaxis()->CenterTitle(true);
g1->GetYaxis()->SetLabelOffset(0.007);
g1->GetYaxis()->SetLabelSize(0.10);
g1->GetYaxis()->SetTitleSize(0.16);
g1->GetYaxis()->SetTitleOffset(0.25);
g1->GetYaxis()->SetTitleFont(22);
g1->GetYaxis()->SetLabelFont(22);
g1->GetYaxis()->SetTickLength(0.05);
g1->SetLineStyle( lineStyle[idx-1] );
g1->SetLineColor( 1 );
if( use_color ) g1->SetLineColor( color[idx-1] );
g1->Draw("AL");
TString title = ((TObjString*)v_Title->At(idxc))->GetString();
topTitle(title.Data());
}
else if ( idx == 2 ) {
std::cout << " - " << idxc << " " << idx << std::endl;
g1->SetLineColor( 1 );
if( use_color ) g1->SetLineColor( color[idx-1] );
g1->SetLineStyle( lineStyle[idx-1] );
g1->Draw("L");
}
else if ( idx == 3 ) {
std::cout << " -- "<< idxc << " " << idx << std::endl;
g1->SetLineColor( 1 );
if( use_color ) g1->SetLineColor( color[idx-1]);
g1->SetLineStyle( lineStyle[idx-1] );
g1->Draw("L");
idxc += 1;
} else { }
idx += 1;
}
c2->cd(1);
TGraph * g1 = (TGraph*)RatioGraphs->At(0);
g1->Draw("L");
c2->cd(2);
g1 = (TGraph*)RatioGraphs->At(3);
g1->Draw("L");
c2->cd(3);
g1 = (TGraph*)RatioGraphs->At(6);
g1->Draw("L");
c2->cd();
//
saveAs.str("");
saveAs << path << modelA << "/pdf/" << "nueosc_flux_" << config << "_4x_Ratios_noLog" << ".pdf";
c2->SaveAs( saveAs.str().c_str() );
saveAs.str("");
saveAs << path << modelA << "/png/" << "nueosc_flux_" << config << "_4x_Ratios_noLog" << ".png";
c2->SaveAs( saveAs.str().c_str() );
saveAs.str("");
saveAs << path << modelA << "/eps/" << "nueosc_flux_" << config << "_4x_Ratios_noLog" << ".eps";
c2->SaveAs( saveAs.str().c_str() );
}
TGraph* getContour(TH2D* h, TString name) {
TGraph* graph = new TGraph(100);
graph->SetName(name);
int ip = 0;
int nx = h->GetXaxis()->GetNbins();
int ny = h->GetYaxis()->GetNbins();
// for y>x
int ix = -1;
for(int j=ny;true; j--) {
int k = -1;
for(int i=2; i<nx-1; i++) {
if(h->GetBinContent(i,j) < 0) {
std::cout << "i,j,z : " << i << ", " << j << ", " << h->GetBinContent(i,j) << std::endl;
k = i;
break;
}
}// for i
if(k<0) continue;
double y = h->GetYaxis()->GetBinCenter(j);
double x1 = h->GetXaxis()->GetBinCenter(k-1);
double x2 = h->GetXaxis()->GetBinCenter(k);
double z1 = h->GetBinContent(k-1,j);
double z2 = h->GetBinContent(k,j);
double x = x1 + (x2-x1)*fabs(z1)/fabs(z2-z1);
std::cout << "y, x1, x2, z1, z2, x : " << y << ", " << x1 << ", " << x2 << ", " << x << ", " << z1 << ", " << z2 << std::endl;
graph->SetPoint(ip++,x,y);
if(h->GetYaxis()->GetBinCenter(j) < h->GetXaxis()->GetBinCenter(k)) {
ix = k;
break;
}
}// for j
if(ix < 0) std::cout << "Something wrong...." << std::endl;
// for y<x
for(int i=ix; i<=nx; i++) {
int k = -1;
for(int j=2; j<ny-1; j++) {
if(h->GetBinContent(i,j) < 0) {
k = j;
break;
}
}// for j
if(k<0) continue;
double x = h->GetXaxis()->GetBinCenter(i);
double y1 = h->GetYaxis()->GetBinCenter(k-1);
double y2 = h->GetYaxis()->GetBinCenter(k);
double z1 = h->GetBinContent(i,k-1);
double z2 = h->GetBinContent(i,k);
double y = y1 + (y2-y1)*fabs(z1)/fabs(z2-z1);
std::cout << "x, y1, y2, z1, z2, y : " << x << ", " << y1 << ", " << y2 << ", " << y << ", " << z1 << ", " << z2 << std::endl;
graph->SetPoint(ip++,x,y);
}// for i
ip = graph->GetN()-1;
while(1) {
double x, y;
graph->GetPoint(ip,x,y);
if(x>1) break;
else graph->RemovePoint(ip);
ip--;
}
return graph;
}
int main(){
system("mkdir -p plots");
RooMsgService::instance().setGlobalKillBelow(RooFit::ERROR);
TFile *bkgFile = TFile::Open("comb_svn/hgg.inputbkgdata_8TeV_MVA.root");
TFile *sigFile = TFile::Open("comb_svn/hgg.inputsig_8TeV_nosplitVH_MVA.root");
RooWorkspace *bkgWS = (RooWorkspace*)bkgFile->Get("cms_hgg_workspace");
RooWorkspace *sigWS = (RooWorkspace*)sigFile->Get("wsig_8TeV");
RooRealVar *mass = (RooRealVar*)bkgWS->var("CMS_hgg_mass");
RooRealVar *mu = new RooRealVar("mu","mu",-5.,5.);
mass->setBins(320);
cout << mass->getBins() << endl;
RooDataSet *dataAll;
int firstCat=1;
int lastCat=1;
float mu_low=-1.;
float mu_high=3.;
float mu_step=0.01;
vector<pair<double,TGraph*> > minNlltrack;
for (int cat=firstCat; cat<=lastCat; cat++){
RooDataSet *data = (RooDataSet*)bkgWS->data(Form("data_mass_cat%d",cat));
if (cat==firstCat) dataAll = (RooDataSet*)data->Clone("data_mass_all");
else dataAll->append(*data);
RooDataHist *dataBinned = new RooDataHist(Form("roohist_data_mass_cat%d",cat),Form("roohist_data_mass_cat%d",cat),RooArgSet(*mass),*data);
RooDataSet *sigMC = (RooDataSet*)sigWS->data(Form("sig_mass_m125_cat%d",cat));
if (!dataBinned || !sigMC){
cerr << "ERROR -- one of data or signal is NULL" << endl;
exit(1);
}
// Construct PDFs for this category using PdfModelBuilder
PdfModelBuilder modelBuilder;
modelBuilder.setObsVar(mass);
modelBuilder.setSignalModifier(mu);
// For Standard Analysis
//if (cat>=0 && cat<=3) modelBuilder.addBkgPdf("Bernstein",5,Form("pol5_cat%d",cat));
//if (cat>=4 && cat<=5) modelBuilder.addBkgPdf("Bernstein",4,Form("pol4_cat%d",cat));
//if (cat>=6 && cat<=8) modelBuilder.addBkgPdf("Bernstein",3,Form("pol3_cat%d",cat));
// To Profile Multiple PDFs
if (cat==0 || cat==1 || cat==2 || cat==3){
modelBuilder.addBkgPdf("Bernstein",4,Form("pol4_cat%d",cat));
modelBuilder.addBkgPdf("Bernstein",5,Form("pol5_cat%d",cat));
modelBuilder.addBkgPdf("Bernstein",6,Form("pol6_cat%d",cat));
/*
modelBuilder.addBkgPdf("PowerLaw",1,Form("pow1_cat%d",cat));
modelBuilder.addBkgPdf("PowerLaw",3,Form("pow3_cat%d",cat));
modelBuilder.addBkgPdf("PowerLaw",5,Form("pow5_cat%d",cat));
modelBuilder.addBkgPdf("Exponential",1,Form("exp1_cat%d",cat));
modelBuilder.addBkgPdf("Exponential",3,Form("exp3_cat%d",cat));
modelBuilder.addBkgPdf("Exponential",5,Form("exp5_cat%d",cat));
modelBuilder.addBkgPdf("Laurent",1,Form("lau1_cat%d",cat));
modelBuilder.addBkgPdf("Laurent",3,Form("lau3_cat%d",cat));
modelBuilder.addBkgPdf("Laurent",5,Form("lau5_cat%d",cat));
*/
}
if (cat==4 || cat==5 || cat==6 || cat==7 || cat==8) {
modelBuilder.addBkgPdf("Bernstein",3,Form("pol3_cat%d",cat));
modelBuilder.addBkgPdf("Bernstein",4,Form("pol4_cat%d",cat));
/*
modelBuilder.addBkgPdf("PowerLaw",1,Form("pow1_cat%d",cat));
modelBuilder.addBkgPdf("PowerLaw",3,Form("pow3_cat%d",cat));
modelBuilder.addBkgPdf("Exponential",1,Form("exp1_cat%d",cat));
modelBuilder.addBkgPdf("Exponential",3,Form("exp3_cat%d",cat));
modelBuilder.addBkgPdf("Laurent",1,Form("lau1_cat%d",cat));
modelBuilder.addBkgPdf("Laurent",3,Form("lau3_cat%d",cat));
*/
}
map<string,RooAbsPdf*> bkgPdfs = modelBuilder.getBkgPdfs();
modelBuilder.setSignalPdfFromMC(sigMC);
modelBuilder.makeSBPdfs();
map<string,RooAbsPdf*> sbPdfs = modelBuilder.getSBPdfs();
modelBuilder.fitToData(dataBinned,true,true);
modelBuilder.fitToData(dataBinned,false,true);
modelBuilder.throwToy(Form("cat%d_toy0",cat),dataBinned->sumEntries(),true,true);
// Profile this category using ProfileMultiplePdfs
ProfileMultiplePdfs profiler;
for (map<string,RooAbsPdf*>::iterator pdf=sbPdfs.begin(); pdf!=sbPdfs.end(); pdf++) {
string bkgOnlyName = pdf->first.substr(pdf->first.find("sb_")+3,string::npos);
if (bkgPdfs.find(bkgOnlyName)==bkgPdfs.end()){
cerr << "ERROR -- couldn't find bkg only pdf " << bkgOnlyName << " for SB pdf " << pdf->first << endl;
pdf->second->fitTo(*dataBinned);
exit(1);
}
int nParams = bkgPdfs[bkgOnlyName]->getVariables()->getSize()-1;
profiler.addPdf(pdf->second,2*nParams);
//profiler.addPdf(pdf->second);
cout << pdf->second->GetName() << " nParams=" << pdf->second->getVariables()->getSize() << " nBkgParams=" << nParams << endl;
}
profiler.printPdfs();
//cout << "Continue?" << endl;
//string bus; cin >> bus;
profiler.plotNominalFits(dataBinned,mass,80,Form("cat%d",cat));
pair<double,map<string,TGraph*> > minNlls = profiler.profileLikelihood(dataBinned,mass,mu,mu_low,mu_high,mu_step);
pair<double,map<string,TGraph*> > correctedNlls = profiler.computeEnvelope(minNlls,Form("cat%d",cat),2.);
minNlltrack.push_back(make_pair(correctedNlls.first,correctedNlls.second["envelope"]));
//minNlls.second.insert(pair<string,TGraph*>("envelope",envelopeNll.second));
//map<string,TGraph*> minNLLs = profiler.profileLikelihoodEnvelope(dataBinned,mu,mu_low,mu_high,mu_step);
profiler.plot(correctedNlls.second,Form("cat%d_nlls",cat));
//profiler.print(minNLLs,mu_low,mu_high,mu_step);
/*
if (minNLLs.find("envelope")==minNLLs.end()){
cerr << "ERROR -- envelope TGraph not found in minNLLs" << endl;
exit(1);
}
*/
//minNlltrack.push_back(make_pair(profiler.getGlobalMinNLL(),minNLLs["envelope"]));
}
//exit(1);
TGraph *comb = new TGraph();
for (vector<pair<double,TGraph*> >::iterator it=minNlltrack.begin(); it!=minNlltrack.end(); it++){
if (it->second->GetN()!=minNlltrack.begin()->second->GetN()){
cerr << "ERROR -- unequal number of points for TGraphs " << it->second->GetName() << " and " << minNlltrack.begin()->second->GetName() << endl;
exit(1);
}
}
for (int p=0; p<minNlltrack.begin()->second->GetN(); p++){
double x,y,sumy=0;
for (vector<pair<double,TGraph*> >::iterator it=minNlltrack.begin(); it!=minNlltrack.end(); it++){
it->second->GetPoint(p,x,y);
sumy += (y+it->first);
}
comb->SetPoint(p,x,sumy);
}
pair<double,double> globalMin = getGraphMin(comb);
for (int p=0; p<comb->GetN(); p++){
double x,y;
comb->GetPoint(p,x,y);
comb->SetPoint(p,x,y-globalMin.second);
}
vector<double> fitVal = getValsFromLikelihood(comb);
cout << "Best fit.." << endl;
cout << "\t mu = " << Form("%4.3f",fitVal[0]) << " +/- (1sig) = " << fitVal[2]-fitVal[0] << " / " << fitVal[0]-fitVal[1] << endl;
cout << "\t " << " " << " +/- (2sig) = " << fitVal[4]-fitVal[0] << " / " << fitVal[0]-fitVal[3] << endl;
cout << comb->Eval(fitVal[0]) << " " << comb->Eval(fitVal[1]) << " " << comb->Eval(fitVal[2]) << " " << comb->Eval(fitVal[3]) << " " << comb->Eval(fitVal[4]) << endl;
double quadInterpVal = ProfileMultiplePdfs::quadInterpMinimum(comb);
cout << "quadInterp: mu = " << quadInterpVal << endl;
cout << "\t " << comb->Eval(quadInterpVal) << " " << comb->Eval(quadInterpVal-0.005) << " " << comb->Eval(quadInterpVal-0.01) << " " << comb->Eval(quadInterpVal+0.005) << " " << comb->Eval(quadInterpVal+0.01) << endl;
comb->SetLineWidth(2);
TCanvas *canv = new TCanvas();
comb->Draw("ALP");
canv->Print("plots/comb.pdf");
TFile *tempOut = new TFile("tempOut.root","RECREATE");
tempOut->cd();
comb->SetName("comb");
comb->Write();
tempOut->Close();
return 0;
}
void plotMSSM(const TString& what="(ggA+bbA)*BRAZh*BRhbb"){
const double BRZll=0.06726;
const double fb2pb=1000;
//TString scale(Form("*%f*%f",BRZll,fb2pb));
TString scale("");
TString cname(what);
cname.ReplaceAll("*","x");
cname.ReplaceAll("(","U");
cname.ReplaceAll(")","U");
cname+="_MSSM_mhmax";
//
TString goodName(what);
goodName.ReplaceAll("mh","m_{h}");
goodName.ReplaceAll("ggA","#sigma_{gg#rightarrowA}");
goodName.ReplaceAll("bbA","#sigma_{bb#rightarrowA}");
goodName.ReplaceAll("BRAZh","B(A#rightarrowZh)");
goodName.ReplaceAll("BRhbb","B(h#rightarrowbb)");
//goodName+=("*B(Z#rightarrowll)");
//goodName+=("[pb] ");
goodName+=("[GeV] ");
TString goodType("MSSM m_{h}^{max}");
//goodName=("#sigma*B(pp#rightarrowA#rightarrowZh#rightarrowllbb) [fb]");
//goodName=("#sigma*B(pp#rightarrowA) [fb]");
//goodName=("BR(A#rightarrowZh)");
//goodName=("BR(h#rightarrowbb)");
//if (m>0) mass=(Form(" * (mA==%d)",m));
//TString ok(" * validity * stability * perturbativity * unitarity ");
//TString ok(" * unitarity");
TString ok("");
TChain* ch=new TChain("TreeMSSM");
ch->Add("lsf_working_dir_M225_20636539/parameter_MSSM.root");
ch->Add("lsf_working_dir_M250_20636540/parameter_MSSM.root");
ch->Add("lsf_working_dir_M275_20636541/parameter_MSSM.root");
ch->Add("lsf_working_dir_M300_20636542/parameter_MSSM.root");
ch->Add("lsf_working_dir_M325_20636543/parameter_MSSM.root");
ch->Add("lsf_working_dir_M350_20636544/parameter_MSSM.root");
ch->Add("lsf_working_dir_M400_20636545/parameter_MSSM.root");
ch->Add("lsf_working_dir_M500_20636546/parameter_MSSM.root");
ch->Add("lsf_working_dir_M600_20636547/parameter_MSSM.root");
//double tanbeta[30]={1,10,20,30,40,50,60,70,80,90,100,120,140,160,180,200,220,240,260,280,300,400,500,600,700,800,900,1000,1100,10000};
//double tanbeta[51]={0,10,20,30,40,50,60,70,80,90,100,120,140,160,180,200,220,240,260,280,300,320,340,360,380,400,420,440,460,480,500,550,600,650,700,750,800,850,900,950,1000,1100,1200,1300,1400,1500,2000,3000,4000,5000,6000};
double tanbeta[51]={0,10,20,30,40,50,60,70,80,90,100,120,140,160,180,200,220,240,260,280,300,320,340,360,380,400,420,440,460,500,550,580,600,650,700,750,800,850,900,950,1000,1100,1200,1300,1400,1500,2000,3000,4000,5000,6000};
Double_t bin_tb[50];
for (unsigned int i=0; i<50; i++) {
bin_tb[i]=0.005*(tanbeta[i]+tanbeta[i+1]);
//cout << "bin_tb[" << i << "]=" << bin_tb[i] << " " << tanbeta[i+1]/100. << endl;
}
double mA[11]={200,225,250,275,300,325,350,400,500,600,700};
Double_t bin_mA[10];
for (unsigned int i=0; i<=10; ++i) {
bin_mA[i]=0.5*(mA[i]+mA[i+1]);
//cout << "bin_mA["<<i<<"]=" << bin_mA[i] << endl;
}
bin_mA[10]=650;
TH2F* hggA=new TH2F("hggA","ggA cross section vs tan#beta,m_{A}; m_{A} GeV; tan#beta",9,bin_mA,49,bin_tb);
hggA->Sumw2();
//hggA->Draw();
TString cut=what+scale+ok;
cout << "CUT: " << cut << endl;
ch->Project("hggA","tb:mA",cut);
TStyle *tdrStyle = gROOT->GetStyle("tdrStyle");
// Double_t level[15]={.01,.02,.05,.1,.2,.5,1.,2.,5.,10.,20.,50.,100.,200.,500.};
// hggA->SetContour(14,level);
// hggA->SetMinimum(level[0]);
//
//Double_t level[10]={1.,5.,10.,20.,50.,100.,200.,500.,800.,1000.}; // for x-section
//Double_t level[10]={100,105,110.,115.,120.,123,125.7,127,130.,135.}; // for mh
Double_t level[10]={1,2,3.,4.,120.,123,125.7,127,130.,135.}; // for mh
//Double_t level[10]={.01,.1,.2,0.5,0.6,0.65,0.7,0.75,0.8,0.9}; // for BR
//Double_t level[10]={.01,.02,.05,.07,.1,.15,0.2,0.5,0.75,1.}; // for BR
hggA->SetContour(9,level);
hggA->SetMinimum(level[0]);
Double_t level[7]={122.7.,123.7,125.4,126.0,127.7,128.7.,150}; // for mh
hggA->SetContour(6,level);
hggA->SetMinimum(90);
Int_t colors[7] = {kWhite,kGreen,kGreen+2,kBlack,kGreen+2,kGreen,kWhite};
tdrStyle->SetPalette((sizeof(colors)/sizeof(Int_t)), colors);
// DRAW
tdrStyle->SetOptStat(0);
// tdrStyle->SetPadGridX(true);
// tdrStyle->SetPadGridY(true);
// tdrStyle->SetPadTopMargin(0.05);
// tdrStyle->SetPadBottomMargin(0.13);
tdrStyle->SetTitleYOffset(1.3);
tdrStyle->SetTitleXOffset(1.6);
tdrStyle->SetTitleOffset(1.3,"Z");
// tdrStyle->SetOptLogz(1);
// tdrStyle->SetOptLogy(1);
tdrStyle->SetPadRightMargin(0.14);
//tdrStyle->SetPalette(1);
tdrStyle->cd();
gROOT->ForceStyle();
cout << "Creating canvas " << cname << endl;
TCanvas* c1=new TCanvas(cname,goodName,1200,600);
cout << " done " << c1->GetName() << endl;
c1->Divide(2);
c1->cd(1);
hggA->DrawCopy("lego2");
gPad->SetLogz();
gPad->SetLogy();
//gPad->SetPhi(120);
gPad->SetPhi(-150);
//gPad->SetTheta(30);
gPad->UseCurrentStyle();
gPad->Update();
TLatex tl;
tl.SetTextSize(0.04);
tl.SetNDC();
tl.DrawLatex(0.1,0.95,goodName);
tl.SetTextAlign(11);
tl.DrawLatex(0.1,0.89,goodType);
c1->cd(2);
// tdrStyle->SetPadLeftMargin(0.25);
gPad->UseCurrentStyle();
gPad->Update();
hggA->GetXaxis()->SetTitleOffset(1.1);
hggA->GetYaxis()->SetTitleOffset(1.1);
hggA->GetZaxis()->SetTitleOffset(100);
//hggA->Smooth();
gPad->SetLogy(kFALSE);
hggA->DrawCopy("zcont1");
tl.DrawLatex(0.15,0.97,goodName);
tl.SetTextAlign(11);
tl.DrawLatex(0.2,0.9,goodType);
TCanvas* ctmp=new TCanvas(cname,goodName,600,600);
hggA->GetYaxis()->SetRangeUser(0.1,10.);
hggA->DrawCopy("zcont1");
tl.DrawLatex(0.83,0.97,goodName);
tl.SetTextAlign(11);
tl.DrawLatex(0.2,0.9,goodType);
pCan(ctmp,cname+"_Lin");
// TH1F* test=new TH1F("test","ggA cross section vs tan#beta; tan#beta",27,bin_tb);
// ch->Project("test","tb",what);
// test->Draw();
TCanvas* c2=new TCanvas(cname+"Obs",goodName,800,800);
gPad->UseCurrentStyle();
gPad->Update();
hggA->GetXaxis()->SetTitleOffset(1.1);
hggA->GetYaxis()->SetTitleOffset(1.1);
hggA->DrawCopy("cont list");
gPad->Update();
//return;
// Get Contours
TObjArray *conts = (TObjArray*)gROOT->GetListOfSpecials()->FindObject("contours");
TList* contLevel = NULL;
TGraph* curv = NULL;
TGraph* gc = NULL;
Int_t nGraphs = 0;
Int_t TotalConts = 0;
if (conts == NULL){
printf("*** No Contours Were Extracted!\n");
TotalConts = 0;
return;
} else {
TotalConts = conts->GetSize();
}
printf("TotalConts = %d\n", TotalConts);
for(i = 0; i < TotalConts; i++){
contLevel = (TList*)conts->At(i);
printf("Contour %d has %d Graphs\n", i, contLevel->GetSize());
nGraphs += contLevel->GetSize();
}
nGraphs = 0;
TH2F *hr = new TH2F("hr", ";m_{A};tan#beta", 2, 225, 600, 2, 0.1, 100);
hr->GetXaxis()->SetTitleOffset(1.1);
hr->GetXaxis()->SetRangeUser(200,650);
hr->GetYaxis()->SetTitleOffset(1.2);
hr->GetYaxis()->SetNdivisions(110,kFALSE);
hr->GetXaxis()->SetNdivisions(20205,kFALSE);
hr->Draw();
Double_t x0, y0, z0;
TLatex l;
l.SetTextSize(0.03);
l.SetTextAlign(32);
char val[20];
for(i = 0; i < TotalConts; i++){
contLevel = (TList*)conts->At(i);
z0 = level[i];
printf("Z-Level Passed in as: Z = %f\n", z0);
// Get first graph from list on curves on this level
curv = (TGraph*)contLevel->First();
for(j = 0; j < contLevel->GetSize(); j++){
// last point
//curv->GetPoint(curv->GetN()-1, x0, y0);
// first point
curv->GetPoint(2, x0, y0);
// if (z0<0) curv->SetLineColor(kRed);
// if (z0>0) curv->SetLineColor(kBlue);
nGraphs ++;
printf("\tGraph: %d -- %d Elements\n", nGraphs,curv->GetN());
// Draw clones of the graphs to avoid deletions in case the 1st
// pad is redrawn.
gc = (TGraph*)curv->Clone();
gc->Draw("C");
if (z0>=.01) sprintf(val,"%0.2f",z0);
if (z0>=.1) sprintf(val,"%0.2f",z0);
if (z0>=1) sprintf(val,"%0.0f",z0);
l.DrawLatex(x0*0.99,y0,val);
curv = (TGraph*)contLevel->After(curv); // Get Next graph
}
}
gPad->SetLogy();
gPad->SetGridx();
gPad->SetGridy();
gPad->SetRightMargin(0.05);
gPad->SetTopMargin(0.10);
c2->Update();
printf("\n\n\tExtracted %d Contours and %d Graphs \n", TotalConts, nGraphs );
tl.SetTextAlign(31);
tl.DrawLatex(0.8,0.85,goodName);
tl.SetTextAlign(31);
tl.DrawLatex(0.8,0.77,goodType);
pCan(c2,cname+"_BW");
c1->cd(1);
gPad->SetLogy();
gPad->SetLogz();
c1->cd(2);
gPad->SetLogy();
c1->Update();
pCan(c1,cname);
}
TCanvas *ContourList(){
const Double_t PI = TMath::Pi();
TCanvas* c = new TCanvas("c","Contour List",0,0,600,600);
c->SetRightMargin(0.15);
c->SetTopMargin(0.15);
Int_t i, j, TotalConts;
Int_t nZsamples = 80;
Int_t nPhiSamples = 80;
Double_t HofZwavelength = 4.0; // 4 meters
Double_t dZ = HofZwavelength/(Double_t)(nZsamples - 1);
Double_t dPhi = 2*PI/(Double_t)(nPhiSamples - 1);
TArrayD z(nZsamples);
TArrayD HofZ(nZsamples);
TArrayD phi(nPhiSamples);
TArrayD FofPhi(nPhiSamples);
// Discretized Z and Phi Values
for ( i = 0; i < nZsamples; i++) {
z[i] = (i)*dZ - HofZwavelength/2.0;
HofZ[i] = SawTooth(z[i], HofZwavelength);
}
for(Int_t i=0; i < nPhiSamples; i++){
phi[i] = (i)*dPhi;
FofPhi[i] = sin(phi[i]);
}
// Create Histogram
TH2D *HistStreamFn = new TH2D("HstreamFn",
"#splitline{Histogram with negative and positive contents. Six contours are defined.}{It is plotted with options CONT LIST to retrieve the contours points in TGraphs}",
nZsamples, z[0], z[nZsamples-1], nPhiSamples, phi[0], phi[nPhiSamples-1]);
// Load Histogram Data
for (Int_t i = 0; i < nZsamples; i++) {
for(Int_t j = 0; j < nPhiSamples; j++){
HistStreamFn->SetBinContent(i,j, HofZ[i]*FofPhi[j]);
}
}
gStyle->SetPalette(1);
gStyle->SetOptStat(0);
gStyle->SetTitleW(0.99);
gStyle->SetTitleH(0.08);
Double_t contours[6];
contours[0] = -0.7;
contours[1] = -0.5;
contours[2] = -0.1;
contours[3] = 0.1;
contours[4] = 0.4;
contours[5] = 0.8;
HistStreamFn->SetContour(6, contours);
// Draw contours as filled regions, and Save points
HistStreamFn->Draw("CONT Z LIST");
c->Update(); // Needed to force the plotting and retrieve the contours in TGraphs
// Get Contours
TObjArray *conts = (TObjArray*)gROOT->GetListOfSpecials()->FindObject("contours");
TList* contLevel = NULL;
TGraph* curv = NULL;
TGraph* gc = NULL;
Int_t nGraphs = 0;
Int_t TotalConts = 0;
if (conts == NULL){
printf("*** No Contours Were Extracted!\n");
TotalConts = 0;
return;
} else {
TotalConts = conts->GetSize();
}
printf("TotalConts = %d\n", TotalConts);
for(i = 0; i < TotalConts; i++){
contLevel = (TList*)conts->At(i);
printf("Contour %d has %d Graphs\n", i, contLevel->GetSize());
nGraphs += contLevel->GetSize();
}
nGraphs = 0;
TCanvas* c1 = new TCanvas("c1","Contour List",610,0,600,600);
c1->SetTopMargin(0.15);
TH2F *hr = new TH2F("hr",
"#splitline{Negative contours are returned first (highest to lowest). Positive contours are returned from}{lowest to highest. On this plot Negative contours are drawn in red and positive contours in blue.}",
2, -2, 2, 2, 0, 6.5);
hr->Draw();
Double_t x0, y0, z0;
TLatex l;
l.SetTextSize(0.03);
char val[20];
for(i = 0; i < TotalConts; i++){
contLevel = (TList*)conts->At(i);
if (i<3) z0 = contours[2-i];
else z0 = contours[i];
printf("Z-Level Passed in as: Z = %f\n", z0);
// Get first graph from list on curves on this level
curv = (TGraph*)contLevel->First();
for(j = 0; j < contLevel->GetSize(); j++){
curv->GetPoint(0, x0, y0);
if (z0<0) curv->SetLineColor(kRed);
if (z0>0) curv->SetLineColor(kBlue);
nGraphs ++;
printf("\tGraph: %d -- %d Elements\n", nGraphs,curv->GetN());
// Draw clones of the graphs to avoid deletions in case the 1st
// pad is redrawn.
gc = (TGraph*)curv->Clone();
gc->Draw("C");
sprintf(val,"%g",z0);
l.DrawLatex(x0,y0,val);
curv = (TGraph*)contLevel->After(curv); // Get Next graph
}
}
c1->Update();
printf("\n\n\tExtracted %d Contours and %d Graphs \n", TotalConts, nGraphs );
gStyle->SetTitleW(0.);
gStyle->SetTitleH(0.);
return c1;
}
///
/// Make a plot out of a 1D histogram holding a 1-CL curve.
/// The strategy is to always convert the 1-CL histogram (hCL) into
/// a TGraph. This way we can add known points (solutions, points
/// at end of scan range) and also have a filled area without line
/// smoothing. This is not possible with histograms due to a Root bug.
///
/// The function draws the TGraphs, and returns a pointer to the
/// TGraph object that can be used in the TLegend.
///
/// Markers are plotted if the method name of the scanner is "Plugin" or "BergerBoos" or "DatasetsPlugin".
/// One can plot a line instead of points even for the Plugin method by
/// using setPluginMarkers().
///
/// For the angle variables, a new axis is painted that is in Deg.
///
/// \param s The scanner to plot.
/// \param first
/// \param last
/// \param filled
///
TGraph* OneMinusClPlot::scan1dPlot(MethodAbsScan* s, bool first, bool last, bool filled, int CLsType)
{
if ( arg->debug ){
cout << "OneMinusClPlot::scan1dPlot() : plotting ";
cout << s->getName() << " (" << s->getMethodName() << ")" << endl;
}
if ( m_mainCanvas==0 ){
m_mainCanvas = newNoWarnTCanvas(name+getUniqueRootName(), title, 800, 600);
}
m_mainCanvas->cd();
bool plotPoints = ( s->getMethodName()=="Plugin" || s->getMethodName()=="BergerBoos" || s->getMethodName()=="DatasetsPlugin" ) && plotPluginMarkers;
TH1F *hCL = (TH1F*)s->getHCL()->Clone(getUniqueRootName());
if (CLsType==1) hCL = (TH1F*)s->getHCLs()->Clone(getUniqueRootName());
else if (CLsType==2) hCL = (TH1F*)s->getHCLsFreq()->Clone(getUniqueRootName());
// fix inf and nan entries
for ( int i=1; i<=s->getHCL()->GetNbinsX(); i++ ){
if ( s->getHCL()->GetBinContent(i)!=s->getHCL()->GetBinContent(i)
|| std::isinf(s->getHCL()->GetBinContent(i)) ) s->getHCL()->SetBinContent(i, 0.0);
}
// remove errors the hard way, else root ALWAYS plots them
if ( !plotPoints ) hCL = histHardCopy(hCL, true, true);
// disable any statistics box
hCL->SetStats(0);
// Convert the histogram into a TGraph so we can add the solution.
// Also, the lf2 drawing option is broken in latest root versions.
TGraph *g;
if ( plotPoints ) g = new TGraphErrors(hCL->GetNbinsX());
else g = new TGraph(hCL->GetNbinsX());
g->SetName(getUniqueRootName());
for ( int i=0; i<hCL->GetNbinsX(); i++ ){
g->SetPoint(i, hCL->GetBinCenter(i+1), hCL->GetBinContent(i+1));
if ( plotPoints ) ((TGraphErrors*)g)->SetPointError(i, 0.0, hCL->GetBinError(i+1));
}
// add solution
if ( ! s->getSolutions().empty() ){
TGraphTools t;
TGraph *gNew = t.addPointToGraphAtFirstMatchingX(g, s->getScanVar1Solution(0), 1.0);
delete g;
g = gNew;
}
// // set last point to the same p-value as first point by hand
// // some angle plots sometimes don't manage to do it by themselves...
// if ( arg->isQuickhack(XX) )
// {
// Double_t pointx0, pointy0, err0;
// Double_t pointx1, pointy1, err1;
// g->GetPoint(0, pointx0, pointy0);
// g->GetPoint(g->GetN()-1, pointx1, pointy1);
// g->SetPoint(g->GetN()-1, pointx1, pointy0);
// if ( plotPoints ) err0 = ((TGraphErrors*)g)->GetErrorY(0);
// if ( plotPoints ) ((TGraphErrors*)g)->SetPointError(g->GetN()-1, 0.0, err0);
// }
// add end points of scan range
if ( !plotPoints )
{
Double_t pointx0, pointy0;
TGraph *gNew = new TGraph(g->GetN()+4);
gNew->SetName(getUniqueRootName());
for ( int i=0; i<g->GetN(); i++)
{
g->GetPoint(i, pointx0, pointy0);
gNew->SetPoint(i+2, pointx0, pointy0);
}
// add origin
gNew->SetPoint(0, hCL->GetXaxis()->GetXmin(), 0);
// add a point at first y height but at x=origin.
g->GetPoint(0, pointx0, pointy0);
gNew->SetPoint(1, hCL->GetXaxis()->GetXmin(), pointy0);
// add a point at last y height but at x=xmax.
g->GetPoint(g->GetN()-1, pointx0, pointy0);
gNew->SetPoint(gNew->GetN()-2, hCL->GetXaxis()->GetXmax(), pointy0);
// add a point at xmax, 0
gNew->SetPoint(gNew->GetN()-1, hCL->GetXaxis()->GetXmax(), 0);
g = gNew;
}
int color = s->getLineColor();
if(CLsType>0 && s->getMethodName().Contains("Plugin") && !arg->plotpluginonly) {
if (CLsType==1) color = kBlue-7;
else if (CLsType==2) color = kBlue+2;
}
else if(CLsType>0) {
if (CLsType==1) color = s->getLineColor() - 5;
if (CLsType==2) color = s->getLineColor() - 4;
}
g->SetLineColor(color);
if ( filled ){
g->SetLineWidth(2);
double alpha = arg->isQuickhack(12) ? 0.4 : 1.;
if ( arg->isQuickhack(24) ) alpha = 0.;
g->SetFillColorAlpha(color,alpha);
g->SetLineStyle(1);
g->SetFillStyle( s->getFillStyle() );
}
else{
g->SetLineWidth(2);
g->SetLineStyle(s->getLineStyle());
if ( last && arg->isQuickhack(25) ) g->SetLineWidth(3);
}
if ( plotPoints ){
g->SetLineWidth(1);
g->SetMarkerColor(color);
g->SetMarkerStyle(8);
g->SetMarkerSize(0.6);
if(CLsType==1) {
g->SetMarkerStyle(33);
g->SetMarkerSize(1);
}
if(CLsType==2) {
g->SetMarkerStyle(21);
}
}
// build a histogram which holds the axes
float min = arg->scanrangeMin == arg->scanrangeMax ? hCL->GetXaxis()->GetXmin() : arg->scanrangeMin;
float max = arg->scanrangeMin == arg->scanrangeMax ? hCL->GetXaxis()->GetXmax() : arg->scanrangeMax;
TH1F *haxes = new TH1F("haxes"+getUniqueRootName(), "", 100, min, max);
haxes->SetStats(0);
haxes->GetXaxis()->SetTitle(s->getScanVar1()->GetTitle());
haxes->GetYaxis()->SetTitle("1-CL");
haxes->GetXaxis()->SetLabelFont(font);
haxes->GetYaxis()->SetLabelFont(font);
haxes->GetXaxis()->SetTitleFont(font);
haxes->GetYaxis()->SetTitleFont(font);
haxes->GetXaxis()->SetTitleOffset(0.9);
haxes->GetYaxis()->SetTitleOffset(0.85);
haxes->GetXaxis()->SetLabelSize(labelsize);
haxes->GetYaxis()->SetLabelSize(labelsize);
haxes->GetXaxis()->SetTitleSize(titlesize);
haxes->GetYaxis()->SetTitleSize(titlesize);
int xndiv = arg->ndiv==-1 ? 407 : abs(arg->ndiv);
bool optimizeNdiv = arg->ndiv<0 ? true : false;
haxes->GetXaxis()->SetNdivisions(xndiv, optimizeNdiv);
haxes->GetYaxis()->SetNdivisions(407, true);
// plot y range
float plotYMax;
float plotYMin;
if ( plotLegend && !arg->isQuickhack(22) ) {
if ( arg->plotlog ) { plotYMin = 1.e-3; plotYMax = 10.; }
else { plotYMin = 0.0 ; plotYMax = 1.3; }
}
else {
if ( arg->plotlog ) { plotYMin = 1.e-3; plotYMax = 1.0; }
else { plotYMin = 0.0 ; plotYMax = 1.0; }
}
// change if passed as option
plotYMin = arg->plotymin > 0. ? arg->plotymin : plotYMin;
plotYMax = arg->plotymax > 0. ? arg->plotymax : plotYMax;
haxes->GetYaxis()->SetRangeUser( plotYMin, plotYMax );
haxes->Draw("axissame");
g->SetHistogram(haxes);
TString drawOption = "";
if ( plotPoints ) drawOption += " pe";
else if ( filled ) drawOption += " F";
else drawOption += " L";
if ( first ) drawOption += " A";
g->Draw(drawOption);
//if ( drawOption.Contains("F") ) ((TGraph*)g->Clone())->Draw("L");
gPad->Update();
float ymin = gPad->GetUymin();
float ymax = gPad->GetUymax();
float xmin = gPad->GetUxmin();
float xmax = gPad->GetUxmax();
// for the angles, draw a new axis in units of degrees
if ( isAngle(s->getScanVar1()) ){
haxes->GetXaxis()->SetTitle(s->getScanVar1()->GetTitle() + TString(" [#circ]"));
haxes->GetXaxis()->SetNdivisions(0); // disable old axis
if ( last ){
// new top axis
TString chopt = "-U"; // - = downward ticks, U = unlabeled, http://root.cern.ch/root/html534/TGaxis.html
if ( !optimizeNdiv ) chopt += "N"; // n = no bin optimization
TGaxis *axist = new TGaxis(xmin, 1, xmax, 1, RadToDeg(xmin), RadToDeg(xmax), xndiv, chopt);
axist->SetName("axist");
axist->Draw();
// new bottom axis
float axisbMin = RadToDeg(xmin);
float axisbMax = RadToDeg(xmax);
if ( arg->isQuickhack(3) ){ ///< see documentation of --qh option in OptParser.cpp
axisbMin += 180.;
axisbMax += 180.;
}
chopt = ""; // - = downward ticks, U = unlabeled, http://root.cern.ch/root/html534/TGaxis.html
if ( !optimizeNdiv ) chopt += "N"; // n = no bin optimization
TGaxis *axisb = new TGaxis(xmin, ymin, xmax, ymin, axisbMin, axisbMax, xndiv, chopt);
axisb->SetName("axisb");
axisb->SetLabelFont(font);
axisb->SetLabelSize(labelsize);
axisb->Draw();
}
}
else
{
if ( last ){
// add top axis
TString chopt = "-U"; // - = downward ticks, U = unlabeled, http://root.cern.ch/root/html534/TGaxis.html
if ( !optimizeNdiv ) chopt += "N"; // n = no bin optimization
TGaxis *axist = new TGaxis(xmin, 1.0, xmax, 1.0, xmin, xmax, xndiv, chopt);
axist->SetName("axist");
axist->SetLineWidth(1);
axist->Draw();
}
}
if ( last )
{
// add right axis
TGaxis *axisr = 0;
if ( arg->plotlog ){
float f3min = 1e-3;
float f3max = (plotLegend && !arg->isQuickhack(22)) ? 10. : 1.;
TF1 *f3 = new TF1("f3","log10(x)",f3min,f3max);
axisr = new TGaxis(xmax, f3min, xmax, f3max, "f3", 510, "G+");
}
else{
axisr = new TGaxis(xmax, ymin, xmax, ymax, 0, (plotLegend && !arg->isQuickhack(22)) ? 1.3 : 1.0, 407, "+");
}
axisr->SetLabelSize(0);
axisr->SetLineWidth(1);
axisr->SetName("axisr");
axisr->SetLabelColor(kWhite);
axisr->SetTitleColor(kWhite);
axisr->Draw();
// redraw right axis as well because the 1-CL graph can cover the old one
haxes->Draw("axissame");
}
return g;
}
///
/// Make a plot for the CLs stuff.
/// The strategy is to convert the hCLExp and hCLErr histogrms
/// into TGraphs and TGraphAsymmErrors
/// We can then provide some smoothing options as well
///
/// \param s The scanner to plot.
/// \param smooth
///
void OneMinusClPlot::scan1dCLsPlot(MethodAbsScan *s, bool smooth, bool obsError)
{
if ( arg->debug ){
cout << "OneMinusClPlot::scan1dCLsPlot() : plotting ";
cout << s->getName() << " (" << s->getMethodName() << ")" << endl;
}
m_mainCanvas->cd();
s->checkCLs();
TH1F *hObs = (TH1F*)s->getHCLsFreq()->Clone(getUniqueRootName());
TH1F *hExp = (TH1F*)s->getHCLsExp()->Clone(getUniqueRootName());
TH1F *hErr1Up = (TH1F*)s->getHCLsErr1Up()->Clone(getUniqueRootName());
TH1F *hErr1Dn = (TH1F*)s->getHCLsErr1Dn()->Clone(getUniqueRootName());
TH1F *hErr2Up = (TH1F*)s->getHCLsErr2Up()->Clone(getUniqueRootName());
TH1F *hErr2Dn = (TH1F*)s->getHCLsErr2Dn()->Clone(getUniqueRootName());
if ( !hObs ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - can't find histogram hObs" << endl;
if ( !hExp ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - can't find histogram hExp" << endl;
if ( !hErr1Up ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - can't find histogram hErr1Up" << endl;
if ( !hErr1Dn ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - can't find histogram hErr1Dn" << endl;
if ( !hErr2Up ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - can't find histogram hErr2Up" << endl;
if ( !hErr2Dn ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - can't find histogram hErr2Dn" << endl;
// convert obs to graph
TGraph *gObs = convertTH1ToTGraph(hObs,obsError);
// convert others to raw graphs
TGraph *gExpRaw = convertTH1ToTGraph(hExp);
TGraph *gErr1UpRaw = convertTH1ToTGraph(hErr1Up);
TGraph *gErr1DnRaw = convertTH1ToTGraph(hErr1Dn);
TGraph *gErr2UpRaw = convertTH1ToTGraph(hErr2Up);
TGraph *gErr2DnRaw = convertTH1ToTGraph(hErr2Dn);
// smoothing if needed
TGraph *gExp;
TGraph *gErr1Up;
TGraph *gErr1Dn;
TGraph *gErr2Up;
TGraph *gErr2Dn;
TGraphSmooth *smoother = new TGraphSmooth();
if (smooth) {
if ( arg->debug ) cout << "OneMinusClPlot::scan1dCLsPlot() : smoothing graphs" << endl;
gExp = (TGraph*)smoother->SmoothSuper( gExpRaw )->Clone("gExp");
gErr1Up = (TGraph*)smoother->SmoothSuper( gErr1UpRaw )->Clone("gErr1Up");
gErr1Dn = (TGraph*)smoother->SmoothSuper( gErr1DnRaw )->Clone("gErr1Dn");
gErr2Up = (TGraph*)smoother->SmoothSuper( gErr2UpRaw )->Clone("gErr2Up");
gErr2Dn = (TGraph*)smoother->SmoothSuper( gErr2DnRaw )->Clone("gErr2Dn");
if ( arg->debug ) cout << "OneMinusClPlot::scan1dCLsPlot() : done smoothing graphs" << endl;
}
else {
gExp = gExpRaw;
gErr1Up = gErr1UpRaw;
gErr1Dn = gErr1DnRaw;
gErr2Up = gErr2UpRaw;
gErr2Dn = gErr2DnRaw;
}
if ( !gObs ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - null graph gObs" << endl;
if ( !gExp ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - null graph gExp" << endl;
if ( !gErr1Up ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - null graph gErr1Up" << endl;
if ( !gErr1Dn ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - null graph gErr1Dn" << endl;
if ( !gErr2Up ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - null graph gErr2Up" << endl;
if ( !gErr2Dn ) cout << "OneMinusClPlot::scan1dCLsPlot() : problem - null graph gErr2Dn" << endl;
gObs->SetName("gObs");
gExp->SetName("gExp");
gErr1Up->SetName("gErr1Up");
gErr1Dn->SetName("gErr1Dn");
gErr2Up->SetName("gErr2Up");
gErr2Dn->SetName("gErr2Dn");
// now make the graphs for the error bands
TGraphAsymmErrors *gErr1 = new TGraphAsymmErrors( gExp->GetN() );
gErr1->SetName("gErr1");
TGraphAsymmErrors *gErr2 = new TGraphAsymmErrors( gExp->GetN() );
gErr2->SetName("gErr2");
double x,y,yerrUp,yerrDn;
double xerr = (hExp->GetBinCenter(2)-hExp->GetBinCenter(1))/2.;
// protect against smoothing over 1
for (int i=0; i<gExp->GetN(); i++) {
gExp->GetPoint(i,x,y); gExp->SetPoint(i,x,TMath::Min(y,1.));
gErr1Up->GetPoint(i,x,y); gErr1Up->SetPoint(i,x,TMath::Min(y,1.));
gErr1Dn->GetPoint(i,x,y); gErr1Dn->SetPoint(i,x,TMath::Min(y,1.));
gErr2Up->GetPoint(i,x,y); gErr2Up->SetPoint(i,x,TMath::Min(y,1.));
gErr2Dn->GetPoint(i,x,y); gErr2Dn->SetPoint(i,x,TMath::Min(y,1.));
}
for (int i=0; i<gExp->GetN(); i++) {
gExp->GetPoint(i,x,y);
gErr1->SetPoint(i,x,y);
gErr2->SetPoint(i,x,y);
gErr1Up->GetPoint(i,x,yerrUp);
gErr1Dn->GetPoint(i,x,yerrDn);
gErr1->SetPointError(i, xerr, xerr, y-yerrDn, yerrUp-y );
gErr2Up->GetPoint(i,x,yerrUp);
gErr2Dn->GetPoint(i,x,yerrDn);
gErr2->SetPointError(i, xerr, xerr, y-yerrDn, yerrUp-y );
}
gErr2->SetFillColor( TColor::GetColor("#3182bd") );
gErr2->SetLineColor( TColor::GetColor("#3182bd") );
gErr1->SetFillColor( TColor::GetColor("#9ecae1") );
gErr1->SetLineColor( TColor::GetColor("#9ecae1") );
gExp->SetLineColor(kRed);
gExp->SetLineWidth(3);
gObs->SetLineColor(kBlack);
gObs->SetMarkerColor(kBlack);
gObs->SetLineWidth(3);
gObs->SetMarkerSize(1);
gObs->SetMarkerStyle(20);
float min = arg->scanrangeMin == arg->scanrangeMax ? hObs->GetXaxis()->GetXmin() : arg->scanrangeMin;
float max = arg->scanrangeMin == arg->scanrangeMax ? hObs->GetXaxis()->GetXmax() : arg->scanrangeMax;
TH1F *haxes = new TH1F("haxes"+getUniqueRootName(), "", 100, min, max);
haxes->SetStats(0);
haxes->GetXaxis()->SetTitle(s->getScanVar1()->GetTitle());
haxes->GetYaxis()->SetTitle("CL_{S}");
haxes->GetXaxis()->SetLabelFont(font);
haxes->GetYaxis()->SetLabelFont(font);
haxes->GetXaxis()->SetTitleFont(font);
haxes->GetYaxis()->SetTitleFont(font);
haxes->GetXaxis()->SetTitleOffset(0.9);
haxes->GetYaxis()->SetTitleOffset(0.85);
haxes->GetXaxis()->SetLabelSize(labelsize);
haxes->GetYaxis()->SetLabelSize(labelsize);
haxes->GetXaxis()->SetTitleSize(titlesize);
haxes->GetYaxis()->SetTitleSize(titlesize);
int xndiv = arg->ndiv==-1 ? 407 : abs(arg->ndiv);
bool optimizeNdiv = arg->ndiv<0 ? true : false;
haxes->GetXaxis()->SetNdivisions(xndiv, optimizeNdiv);
haxes->GetYaxis()->SetNdivisions(407, true);
haxes->GetYaxis()->SetRangeUser(0.,1.);
// Legend:
// make the legend short, the text will extend over the boundary, but the symbol will be shorter
float legendXmin = 0.68 ;
float legendYmin = 0.58 ;
float legendXmax = legendXmin + 0.25 ;
float legendYmax = legendYmin + 0.22 ;
TLegend* leg = new TLegend(legendXmin,legendYmin,legendXmax,legendYmax);
leg->SetFillColor(kWhite);
leg->SetFillStyle(0);
leg->SetLineColor(kWhite);
leg->SetBorderSize(0);
leg->SetTextFont(font);
leg->SetTextSize(legendsize*0.75);
if (obsError) leg->AddEntry( gObs, "Observed", "LEP" );
else leg->AddEntry( gObs, "Observed", "LP" );
leg->AddEntry( gExp, "Expected", "L" );
leg->AddEntry( gErr1, "#pm 1#sigma", "F");
leg->AddEntry( gErr2, "#pm 2#sigma", "F");
haxes->Draw("AXIS+");
gErr2->Draw("E3same");
gErr1->Draw("E3same");
gExp->Draw("Lsame");
if (obsError) gObs->Draw("LEPsame");
else gObs->Draw("LPsame");
leg->Draw("same");
drawCLguideLine(0.1);
double yGroup = 0.83;
if ( arg->plotprelim || arg->plotunoff ) yGroup = 0.8;
drawGroup(yGroup);
m_mainCanvas->SetTicks();
m_mainCanvas->RedrawAxis();
m_mainCanvas->Update();
m_mainCanvas->Modified();
m_mainCanvas->Show();
savePlot( m_mainCanvas, name+"_cls"+arg->plotext );
m_mainCanvas->SetTicks(false);
}
void createNNLOplot(TString theory="ahrens")
{
// theory="ahrens", "kidonakis"
TString outputRootFile="test.root";
// NB: add new datset name here
if(theory.Contains("ahrens") ){
outputRootFile="AhrensNLONNLL";
//if(theory.Contains("mtt") ) outputRootFile+="mttbar" ;
//else if(theory.Contains("pt")) outputRootFile+="pTttbar";
outputRootFile+=".root";
}
else if(theory=="kidonakis") outputRootFile="KidonakisAproxNNLO.root";
// general options
gStyle->SetOptStat(0);
bool usequad=true;
bool divideByBinwidth=true;
// list of variables
std::vector<TString> xSecVariables_, xSecLabel_;
// NB: add variables for new datset name here
TString xSecVariablesUsedAhrens[] ={"ttbarMass", "ttbarPt"};
TString xSecVariablesUsedKidonakis[] ={"topPt" , "topY" };
if( theory.Contains("ahrens") ) xSecVariables_ .insert( xSecVariables_.begin(), xSecVariablesUsedAhrens , xSecVariablesUsedAhrens + sizeof(xSecVariablesUsedAhrens )/sizeof(TString) );
else if(theory=="kidonakis") xSecVariables_ .insert( xSecVariables_.begin(), xSecVariablesUsedKidonakis, xSecVariablesUsedKidonakis + sizeof(xSecVariablesUsedKidonakis)/sizeof(TString) );
// get variable binning used for final cross sections
std::map<TString, std::vector<double> > bins_=makeVariableBinning();
//std::vector<double> tempbins_;
//double ttbarMassBins[]={345,445,545,745, 1045};
//tempbins_.insert( tempbins_.begin(), ttbarMassBins, ttbarMassBins + sizeof(ttbarMassBins)/sizeof(double) );
//bins_["ttbarMass"]=tempbins_;
// loop all variables
for(unsigned var=0; var<xSecVariables_.size(); ++var){
TString variable=xSecVariables_[var];
std::cout << "----------" << std::endl;
std::cout << theory << ": " << variable << std::endl;
// get bin boundaries
double low =bins_[variable][0];
double high=bins_[variable][bins_[variable].size()-1];
// --------------------------
// get raw nnlo theory points
// --------------------------
// NB: add new datset file names here
TGraph * rawHist;
TString predictionfolder="/afs/naf.desy.de/group/cms/scratch/tophh/CommonFiles/";
if(theory=="ahrens" ){
if(variable.Contains("ttbarMass")) rawHist= new TGraph(predictionfolder+"AhrensTheory_Mttbar_8000_172.5_NLONNLL_norm.dat");//AhrensTheory_Mtt_7000_172.5_Mtt_fin.dat
if(variable.Contains("ttbarPt" )) rawHist= new TGraph(predictionfolder+"AhrensTheory_pTttbar_8000_172.5_NLONNLL_abs.dat");//AhrensTheory_pTttbar_7000_172.5_NLONNLL_abs.dat
}
else if(theory=="kidonakis"){
if(variable.Contains("topPt")) rawHist= new TGraph(predictionfolder+"pttopnnloapprox8lhc173m.dat");//"ptnormalNNLO7lhc173m.dat" //"pttopnnloapprox8lhc173m.dat"
if(variable.Contains("topY" )) rawHist= new TGraph(predictionfolder+"ytopnnloapprox8lhc173m.dat" );//"ynormalNNLO7lhc173m.dat" //"ytopnnloapprox8lhc173m.dat"
}
// NB: say if points should be interpreted as single points with
// nothing in between or as integrated value over the range
bool points=true;
if(theory.Contains("ahrens")) points=false;
else if(theory=="kidonakis") points=true;
std::cout << "input: " << rawHist->GetTitle() << std::endl;
std::cout << "interprete values as points?: " << points << std::endl;
// --------------------
// convertion to TH1F*
// --------------------
double *Xvalues = rawHist->GetX();
int Nbins=rawHist->GetN();
//double *Yvalues = rawHist->GetY(); // not working
double xmax=-1;
double xmin=-1;
double binwidth=-1;
//
TH1F* hist;
// NB: add additional binning for new theory here
// NB: if loaded data should be interpreted as points with
// nothing in between (like kidonakis), make suree you
// choose a binning that is fine enough for the
// data points loaded
if(theory=="ahrens"){
if(variable.Contains("ttbarMass")){
xmin= 345.;
xmax=2720.;
binwidth=25.;// 5 for 8TeV, 25 for 7TeV
if(TString(rawHist->GetTitle()).Contains("8000")) binwidth=5.;
}
else if(variable.Contains("ttbarPt")){
xmin= 0.;
xmax=1300.;
binwidth=5.;
}
}
else if(theory=="kidonakis"){
if(variable.Contains("topPt")){
xmin= 0.;
xmax=1500.;
binwidth=1.;
}
else if(variable.Contains("topY")){
xmin=-3.8;
xmax= 3.8;
binwidth=0.01;
}
}
// fill data in binned TH1F
hist= new TH1F ( variable, variable, (int)((xmax-xmin)/binwidth), xmin, xmax);
TH1F* ori=(TH1F*)hist->Clone("original points");
std::cout << "fine binned theory prediction has " << hist->GetNbinsX() << " bins" << std::endl;
std::cout << "loaded values from .dat file: " << std::endl;
// list all data values loaded and the corresponding bin
for(int bin=1; bin<=Nbins; ++bin){
double x=-999;
double y=-999;
// NB: choose if loaded data is interpreted as points with nothing
// between (like kidonakis) or as integrated over the bin range (like ahrens)
if(points){
// check if you are still inside the array
//std::cout << "data point " << bin-1 << "/" << sizeof(Xvalues)/sizeof(double) << std::endl;
if(rawHist->GetPoint(bin-1, x, y)!=-1){
//x=Xvalues[bin-1]; // get value from data points
x+=0.5*binwidth; // add half the binwidth to get the center of the bin
}
}
else{
x=hist->GetBinCenter(bin); // get bin center
y=rawHist->GetY()[bin-1];
}
if(x!=-999){
std::cout << "data point: " << bin;
std::cout << "(<x>=" << x << ")-> bin";
// get bin in target (fine binned) plot
int bin2=bin;
if(points) bin2=hist->FindBin(x);
//double y=Yvalues[bin2-1];
std::cout << bin2 << " (";
std::cout << hist->GetBinLowEdge(bin2) << ".." << hist->GetBinLowEdge(bin2+1);
std::cout << "): " << y << std::endl;
// fill target (fine binned) plot
if(!points) hist->SetBinContent(bin2, y);
// mark bins coming from the original prediction
ori->SetBinContent(bin2, 1.);
// -------------------------------
// fit range without data entries
// -------------------------------
// NB: needed if loaded data is interpreted as points with nothing
// between (like kidonakis)
if(points){
// perform a linear fit wrt previous point
// get the two points (this bin and the previous one)
int binPrev= (bin==1&&variable=="topPt") ? 0 : hist->FindBin(Xvalues[bin-2]+0.5*binwidth);
double x2=-1;
double x1= 0;
double y2=-1;
double y1= 0.;
rawHist->GetPoint(bin-1, x2, y2);
x2+=0.5*binwidth;
if(bin==1&&variable=="topPt"){
y1=0;
x1=0;
}
else{
rawHist->GetPoint(bin-2, x1, y1);
x1+=0.5*binwidth;
}
// calculate linear funtion
double a=(y2-y1)/(x2-x1);
double b=y1-a*x1;
TF1* linInterpol=new TF1("linInterpol"+getTStringFromInt(bin), "[0]*x+[1]", x1, x2);
linInterpol->SetParameter(0,a);
linInterpol->SetParameter(1,b);
double xlow = (bin==1&&variable=="topPt") ? 0. : hist->GetBinLowEdge(binPrev+1);
double xhigh = hist->GetBinLowEdge(bin2+1);
std::cout << " lin. interpolation [ (" << x1 << "," << y1 << ") .. (" << x2 << "," << y2 << ") ]: " << a << "*x+" << b << std::endl;
linInterpol->SetRange(xlow, xhigh);
hist->Add(linInterpol);
}
}
}
// check theory curve
std::cout << std::endl << "analyze theory curve:" << std::endl;
double integralRawTheory=hist->Integral(0.,hist->GetNbinsX()+1);
std::cout << "Integral: " << integralRawTheory << std::endl;
if(integralRawTheory==0.){
std::cout << "ERROR: Integral can not be 0!" << std::endl;
exit(0);
}
std::cout << "binwidth: " << binwidth << std::endl;
std::cout << "Integral*binwidth: " << integralRawTheory*binwidth << std::endl;
std::cout << "binRange: " << xmin << ".." << xmax << std::endl;
std::cout << " -> reco range: " << low << ".." << high << std::endl;
std::vector<double> recoBins_=bins_[variable];
for(unsigned int i=0; i<recoBins_.size(); ++i){
i==0 ? std::cout << "(" : std::cout << ", ";
std::cout << recoBins_[i];
if(i==recoBins_.size()-1) std::cout << ")" << std::endl;
}
// check if you need to divide by binwidth
if(std::abs(1.-integralRawTheory)<0.03){
std::cout << "Integral is approx. 1 -> need to divide by binwidth!" << std::endl;
hist->Scale(1./binwidth);
}
else if(std::abs(1-integralRawTheory*binwidth)<0.03){
std::cout << "Integral*binwidth is approx. 1 -> no scaling needed!" << std::endl;
}
else{
std::cout << "need to normalize and divide by binwidth";
hist->Scale(1./(binwidth*integralRawTheory));
}
// styling
hist->GetXaxis()->SetRangeUser(low,high);
hist->SetMarkerColor(kMagenta);
hist->SetLineColor( kMagenta);
hist->SetMarkerStyle(24);
// create canvas
std::cout << std::endl << "create canvas " << std::endl;
TCanvas *canv = new TCanvas(variable,variable,800,600);
canv->cd();
std::cout << "draw original theory curve " << std::endl;
//temp->Draw("axis");
hist->Draw("p");
//hist->Draw("hist same");
// draw original points
if(points){
for(int bin=1; bin<ori->GetNbinsX(); ++bin){
// create copy of original data points with the normalized values
if(ori->GetBinContent(bin)!=0) ori->SetBinContent(bin, hist->GetBinContent(bin));
ori->SetMarkerColor(kBlack);
ori->SetMarkerStyle(29);
ori->SetMarkerSize(1);
ori->Draw("p same");
}
}
// --------------------
// create rebinned plot
// --------------------
std::cout << std::endl << "create rebinned curve:" << std::endl;
TString name="";
// NB: add name for dataset here
name=variable;
if( theory=="kidonakis") name+="approxnnlo";
else if(theory=="ahrens" ) name+="nlonnll" ;
TH1F* binnedPlot=new TH1F(name, name, bins_[variable].size()-1, &bins_[variable][0]);
for(int bin=1; bin<=hist->GetNbinsX(); ++bin){
double y=hist->GetBinContent(bin)*hist->GetBinWidth(bin);
double xlow =hist->GetBinLowEdge(bin);
double xhigh=hist->GetBinLowEdge(bin+1);
// search corresponding bin in rebinned curve
bool found=false;
//std::cout << "xlow: " << xlow << ", xhigh: " << xhigh << std::endl; // FIXME
for(int binRebinned=0; binRebinned<=binnedPlot->GetNbinsX()+1; ++binRebinned){
if(binnedPlot->GetBinLowEdge(binRebinned)<=xlow&&binnedPlot->GetBinLowEdge(binRebinned+1)>=xhigh){
found=true;
binnedPlot->SetBinContent(binRebinned, binnedPlot->GetBinContent(binRebinned)+y);
break;
}
//else{
// std::cout << "not in: " << binnedPlot->GetBinLowEdge(binRebinned) << ".." << binnedPlot->GetBinLowEdge(binRebinned+1)<< std::endl;
//}
}
// --------------------
// use linear interpolation for edge bins
// --------------------
if(hist->GetBinCenter(bin)<high&&!found){
std::cout << "need interpolation for bin" << bin << "(<x>=" << hist->GetBinCenter(bin) << ")!"<< std::endl;
// search for the two bins involved
double binLow=0;
double binHigh=0;
for(int binRebinned=1; binRebinned<=binnedPlot->GetNbinsX(); ++binRebinned){
// search for bin in binned histo where upper border of is close to lower border of unbinned histo
if(std::abs(binnedPlot->GetBinLowEdge(binRebinned+1)-xlow)<binwidth){
binLow =binRebinned;
binHigh=binRebinned+1;
break;
}
}
std::cout << "theory bin " << xlow << ".." << xhigh << "-> reco bins ";
std::cout << binnedPlot->GetBinLowEdge(binLow) << ".." << binnedPlot->GetBinLowEdge(binLow+1) << " & ";
std::cout << binnedPlot->GetBinLowEdge(binHigh) << ".." << binnedPlot->GetBinLowEdge(binHigh+1) << std::endl;
// get the two points (this bin and the previous one)
double x2=hist->GetBinCenter (bin );
double x1=hist->GetBinCenter (bin-1);
double x3=hist->GetBinCenter (bin+1);
double y2=hist->GetBinContent(bin );
double y1=hist->GetBinContent(bin-1);
double y3=hist->GetBinContent(bin+1);
// calculate linear funtion
double a=(y2-y1)/(x2-x1);
double b=y1-a*x1;
TF1* linInterpol=new TF1("linInterpol"+getTStringFromInt(bin), "[0]*x+[1]", x1, x2);
linInterpol->SetParameter(0,a);
linInterpol->SetParameter(1,b);
// calculate the corresponding area of linear function to binned curve
double contributionLowerBin=linInterpol->Integral(xlow,binnedPlot->GetBinLowEdge(binHigh));
double contributionUpperBin=linInterpol->Integral(binnedPlot->GetBinLowEdge(binHigh),xhigh);
// draw interpolation function for checking
linInterpol->SetRange(xlow,xhigh);
linInterpol->SetLineColor(kMagenta);
linInterpol->DrawClone("same");
// eventually use quadratic interpolation for the first harens m(ttbar) bin
if(theory=="ahrens"&&variable.Contains("ttbarMass")&&usequad&&x2<450){
// calculate quadratic funtion
double a2=(y2-((y3-y1))*(x2-x1)/(x3-x1))/(x2*x2-x1*x1-(x2-x1)*(x3*x3+x1*x1)/(x3-x1));
double b2=((y3-y1)-a2*(x3*x3-x1*x1))/(x3-x1);
double c2=y1-a2*x1*x1-b*x1;
TF1* quadInterpol=new TF1("quadInterpol"+getTStringFromInt(bin), "[0]*x*x+[1]*x+[2]", x1, x2);
quadInterpol->SetParameter(0,a2);
quadInterpol->SetParameter(1,b2);
quadInterpol->SetParameter(2,c2);
// draw quad interpolation function for checking
quadInterpol->SetRange(xlow,xhigh);
quadInterpol->SetLineColor(kGreen);
quadInterpol->SetLineStyle(2);
hist->Fit(quadInterpol, "", "same", x1, x3);
// calculate the corresponding area of linear function to binned curve
quadInterpol->DrawClone("same");
double areaLow =quadInterpol->Integral(xlow,binnedPlot->GetBinLowEdge(binHigh) );
double areaHigh=quadInterpol->Integral(binnedPlot->GetBinLowEdge(binHigh),xhigh);
std::cout << "ratio(high/low) linear/quadratic: " << contributionUpperBin/contributionLowerBin << "/"<< areaHigh/areaLow << std::endl;
contributionLowerBin=y2*binwidth*areaLow /(areaLow+areaHigh);
contributionUpperBin=y2*binwidth*areaHigh/(areaLow+areaHigh);
}
// add fitted result
binnedPlot->SetBinContent(binLow , binnedPlot->GetBinContent(binLow )+contributionLowerBin);
binnedPlot->SetBinContent(binHigh, binnedPlot->GetBinContent(binHigh)+contributionUpperBin);
}
}
// ensure over/underflow is 0
binnedPlot->SetBinContent(0, 0.);
binnedPlot->SetBinContent(binnedPlot->GetNbinsX()+1, 0.);
// ensure normalization
binnedPlot->Scale(1./(binnedPlot->Integral(0.,binnedPlot->GetNbinsX()+1)));
// divide by binwidth
if(divideByBinwidth){
for(int bin=1; bin<=binnedPlot->GetNbinsX(); ++bin){
binnedPlot->SetBinContent(bin, binnedPlot->GetBinContent(bin)/binnedPlot->GetBinWidth(bin));
}
}
std::cout << "-------------------------------------------" << std::endl;
std::cout << "result: binned output histo" << std::endl;
for(int bin=1; bin<=binnedPlot->GetNbinsX(); ++bin){
std::cout << "content bin " << bin << " (" << binnedPlot->GetBinLowEdge(bin) << ".." << binnedPlot->GetBinLowEdge(bin+1) << ")= " << binnedPlot->GetBinContent(bin) << std::endl;
}
// styling
binnedPlot->SetLineColor(kBlue);
binnedPlot->SetLineWidth(2);
std::cout << "draw rebinned theory curve " << std::endl;
binnedPlot->Draw("hist same");
// draw bin boundaries
std::cout << "draw bin boundaries " << std::endl;
int binColor=kRed;
int binWidth=2;
int binStyle=6;
for(int bin=0; bin<(int)bins_.size(); ++bin){
if(!variable.Contains("ttbarMass")||bins_[variable][bin]>=345.) drawLine(bins_[variable][bin], 0, bins_[variable][bin], hist->GetMaximum(), binColor, binWidth, binStyle);
}
TH1F* line=(TH1F*)hist->Clone("line");
line->SetLineColor(binColor);
line->SetLineWidth(binWidth);
line->SetLineStyle(binStyle);
// legend
TLegend *leg = new TLegend(0.7, 0.6, 0.95, 0.9);
legendStyle(*leg,theory);
if(points) leg ->AddEntry(ori, "original data points","P");
leg ->AddEntry(hist , "theory prediction" ,"P");
leg ->AddEntry(line , "reco binning" ,"L");
leg ->AddEntry(hist , "linear interpolation" ,"L");
leg ->AddEntry(binnedPlot, "rebinned curve" ,"L");
leg->Draw("same");
std::cout << "done" << std::endl;
// save in png and rootfile
std::cout << std::endl << "do saving..." << std::endl;
canv->SaveAs(variable+"Norm_Theory.png");
TH1F* out=(TH1F*)binnedPlot->Clone();
out->SetTitle(variable);
out->SetName (variable);
out->GetXaxis()->SetTitle(xSecLabelName(variable));
TString yTile="#frac{1}{#sigma} #frac{d#sigma}{d";
if(variable=="ttbarMass") yTile+="m^{t#bar{t}}} [GeV^{-1}]";
if(variable=="ttbarPt") yTile+="p_{T}^{t#bar{t}}} [GeV^{-1}]";
if(variable=="topPt") yTile+="p_{T}^{t}} [GeV^{-1}]";
if(variable=="topY" ) yTile+="y^{t}}";
out->GetYaxis()->SetTitle(yTile);
out->SetLineColor(kOrange+2);
out->SetLineStyle(2);
std::cout << std::endl << "draw final result " << std::endl;
TCanvas *canv2 = new TCanvas(variable+"Rebinned",variable+"Rebinned",800,600);
canv2->cd();
out->Draw();
saveToRootFile(outputRootFile, out , true, 0,"" );
saveToRootFile(outputRootFile, rawHist, true, 0,"graph" );
saveToRootFile(outputRootFile, canv , true, 0,"detail");
std::cout << "done!" << std::endl;
}
}
void V_t_continuous_grp7()
{
TCanvas *c1 = new TCanvas("c1", "Vxt", 800, 600);
TGraph *gr;
//TCanvas *c1 = new TCanvas("c1","A Simple Graph Example",200,10,700,500);
c1->SetFillColor(42);
c1->SetGrid();
const Int_t n = 20;
Double_t x[n], y[n];
//10 for -5 to +5V, 1 to -500mV to + 500 mV, 100 to -50 mv to + 50 mV
int scale = 1;
char FileName[200];
char ErrFile[200];
char Command[300];
//string err;
// Sweep timer:
time_t start;
bool started;
while(1)
{
//Need to be fixed to use the driver example program we adapted
//sprintf(Command,"./fald-acq -a 400000 -b 0 -n 1 -l 1 -g 1 -e -t 10 0100 > Data.txt");
sprintf(FileName,"%s/Data.txt",gSystem->pwd());
sprintf(ErrFile,"%s/Err.txt",gSystem->pwd());
gSystem->Exec("echo 0 > /sys/devices/hw-adc-100m14b-0100/adc-100m14b-0100/enable");
gSystem->Exec("echo 1 > /sys/devices/hw-adc-100m14b-0100/adc-100m14b-0100/enable");
//sleep(1);
//system("program args 1>/tmp/program.stdout 2>/tmp/program.stderr as in
//http://docstore.mik.ua/orelly/perl/cookbook/ch16_08.htm
//sprintf(Command,"%s/fald-acq -a 1000 -b 0 -n 1 -l 1 -g 1 -e -r 10 0100 1> %s 2> %s",gSystem->pwd(), FileName,ErrFile );
//sprintf(Command,"./fald-acq -a 100 -b 0 -n 1 -l 1 -g 1 -c 1 -t 10000 -r 10 0100 > %s",FileName);
//sprintf(Command,"%s/fald-acq -a 1000 -b 0 -n 1 -l 1 -g 1 -e -r 10 0100",gSystem->pwd());
//gSystem->Exec(Command);
sprintf(Command,"%s/fald-acq -a 500 -b 0 -n 1 -l 1 -g 1 -e -r 1 0100 1> %s 2> %s",gSystem->pwd(), FileName,ErrFile );
FILE *test = gSystem->OpenPipe(Command,"r");
gSystem->ClosePipe(test);
//gr = new TGraph("/tmp/fmcadc.0x0100.ch1.dat", "%lg %lg %*lg %*lg %*lg");
//gSystem->Sleep(100);
//if (TFile::SizeOf(FileName)<=0) break;
//cin >> err;
//cout << err << endl;
//strcmp(err,"./fald-acq: cannot start acquisition: Input/output error");
//cout <<"running" <<endl;
//cout << "TGraph *G1 = new TGraph(FileName = " << FileName << ") , loop i = " << i << endl;
//See the columns configuration in FileName
gr = new TGraph("/tmp/fmcadc.0x0100.ch1.dat", "%lg %lg");
//c1->cd();
// Get very first point of graph:
#define THRESHOLD 0.1
Double_t sample, value1, value2;
gr->GetPoint(0,sample,value1);
gr->GetPoint(3,sample,value2);
if(value1 < 0 && value2 > 0) {
std::cout << "Triggered!" << std::endl;
if(!started) {
// FIXME: use nicer timing function!
start = time(NULL);
started = true;
}
else {
double diff = time(NULL) - start;
started = false;
std::cout << "dT: " << diff << " / " << (1/diff) << "Hz" << std::endl;
}
}
gSystem->ProcessEvents();
//TGraph *G2 = new TGraph();
//cout <<"2" <<endl;
gr->SetLineColor(2);
gr->SetLineWidth(4);
gr->SetMarkerColor(4);
gr->SetMarkerStyle(21);
//cout <<"a simple graph" <<endl;
gr->SetTitle("Vxt");
gr->GetXaxis()->SetTitle("time sample");
gr->GetYaxis()->SetTitle("Volts");
//cout <<"3" <<endl;
gr->Draw("ACP");
gSystem->ProcessEvents();
//cout << "Draw" << endl;
//cout <<"4" <<endl;
// TCanvas::Update() draws the frame, after which one can change it
c1->Update();
c1->GetFrame()->SetFillColor(21);
c1->GetFrame()->SetBorderSize(12);
c1->Modified();
//cout <<"5" <<endl;
gSystem->ProcessEvents();
}
//gr = new TGraph(n,x,y);
delete gr;
cout << "Bye" << endl;
delete c1;
//
return;
}
bool check(int n = 2) {
TFile *file = TFile::Open(TString::Format("merged%d.root",n));
bool result = true;
TH1F *h; file->GetObject("h1",h);
if (!h) {
Error("execFileMerger","h1 is missing\n");
result = false;
}
if (h->GetBinContent(2) != n || h->GetBinContent(3) != n) {
Error("execFileMerger","h1 not added properly");
result = false;
}
THnSparseF *sparse; file->GetObject("sparse",sparse);
if (!sparse) {
Error("execFileMerger","sparse is missing\n");
result = false;
} else {
Int_t coordIdx[5] = {1, 2, 3, 4, 5};
Double_t cont = sparse->GetBinContent(coordIdx);
if (cont > n + 0.4 || cont < n - 0.4) {
Error("execFileMerger","sparse merge failed: expected bin content %g, read %g\n",
(Double_t)n, cont);
result = false;
}
Double_t entries = sparse->GetEntries();
if (entries > n + 0.4 || entries < n - 0.4) {
Error("execFileMerger","sparse merge failed: expected %g entries, read %g\n",
(Double_t)n, entries);
result = false;
}
}
THStack *stack; file->GetObject("stack",stack);
if (!stack) {
Error("execFileMerger","stack is missing\n");
result = false;
}
h = (TH1F*)stack->GetHists()->FindObject("hs_1");
if (!h) {
Error("execFileMerger","hs_1 is missing\n");
result = false;
}
if (h->GetBinContent(2) != n || h->GetBinContent(3) != n) {
Error("execFileMerger","hs_1 not added properly");
result = false;
}
h = (TH1F*)stack->GetHists()->FindObject("hs_2");
if (!h) {
Error("execFileMerger","hs_2 is missing\n");
result = false;
}
if (h->GetBinContent(4) != n || h->GetBinContent(5) != n) {
Error("execFileMerger","hs_2 not added properly");
result = false;
}
TGraph *gr; file->GetObject("exgraph",gr);
if (!gr) {
Error("execFileMerger","exgraph is missing\n");
result = false;
}
if (gr->GetN() != ( n * 3)) {
Error("execFileMerger","exgraph not added properly n=%d rather than %d",gr->GetN(),n*3);
result = false;
} else {
for(Int_t k = 0; k < gr->GetN(); ++k) {
double x,y;
gr->GetPoint(k,x,y);
if ( x != ( (k%3)+1 ) || y != ( (k%3)+1 ) ) {
Error("execFileMerger","exgraph not added properly");
result = false;
}
}
}
TTree *tree; file->GetObject("tree",tree);
if (!tree) {
Error("execFileMerger","tree is missing\n");
result = false;
}
if (tree->GetEntries() != n*2) {
Error("execFileMerger","tree does not have the expected number of entries: %lld rather than %d",tree->GetEntries(),n*2);
result = false;
} else {
if ( tree->GetEntries("data==1") != n ) {
Error("execFileMerger","tree does not have the expected data. We got %lld entries with 'data==1' rather than %d",tree->GetEntries("data==1"),n);
tree->Scan();
result = false;
}
}
return result;
}
void get_results(){
gROOT->SetStyle("Plain");
printf("\n");
printf(" ---------------------------------------------------------------------------\n");
printf(" Sensitivity vs. nSig and Sigma in Fit\n");
printf(" ---------------------------------------------------------------------------\n");
printf(" nSig / SigFit--> | 0.1 | 0.2 | 0.3 | 0.4 | W. Avg (val) \n");
printf(" ---------------------------------------------------------------------------\n");
Double_t p1x, p1y;
Double_t p2x, p2y;
Double_t ix, iy;
TObjArray *a1 = new TObjArray(0);
TGraph *graph0130 = new TGraph(5);
graph0130->SetTitle("Sensitivity vs. Sig-fit");
graph0130->SetName("graph0130");
TGraph *graph1 = new TGraph(5);
graph1->SetTitle("Sensitivity vs. Sig-fit");
graph1->SetName("graph1");
TGraph *graph0196 = new TGraph(5);
graph0196->SetTitle("Sensitivity vs. Sig-fit");
graph0196->SetName("graph0196");
TCanvas *can1 = new TCanvas("can1", "varfits1", 1500, 900);
can1->Divide(5,3);
/***************************************************************************
nSig = 0.130
****************************************************************************/
// =================== nsig=0.130, tSig=0.1 Sig-fit=0.1 ==================
can1->cd(1);
gPad->SetGrid();
TFile lhns("varsig0130_1.root");
TGraph *gs130_1 = (TGraph*)lhns.Get("DilErrvsdm");
gs130_1->SetTitle("nSig=0.130, tSig=0.1, Sig-fit=0.1");
gs130_1->SetName("gs130_1");
gs130_1->GetXaxis()->SetTitle("dm");
gs130_1->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs130_1->Draw("AP*");
gs130_1->GetPoint(16, p1x, p1y);
gs130_1->GetPoint(17, p2x, p2y);
Double_t vs130_1 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph0130->SetPoint(0,0.1,vs130_1);
a1.Add(gs130_1);
// =================== nsig=0.130, tSig=0.1 Sig-fit=0.2 ==================
can1->cd(2);
gPad->SetGrid();
TFile lhns("varsig0130_2.root");
TGraph *gs130_2 = (TGraph*)lhns.Get("DilErrvsdm");
gs130_2->SetTitle("nSig=0.130, tSig=0.1, Sig-fit=0.2");
gs130_2->SetName("gs130_2");
gs130_2->GetXaxis()->SetTitle("dm");
gs130_2->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs130_2->Draw("AP*");
gs130_2->GetPoint(14, p1x, p1y);
gs130_2->GetPoint(15, p2x, p2y);
Double_t vs130_2 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph0130->SetPoint(1,0.2,vs130_2);
a1.Add(gs130_2);
// =================== nsig=0.130, tSig=0.1 Sig-fit=0.3 ====================
can1->cd(3);
gPad->SetGrid();
TFile lhns("varsig0130_3.root");
TGraph *gs130_3 = (TGraph*)lhns.Get("DilErrvsdm");
gs130_3->SetTitle("nSig=0.130, tSig=0.1, Sig-fit=0.3");
gs130_3->SetName("gs130_3");
gs130_3->GetXaxis()->SetTitle("dm");
gs130_3->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs130_3->Draw("AP*");
gs130_3->GetPoint(10, p1x, p1y);
gs130_3->GetPoint(11, p2x, p2y);
Double_t vs130_3 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph0130->SetPoint(2,0.3,vs130_3);
a1.Add(gs130_3);
// =================== nsig=0.130, tSig=0.1 Sig-fit=0.4 ====================
can1->cd(4);
gPad->SetGrid();
TFile lhns("varsig0130_4.root");
TGraph *gs130_4 = (TGraph*)lhns.Get("DilErrvsdm");
gs130_4->SetTitle("nSig=0.130, tSig=0.1, Sig-fit=0.4");
gs130_4->SetName("gs130_4");
gs130_4->GetXaxis()->SetTitle("dm");
gs130_4->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs130_4->Draw("AP*");
gs130_4->GetPoint(13, p1x, p1y);
gs130_4->GetPoint(14, p2x, p2y);
Double_t vs130_4 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph0130->SetPoint(3,0.4,vs130_4);
a1.Add(gs130_4);
// =================== nsig=0.130, tSig=0.1 Sig-fit=Avg =====================
can1->cd(5);
gPad->SetGrid();
TFile lhns("varsig0130_a.root");
TGraph *gs130_a = (TGraph*)lhns.Get("DilErrvsdm");
gs130_a->SetTitle("nSig=0.130, tSig=0.1, Sig-fit=Avg");
gs130_a->SetName("gs130_a");
gs130_a->GetXaxis()->SetTitle("dm");
gs130_a->GetYaxis()->SetTitle("95% CL");
TGraph *gs130_sf = (TGraph*)lhns.Get("SigFit");
gs130_sf->SetTitle("Sigma_Avg in Fit vs. dm , nSig=0.130");
gs130_sf->SetName("gs130_sf");
gs130_sf->GetXaxis()->SetTitle("dm");
gs130_sf->GetYaxis()->SetTitle("Sigma in Fit");
lhns.Close();
gs130_a->Draw("AP*");
gs130_a->GetPoint(12, p1x, p1y);
gs130_a->GetPoint(13, p2x, p2y);
Double_t vs130_a = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph0130->SetPoint(4,0.270111,vs130_a);
a1.Add(gs130_a);
a1.Add(gs130_sf);
printf(" 0.130 | %5.3f | %5.3f | %5.3f | %5.3f | %5.3f (0.270) \n",vs130_1,vs130_2,vs130_3,vs130_4,vs130_a);
//----------- plot the sig-fit vs. dm; histogram sig-fit -----
TCanvas *c0130sf = new TCanvas("Sigfit_vs_dm_0130", "graph0130sf", 800, 400);
c0130sf->Divide(2,1);
c0130sf->cd(1);
gPad->SetGrid();
gs130_sf->Draw("AP*");
c0130sf->cd(2);
TH1F *hs0130_sf = new TH1F("hs0130_sf", "SigFit spread, nSig=0.130", 10, 0.26, 0.28);
for (Int_t i=0.; i<20.; i++){
gs130_sf->GetPoint(i,ix,iy);
//cout << i << ", "<< ix << ", "<< iy <<endl;
hs0130_sf->Fill(iy);
}
gPad->SetGrid();
hs0130_sf->Draw();
a1.Add(hs0130_sf);
a1.Add(c0130sf);
//--------------- plot the sensitivity vs sig-fit -----------
TCanvas *c0130 = new TCanvas("Sens_vs_sigfit_0130", "graph0130", 400, 400);
c0130->SetGrid();
graph0130->GetXaxis()->SetTitle("Sigma in fit");
graph0130->GetYaxis()->SetTitle("Sensitivity");
graph0130->Draw("AP*");
a1.Add(graph0130);
a1.Add(c0130);
/***************************************************************************
nSig = 0.163
**************************************************************************/
// ================== nsig=0.163, tSig=0.1 Sig-fit=0.1 ==================
can1->cd(6);
gPad->SetGrid();
TFile lhns("varsigma_1.root");
TGraph *gs1 = (TGraph*)lhns.Get("DilErrvsdm");
gs1->SetTitle("nSig=0.163, tSig=0.1, Sig-fit=0.1");
gs1->SetName("gs1");
gs1->GetXaxis()->SetTitle("dm");
gs1->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs1->Draw("AP*");
gs1->GetPoint(16, p1x, p1y);
gs1->GetPoint(17, p2x, p2y);
Double_t vs1 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph1->SetPoint(0,0.1,vs1);
a1.Add(gs1);
// ================== nsig=0.163, tSig=0.1 Sig-fit=0.2 ==================
can1->cd(7);
gPad->SetGrid();
TFile lhns("varsigma_2.root");
TGraph *gs2 = (TGraph*)lhns.Get("DilErrvsdm");
gs2->SetTitle("nSig=0.163, tSig=0.1, Sig-fit=0.2");
gs2->SetName("gs2");
gs2->GetXaxis()->SetTitle("dm");
gs2->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs2->Draw("AP*");
gs2->GetPoint(14, p1x, p1y);
gs2->GetPoint(15, p2x, p2y);
Double_t vs2 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph1->SetPoint(1,0.2,vs2);
a1.Add(gs2);
// ================== nsig=0.163, tSig=0.1 Sig-fit=0.3 ==================
can1->cd(8);
gPad->SetGrid();
TFile lhns("varsigma_3.root");
TGraph *gs3 = (TGraph*)lhns.Get("DilErrvsdm");
gs3->SetTitle("nSig=0.163, tSig=0.1, Sig-fit=0.3");
gs3->SetName("gs3");
gs3->GetXaxis()->SetTitle("dm");
gs3->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs3->Draw("AP*");
gs3->GetPoint(10, p1x, p1y);
gs3->GetPoint(11, p2x, p2y);
Double_t vs3 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph1->SetPoint(2,0.3,vs3);
a1.Add(gs3);
// ================== nsig=0.163, tSig=0.1 Sig-fit=0.4 ==================
can1->cd(9);
gPad->SetGrid();
TFile lhns("varsigma_4.root");
TGraph *gs4 = (TGraph*)lhns.Get("DilErrvsdm");
gs4->SetTitle("nSig=0.163, tSig=0.1, Sig-fit=0.4");
gs4->SetName("gs4");
gs4->GetXaxis()->SetTitle("dm");
gs4->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs4->Draw("AP*");
gs4->GetPoint(13, p1x, p1y);
gs4->GetPoint(14, p2x, p2y);
Double_t vs4 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph1->SetPoint(3,0.4,vs4);
a1.Add(gs4);
// ================== nsig=0.163, tSig=0.1 Sig-fit=Avg ==================
can1->cd(10);
gPad->SetGrid();
TFile lhns("varsigma_a.root");
TGraph *gsa = (TGraph*)lhns.Get("DilErrvsdm");
gsa->SetTitle("nSig=0.163, tSig=0.1, Sig-fit=Avg");
gsa->SetName("gsa");
gsa->GetXaxis()->SetTitle("dm");
gsa->GetYaxis()->SetTitle("95% CL");
TGraph *gs_sf = (TGraph*)lhns.Get("SigFit");
gs_sf->SetTitle("Sigma_Avg in Fit vs. dm , nSig=0.163");
gs_sf->SetName("gs_sf");
gs_sf->GetXaxis()->SetTitle("dm");
gs_sf->GetYaxis()->SetTitle("Sigma in Fit");
lhns.Close();
gsa->Draw("AP*");
gsa->GetPoint(11, p1x, p1y);
gsa->GetPoint(12, p2x, p2y);
Double_t vsa = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph1->SetPoint(4,0.313349,vsa);
a1.Add(gsa);
a1.Add(gs_sf);
printf(" 0.163 | %5.3f | %5.3f | %5.3f | %5.3f | %5.3f (0.313) \n",vs1,vs2,vs3,vs4,vsa);
//----------- plot the sig-fit vs. dm; histogram sig-fit -----
TCanvas *csf = new TCanvas("Sigfit_vs_dm_0163", "graphsf", 800, 400);
csf->Divide(2,1);
csf->cd(1);
gPad->SetGrid();
gs_sf->Draw("AP*");
csf->cd(2);
TH1F *hs_sf = new TH1F("hs_sf", "SigFit spread, nSig=0.163", 10, 0.3, 0.325);
for (Int_t i=0.; i<20.; i++){
gs_sf->GetPoint(i,ix,iy);
//cout << i << ", "<< ix << ", "<< iy <<endl;
hs_sf->Fill(iy);
}
gPad->SetGrid();
hs_sf->Draw();
a1.Add(hs_sf);
a1.Add(csf);
//--------------- plot the sensitivity vs sig-fit -----------
TCanvas *can2 = new TCanvas("Sens_vs_sigfit_0163", "graph1", 400, 400);
can2->SetGrid();
graph1->GetXaxis()->SetTitle("Sigma in fit");
graph1->GetYaxis()->SetTitle("Sensitivity");
graph1->Draw("AP*");
a1.Add(graph1);
a1.Add(can2);
/***************************************************************************
nSig = 0.196
**************************************************************************/
// ================== nsig=0.196, tSig=0.1 Sig-fit=0.1 ==================
can1->cd(11);
gPad->SetGrid();
TFile lhns("varsig0196_1.root");
TGraph *gs196_1 = (TGraph*)lhns.Get("DilErrvsdm");
gs196_1->SetTitle("nSig=0.196, tSig=0.1, Sig-fit=0.1");
gs196_1->SetName("gs196_1");
gs196_1->GetXaxis()->SetTitle("dm");
gs196_1->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs196_1->Draw("AP*");
gs196_1->GetPoint(16, p1x, p1y);
gs196_1->GetPoint(17, p2x, p2y);
Double_t vs196_1 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph0196->SetPoint(0,0.1,vs196_1);
a1.Add(gs196_1);
// ================== nsig=0.196, tSig=0.1 Sig-fit=0.2 ====================
can1->cd(12);
gPad->SetGrid();
TFile lhns("varsig0196_2.root");
TGraph *gs196_2 = (TGraph*)lhns.Get("DilErrvsdm");
gs196_2->SetTitle("nSig=0.196, tSig=0.1, Sig-fit=0.2");
gs196_2->SetName("gs196_2");
gs196_2->GetXaxis()->SetTitle("dm");
gs196_2->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs196_2->Draw("AP*");
gs196_2->GetPoint(14, p1x, p1y);
gs196_2->GetPoint(15, p2x, p2y);
Double_t vs196_2 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph0196->SetPoint(1,0.2,vs196_2);
a1.Add(gs196_2);
// ================== nsig=0.196, tSig=0.1 Sig-fit=0.3 ==================
can1->cd(13);
gPad->SetGrid();
TFile lhns("varsig0196_3.root");
TGraph *gs196_3 = (TGraph*)lhns.Get("DilErrvsdm");
gs196_3->SetTitle("nSig=0.196, tSig=0.1, Sig-fit=0.3");
gs196_3->SetName("gs196_3");
gs196_3->GetXaxis()->SetTitle("dm");
gs196_3->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs196_3->Draw("AP*");
gs196_3->GetPoint(10, p1x, p1y);
gs196_3->GetPoint(11, p2x, p2y);
Double_t vs196_3 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph0196->SetPoint(2,0.3,vs196_3);
a1.Add(gs196_3);
// ================== nsig=0.196, tSig=0.1 Sig-fit=0.4 ==================
can1->cd(14);
gPad->SetGrid();
TFile lhns("varsig0196_4.root");
TGraph *gs196_4 = (TGraph*)lhns.Get("DilErrvsdm");
gs196_4->SetTitle("nSig=0.196, tSig=0.1, Sig-fit=0.4");
gs196_4->SetName("gs196_4");
gs196_4->GetXaxis()->SetTitle("dm");
gs196_4->GetYaxis()->SetTitle("95% CL");
lhns.Close();
gs196_4->Draw("AP*");
gs196_4->GetPoint(13, p1x, p1y);
gs196_4->GetPoint(14, p2x, p2y);
Double_t vs196_4 = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph0196->SetPoint(3,0.4,vs196_4);
a1.Add(gs196_4);
// ================== nsig=0.196, tSig=0.1 Sig-fit=Avg ==================
can1->cd(15);
gPad->SetGrid();
TFile lhns("varsig0196_a.root");
TGraph *gs196_a = (TGraph*)lhns.Get("DilErrvsdm");
gs196_a->SetTitle("nSig=0.196, tSig=0.1, Sig-fit=Avg");
gs196_a->SetName("gs196_a");
gs196_a->GetXaxis()->SetTitle("dm");
gs196_a->GetYaxis()->SetTitle("95% CL");
TGraph *gs196_sf = (TGraph*)lhns.Get("SigFit");
gs196_sf->SetTitle("Sigma(Avg) in Fit vs. dm (nSig=0.196)");
gs196_sf->SetName("gs196_sf");
gs196_sf->GetXaxis()->SetTitle("dm");
gs196_sf->GetYaxis()->SetTitle("Sigma in Fit");
lhns.Close();
gs196_a->Draw("AP*");
gs196_a->GetPoint(10, p1x, p1y);
gs196_a->GetPoint(11, p2x, p2y);
Double_t vs196_a = (((1-p1y)/(1-p2y))*p2x - p1x)/(((1-p1y)/(1-p2y))-1);
graph0196->SetPoint(4,0.356301,vs196_a);
a1.Add(gs196_a);
a1.Add(gs196_sf);
printf(" 0.196 | %5.3f | %5.3f | %5.3f | %5.3f | %5.3f (0.270) \n",vs196_1,vs196_2,vs196_3,vs196_4,vs196_a);
//----------- plot the sig-fit vs. dm; histogram sig-fit -----
TCanvas *c0196sf = new TCanvas("Sigfit_vs_dm_0196", "graph0196sf", 800, 400);
c0196sf->Divide(2,1);
c0196sf->cd(1);
gPad->SetGrid();
gs196_sf->Draw("AP*");
c0196sf->cd(2);
TH1F *hs0196_sf = new TH1F("hs0196_sf", "SigFit spread, nSig=0.196", 10, 0.34, 0.37);
for (Int_t i=0.; i<20.; i++){
gs196_sf->GetPoint(i,ix,iy);
//cout << i << ", "<< ix << ", "<< iy <<endl;
hs0196_sf->Fill(iy);
}
gPad->SetGrid();
hs0196_sf->Draw();
a1.Add(hs0196_sf);
a1.Add(c0196sf);
//--------------- plot the sensitivity vs sig-fit -----------
TCanvas *c0196 = new TCanvas("Sens_vs_sigfit_0196", "graph0196", 400, 400);
c0196->SetGrid();
graph0196->GetXaxis()->SetTitle("Sigma in fit");
graph0196->GetYaxis()->SetTitle("Sensitivity");
graph0196->Draw("AP*");
a1.Add(graph0196);
a1.Add(c0196);
a1.Add(can1);
//can1->Close();
/***************************************************************************
**************************************************************************/
printf(" ---------------------------------------------------------------------------\n");
printf("\n");
TCanvas *combined = new TCanvas("Sens_vs_dm_combined", "combined", 400, 400);
combined->SetGrid();
graph0130->SetMarkerColor(4);
graph0130->SetMarkerStyle(4);
graph0130->Draw("AP");
graph1->SetMarkerColor(2);
graph1->SetMarkerStyle(22);
graph1->Draw("P");
graph0196->SetMarkerColor(8);
graph0196->SetMarkerStyle(28);
graph0196->Draw("P");
a1.Add(combined);
TFile file1("get_results.root", "recreate");
a1.Write();
file1.Close();
}
void Polarization(){
TGraph *gObs;
TGraph *gExp;
TGraph *gObsL;
TGraph *gExpL;
TGraph *gObsR;
TGraph *gExpR;
TFile *fc = TFile::Open("Limits2DHistograms_T2tt_postfit.root");
TFile *fl = TFile::Open("Limits2DHistograms_T2tt_lefthanded_postfit.root");
TFile *fr = TFile::Open("Limits2DHistograms_T2tt_righthanded_postfit.root");
TGraph *g;
fc->cd();
g = (TGraph*)fc->Get("gObs");
gObs = (TGraph*)g->Clone("Obs");
g = (TGraph*)fc->Get("gExp");
gExp = (TGraph*)g->Clone("Exp");
fl->cd();
g = (TGraph*)fl->Get("gObs_2");
gObsL = (TGraph*)g->Clone("ObsL");
g = (TGraph*)fl->Get("gExp_2");
gExpL = (TGraph*)g->Clone("ExpL");
fr->cd();
g = (TGraph*)fr->Get("gObs");
gObsR = (TGraph*)g->Clone("ObsR");
g = (TGraph*)fr->Get("gExp");
gExpR = (TGraph*)g->Clone("ExpR");
gObs->SetLineWidth(4);
gExp->SetLineWidth(4);
gObsL->SetLineWidth(2);
gExpL->SetLineWidth(2);
gObsR->SetLineWidth(2);
gExpR->SetLineWidth(2);
gObs->SetLineStyle(1);
gExp->SetLineStyle(7);
gObsL->SetLineStyle(1);
gExpL->SetLineStyle(7);
gObsR->SetLineStyle(1);
gExpR->SetLineStyle(7);
gObs->SetLineColor(kBlack);
gExp->SetLineColor(kBlack);
gObsL->SetLineColor(kBlue);
gExpL->SetLineColor(kBlue);
gObsR->SetLineColor(kRed);
gExpR->SetLineColor(kRed);
if(killlowdiag){
for( int i = gObs->GetN()-1; i>=0;--i){
double x,y;
gObs->GetPoint(i,x,y);
if(x-y<172.5) gObs->RemovePoint(i);
}
for( int i = gExp->GetN()-1; i>=0;--i){
double x,y;
gExp->GetPoint(i,x,y);
if(x-y<172.5) gExp->RemovePoint(i);
}
}
for( int i = gObsL->GetN()-1; i>=0;--i){
double x,y;
gObsL->GetPoint(i,x,y);
if(x-y<172.5) gObsL->RemovePoint(i);
}
for( int i = gObsR->GetN()-1; i>=0;--i){
double x,y;
gObsR->GetPoint(i,x,y);
if(x-y<172.5) gObsR->RemovePoint(i);
}
for( int i = gExpL->GetN()-1; i>=0;--i){
double x,y;
gExpL->GetPoint(i,x,y);
if(x-y<172.5) gExpL->RemovePoint(i);
}
for( int i = gExpR->GetN()-1; i>=0;--i){
double x,y;
gExpR->GetPoint(i,x,y);
if(x-y<172.5) gExpR->RemovePoint(i);
}
TCanvas *c1 = new TCanvas("c1", "c1",50,50,600,600);
gStyle->SetOptFit(1);
gStyle->SetOptStat(0);
gStyle->SetOptTitle(0);
gStyle->SetErrorX(0.5);
//c1->Range(-6.311689,-1.891383,28.75325,4.56342);
c1->SetFillColor(0);
c1->SetBorderMode(0);
c1->SetBorderSize(2);
//c1->SetLogy();
c1->SetTickx(1);
c1->SetTicky(1);
c1->SetLeftMargin(0.15);
c1->SetRightMargin(0.05);
c1->SetTopMargin(0.07);
c1->SetBottomMargin(0.15);
c1->SetFrameFillStyle(0);
c1->SetFrameBorderMode(0);
c1->SetFrameFillStyle(0);
c1->SetFrameBorderMode(0);
gStyle->SetHatchesLineWidth(0);
TH1F *hSum = new TH1F("hSum","",10,150,950);
hSum->SetMinimum(0.);
hSum->SetMaximum(550);
hSum->SetDirectory(0);
hSum->SetStats(0);
hSum->Draw();
hSum->GetYaxis()->SetRangeUser(0,500);
hSum->GetXaxis()->SetRangeUser(150,950);
Int_t ci; // for color index setting
ci = TColor::GetColor("#000099");
hSum->SetLineColor(ci);
hSum->SetLineStyle(0);
hSum->SetMarkerStyle(20);
hSum->GetXaxis()->SetTitle("m_{#tilde{t}} [GeV]");
//hSum->GetXaxis()->SetBit(TAxis::kLabelsVert);
hSum->GetXaxis()->SetLabelFont(42);
//hSum->GetXaxis()->SetLabelOffset(0.005);
hSum->GetXaxis()->SetLabelSize(0.035);
hSum->GetXaxis()->SetTitleSize(0.06);
hSum->GetXaxis()->SetTitleOffset(1.2);
hSum->GetXaxis()->SetTitleFont(42);
hSum->GetYaxis()->SetTitle("m_{#tilde{#chi}}_{1}^{0} [GeV]");
hSum->GetYaxis()->SetLabelFont(42);
//hSum->GetYaxis()->SetLabelOffset(0.007);
hSum->GetYaxis()->SetLabelSize(0.035);
hSum->GetYaxis()->SetTitleSize(0.05);
hSum->GetYaxis()->SetTitleOffset(1.3);
hSum->GetYaxis()->SetTitleFont(42);
//TLegend *leg = new TLegend(0.4992416,0.4811189,0.898906,0.7503497,NULL,"brNDC");
//TLegend *leg = new TLegend(0.4992416,0.4811189,0.698906,0.7503497,NULL,"brNDC");
//TLegend *leg = new TLegend(0.6992416,0.2811189,0.898906,0.4503497,NULL,"brNDC");
//TLegend *leg = new TLegend(0.6992416,0.3311189,0.898906,0.7903497,NULL,"brNDC");
//TLegend *leg = new TLegend(0.7582416,0.4211189,0.912,0.8043497,NULL,"brNDC");
TLegend *legE = new TLegend(0.51,0.675,0.81,0.855,NULL,"brNDC");
//leg-> SetNColumns(2);
legE->SetBorderSize(0);
legE->SetTextSize(0.04);
legE->SetTextFont(42);
legE->SetLineColor(1);
legE->SetLineStyle(1);
legE->SetLineWidth(2);
legE->SetFillColor(0);
legE->SetFillStyle(1001);
legE->SetHeader("Expected");
legE->AddEntry(gExp, "unpolarized","l");
legE->AddEntry(gExpR, "right-handed","l");
legE->AddEntry(gExpL, "left-handed","l");
TLegend *legO = new TLegend(0.175,0.675,0.50,0.855,NULL,"brNDC");
//legO-> SetNColumns(2);
legO->SetBorderSize(0);
legO->SetTextSize(0.04);
legO->SetTextFont(42);
legO->SetLineColor(1);
legO->SetLineStyle(1);
legO->SetLineWidth(2);
legO->SetFillColor(0);
legO->SetFillStyle(1001);
legO->SetHeader("Observed");
legO->AddEntry(gObs, "unpolarized","l");
legO->AddEntry(gObsR, "right-handed","l");
legO->AddEntry(gObsL, "left-handed","l");
TGraph* graphWhite = new TGraph(5);
graphWhite->SetName("white");
graphWhite->SetTitle("white");
graphWhite->SetFillColor(kWhite);
graphWhite->SetFillStyle(1001);
graphWhite->SetLineColor(kBlack);
graphWhite->SetLineStyle(1);
graphWhite->SetLineWidth(3);
graphWhite->SetPoint(0,150, 500);
graphWhite->SetPoint(1,950, 500);
graphWhite->SetPoint(2,950, 500*0.6666666667);
graphWhite->SetPoint(3,150, 500*0.6666666667);
graphWhite->SetPoint(4,150, 500);
Float_t diagX[4] = {175.+25.,175.+25.+5000,175.-25.+5000,175.-25.};
Float_t diagY[4] = {0,5000,5000,0};
TGraph *gdiagonal = new TGraph(4, diagX, diagY);
gdiagonal->SetName("MtopDiagonal");
gdiagonal->SetFillColor(kWhite);
//#gdiagonal->SetFillColor(18);
TLine* ldiagonal = new TLine(175,0.,650-25.,450);
//TLine* ldiagonal = new TLine(175.,25,175+500,500);
ldiagonal->SetLineColor(kGray);
ldiagonal->SetLineStyle(2);
TLatex* tdiagonal = new TLatex(400-2.5, 400-172.5,"m_{#tilde{t}} = m_{t} + m_{#tilde{#chi}_{1}^{0}}");
//tdiagonal->SetTextAngle(TMath::RadToDeg()*TMath::ATan(float(800)/float(500)));
tdiagonal->SetTextAngle(56.31);
tdiagonal->SetTextColor(kGray+2);
tdiagonal->SetTextAlign(11);
tdiagonal->SetTextSize(0.025);
TLine* l2 = new TLine(150,75,585,500);
l2->SetLineColor(kGray);
l2->SetLineStyle(2);
if(killlowdiag){
l2->SetX1(200); l2->SetY1(0); l2->SetX2(600); l2->SetY2(400);
}
TLatex *t2 = new TLatex(300, 300-72.5,"m_{#tilde{t}} = m_{W} + m_{#tilde{#chi}_{1}^{0}}");
//t2->SetTextAngle(TMath::RadToDeg()*TMath::ATan(float(800)/float(500)));
t2->SetTextAngle(56.31);
t2->SetTextColor(kGray+2);
t2->SetTextAlign(11);
t2->SetTextSize(0.025);
hSum->Draw("axis");
gExpR->Draw("c");
gExpL->Draw("c");
gExp->Draw("c");
gObsR->Draw("c");
gObsL->Draw("c");
gObs->Draw("c");
gdiagonal->Draw("FSAME");
ldiagonal->Draw("LSAME");
l2->Draw();
if(!killlowdiag) t2->Draw();
tdiagonal->Draw("SAME");
graphWhite->Draw("FSAME");
graphWhite->Draw("LSAME");
legE->Draw();
legO->Draw();
TLatex* textModelLabel= new TLatex(0.175,0.92,"pp #rightarrow #tilde{t} #tilde{t}*, #tilde{t} #rightarrow t #tilde{#chi}^{0}_{1} NLO+NLL exclusion");
//TLatex* textModelLabel= new TLatex(0.175,0.92,"pp #rightarrow #tilde{t} #tilde{t}*, #tilde{t} #rightarrow t #tilde{#chi}^{0}_{1}");
//TLatex* textModelLabel= new TLatex(0.175,0.92,"#tilde{#chi} ");
textModelLabel->SetNDC();
textModelLabel->SetTextAlign(13);
textModelLabel->SetTextFont(42);
textModelLabel->SetTextSize(0.042);
textModelLabel->Draw();
//final CMS style
TLatex *tLumi = new TLatex(0.95,0.944,"2.3 fb^{-1} (13 TeV)");
tLumi->SetNDC();
tLumi->SetTextAlign(31);
tLumi->SetTextFont(42);
tLumi->SetTextSize(0.042);
tLumi->SetLineWidth(2);
tLumi->Draw();
TLatex *tCMS = new TLatex(0.152,0.944,"CMS");
tCMS->SetNDC();
tCMS->SetTextAlign(11);
tCMS->SetTextFont(61);
tCMS->SetTextSize(0.0525);
tCMS->SetLineWidth(2);
tCMS->Draw();
TLatex *tPrel = new TLatex(0.265,0.944,"Preliminary");
tPrel->SetNDC();
tPrel->SetTextAlign(11);
tPrel->SetTextFont(52);
tPrel->SetTextSize(0.042);
tPrel->SetLineWidth(2);
tPrel->Draw();
c1->Modified();
c1->cd();
c1->Update();
c1->SetSelected(c1);
}
TGraph*
DrawExpectedBand( TGraph* gr1, TGraph* gr2, Int_t fillColor, Int_t fillStyle, Int_t cut = 0)
{
// TGraph* gr1 = new TGraph( *graph1 );
// TGraph* gr2 = new TGraph( *graph2 );
int number_of_bins = max(gr1->GetN(),gr2->GetN());
const Int_t gr1N = gr1->GetN();
const Int_t gr2N = gr2->GetN();
const Int_t N = number_of_bins;
Double_t x1[N], y1[N], x2[N], y2[N];
Double_t xx0, yy0;
for(int j=0; j<gr1N; j++) {
gr1->GetPoint(j,xx0,yy0);
x1[j] = xx0;
y1[j] = yy0;
}
if (gr1N < N) {
for(int i=gr1N; i<N; i++) {
x1[i] = x1[gr1N-1];
y1[i] = y1[gr1N-1];
}
}
Double_t xx1, yy1;
for(int j=0; j<gr2N; j++) {
gr2->GetPoint(j,xx1,yy1);
x2[j] = xx1;
y2[j] = yy1;
}
if (gr2N < N) {
for(int i=gr2N; i<N; i++) {
x2[i] = x2[gr1N-1];
y2[i] = y2[gr1N-1];
}
}
TGraph *grshade = new TGraphAsymmErrors(2*N);
for (int i=0;i<N;i++) {
if (x1[i] > cut)
grshade->SetPoint(i,x1[i],y1[i]);
//cout<<"grshade x1="<< x1[i] <<" y1="<<y1[i]<<endl;
if (x2[N-i-1] > cut)
grshade->SetPoint(N+i,x2[N-i-1],y2[N-i-1]);
}
// Apply the cut in the shade plot if there is something that doesn't look good...
int Nshade = grshade->GetN();
double x0, y0;
double x00, y00;
for(int j=0; j<Nshade; j++) {
grshade->GetPoint(j,x0,y0);
if ((x0 != 0) && (y0 != 0)) {
x00 = x0;
y00 = y0;
break;
}
}
for(int j=0; j<Nshade; j++) {
grshade->GetPoint(j,x0,y0);
if ((x0 == 0) && (y0 == 0))
grshade->SetPoint(j,x00,y00);
}
// Now draw the plot...
grshade->SetFillStyle(fillStyle);
grshade->SetFillColor(fillColor);
grshade->SetMarkerStyle(21);
grshade->Draw("F");
return grshade;
}
///
/// Find an interpolated x value near a certain bin position of a histogram that is the
/// best estimate for h(x)=y. Interpolates by means of fitting a second grade polynomial
/// to up to five adjacent points. Because that's giving us two solutions, we use the central
/// value and knowledge about if it is supposed to be an upper or lower boundary to pick
/// one.
///
/// \param h - the histogram to be interpolated
/// \param i - interpolate around this bin. Must be a bin such that i and i+1 are above and below val
/// \param y - the y position we want to find the interpolated x for
/// \param central - Central value of the solution we're trying to get the CL interval for.
/// \param upper - Set to true if we're computing an upper interval boundary.
/// \param val - Return value: interpolated x position
/// \param err - Return value: estimated interpolation error
/// \return true, if inpterpolation was performed, false, if conditions were not met
///
bool CLIntervalMaker::interpolatePol2fit(const TH1F* h, int i, float y, float central, bool upper,
float &val, float &err) const
{
// cout << "CLIntervalMaker::interpolatePol2fit(): i=" << i << " y=" << y << " central=" << central << endl;
// check if too close to border so we don't have enough bins to fit
if ( !( 2 <= i && i <= h->GetNbinsX()-1 ) ) return false;
// check if all necessary bins are on the same side. They are not always,
// if e.g. in a plugin there's statistical fluctuations
if ( binsOnSameSide(i-1, y) && binsOnSameSide(i, y) ){
//cout << "CLIntervalMaker::interpolatePol2fit() : ERROR : bins i-1, i, and i+1 on same side of y" << endl;
return false;
}
// create a TGraph that we can fit
TGraph *g = new TGraph(3);
g->SetPoint(0, h->GetBinCenter(i-1), h->GetBinContent(i-1));
g->SetPoint(1, h->GetBinCenter(i), h->GetBinContent(i));
g->SetPoint(2, h->GetBinCenter(i+1), h->GetBinContent(i+1));
// see if we can add a 4th and 5th point:
if ( 3 <= i && i <= h->GetNbinsX()-2 ){
// add a point to the beginning
if ( (h->GetBinContent(i-2) < h->GetBinContent(i-1) && h->GetBinContent(i-1) < h->GetBinContent(i))
|| (h->GetBinContent(i-2) > h->GetBinContent(i-1) && h->GetBinContent(i-1) > h->GetBinContent(i)) ){
TGraph *gNew = new TGraph(g->GetN()+1);
gNew->SetPoint(0, h->GetBinCenter(i-2), h->GetBinContent(i-2));
Double_t pointx, pointy;
for ( int i=0; i<g->GetN(); i++ ){
g->GetPoint(i, pointx, pointy);
gNew->SetPoint(i+1, pointx, pointy);
}
delete g;
g = gNew;
}
// add a point to the end
if ( (h->GetBinContent(i+2) < h->GetBinContent(i+1) && h->GetBinContent(i+1) < h->GetBinContent(i))
|| (h->GetBinContent(i+2) > h->GetBinContent(i+1) && h->GetBinContent(i+1) > h->GetBinContent(i)) ){
g->Set(g->GetN()+1);
g->SetPoint(g->GetN()-1, h->GetBinCenter(i+2), h->GetBinContent(i+2));
}
}
// debug: show fitted 1-CL histogram
// if ( y<0.1 )
// // if ( methodName == TString("Plugin") && y<0.1 )
// {
// // TString debugTitle = methodName + Form(" y=%.2f ",y);
// // debugTitle += upper?Form("%f upper",central):Form("%f lower",central);
// TString debugTitle = "honk";
// TCanvas *c = newNoWarnTCanvas(getUniqueRootName(), debugTitle);
// g->SetMarkerStyle(3);
// g->SetHistogram(const_cast<TH1F*>(h));
// const_cast<TH1F*>(h)->Draw();
// g->DrawClone("p");
// }
// fit
TF1 *f1 = new TF1("f1", "pol2", h->GetBinCenter(i-2), h->GetBinCenter(i+2));
g->Fit("f1", "q"); // fit linear to get decent start parameters
g->Fit("f1", "qf+"); // refit with minuit to get more correct errors (TGraph fit errors bug)
float p[3], e[3];
for ( int ii=0; ii<3; ii++ ){
p[ii] = f1->GetParameter(ii);
e[ii] = f1->GetParError(ii);
}
// get solution by solving the pol2 for x
float sol0 = pq(p[0], p[1], p[2], y, 0);
float sol1 = pq(p[0], p[1], p[2], y, 1);
// decide which of both solutions to use based on the position of
// the central value
// \todo we probably don't need the central value to decide which solution
// to use. Just take the one closest to the original bin! Can't think of a
// situation where this should fail. So we don't need the central value in
// this method at all, to be removed.
int useSol = 0;
//if ( (sol0<central && sol1>central) || (sol1<central && sol0>central) ){
//if ( upper ){
//if ( sol0<sol1 ) useSol = 1;
//else useSol = 0;
//}
//else{
//if ( sol0<sol1 ) useSol = 0;
//else useSol = 1;
//}
//}
//else{
if ( fabs(h->GetBinCenter(i)-sol0) < fabs(h->GetBinCenter(i)-sol1) ) useSol = 0;
else useSol = 1;
//}
if ( useSol==0 ) val = sol0;
else val = sol1;
// try error propagation: sth is wrong in the formulae
// float err0 = TMath::Max(sq(val-pq(p[0]+e[0], p[1], p[2], y, useSol)), sq(val-pq(p[0]-e[0], p[1], p[2], y, useSol)));
// float err1 = TMath::Max(sq(val-pq(p[0], p[1]+e[1], p[2], y, useSol)), sq(val-pq(p[0], p[1]-e[1], p[2], y, useSol)));
// float err2 = TMath::Max(sq(val-pq(p[0], p[1], p[2]+e[2], y, useSol)), sq(val-pq(p[0], p[1], p[2]-e[2], y, useSol)));
// err = sqrt(err0+err1+err2);
// printf("%f %f %f\n", val, pq(p[0]+e[0], p[1], p[2], y, useSol), pq(p[0]-e[0], p[1], p[2], y, useSol));
// printf("%f %f %f\n", val, pq(p[0], p[1]+e[1], p[2], y, useSol), pq(p[0], p[1]-e[1], p[2], y, useSol));
// printf("%f %f %f\n", val, pq(p[0], p[1], p[2]+e[2], y, useSol), pq(p[0], p[1], p[2]-e[2], y, useSol));
err = 0.0;
delete g;
return true;
}
//____________________________________________________________________________________
// Plot blue band (SM Higgs curve)
void blueBand( )
{
double zerror = 4;
double xmin = 76;
int npoints = 31;
double x[] = { 10.000000, 11.392849, 12.979700, 14.787576, 16.847262, 19.193831, 21.867241,
24.913018, 28.383024, 32.336350, 36.840315, 41.971614, 47.817625, 54.477897,
62.065844, 70.710678, 76, 80.559606, 91.780341, 104.563955, 119.128133, 135.720881,
154.624747, 176.161637, 200.698289, 228.652526, 260.500365, 296.784127,
338.121669, 385.216905, 438.871795, 500.000000 };
double y[] = { 20.929260, 18.757168, 16.647426, 14.611732, 12.661571, 10.808107, 9.062193,
7.434501, 5.935701, 4.576664, 3.368675, 2.323612, 1.454084, 0.776111,
0.300018, 0.042673, 0.0001, 0.020469, 0.251087, 0.750519, 1.538231, 2.633789,
4.056692, 5.826546, 7.962673, 10.483595, 13.406320, 16.745357, 20.511276,
24.717583, 29.345917, 34.380810 };
TGraph* smGraph = new TGraph( npoints, x, y );
if ( npoints > MAXPOINTS ) {
std::cerr << "FATAL: npoints = " << npoints << " is greater than MAXPOINTS" << std::endl;
exit(-1);
}
double x1[2*MAXPOINTS], y1[2*MAXPOINTS];
double x2[MAXPOINTS], y2[MAXPOINTS];
// Find mH at minimum
int i1=0; // iterator for upper curve
int i2=0; // iterator for lower curve
double x0,y0;
double step = 5;
smGraph->GetPoint( 0, x0, y0 );
for ( int i=0; i<100; ++i )
{
double ix = x0+i*step;
double iy = smGraph->Eval( ix, 0, "S" );
double error = TMath::Log( ix/12. )*3.;
if ( ix<=xmin-error ) {
x1[i1] = ix+error; y1[i1]=iy; ++i1;
x2[i2] = ix-error; y2[i2]=iy; ++i2;
}
else if ( ix>=xmin+error) {
x1[i1] = ix-error; y1[i1]=iy; ++i1;
x2[i2] = ix+error; y2[i2]=iy; ++i2;
} else {//if ( iy>0. ) {
x2[i2] = (ix<=xmin)?ix-error:ix+error;
y2[i2]=iy;
++i2;
}
}
// Merge arrays
for ( int i=0; i<i2; ++i ) {
x1[i+i1] = x2[i2-i-1];
y1[i+i1] = y2[i2-i-1];
}
if ( doBands ) {
TGraph* blueBand = new TGraph( i1+i2, x1, y1 );
blueBand->SetFillColor(7);
blueBand->SetLineColor(7);
blueBand->Draw("LF");
blueBand->Draw("C");
} else {
smGraph->SetLineWidth(5);
}
smGraph->SetLineColor(4);
smGraph->Draw("C");
double chi2limit = smGraph->Eval( LEPLIMIT, 0, "S" );
std::cout << "Value at limit (" << LEPLIMIT << "): " << chi2limit << std::endl;
TGraph* lowband = new TGraph( i2, x2, y2 );
std::cout << "Value of (low) blueband at limit: " << lowband->Eval( LEPLIMIT, 0, "S" )
<< std::endl;
}
int main( int argc, char* argv[] ) {
if( argc!=3 && argc!=4 ) {
std::cout << "USAGE: ./draw_golfcourse [(string)data_dataset] [data_mc] [nbtags=\"ALL\"]" << std::endl;
exit(23);
}
std::string data_dataset(argv[1]);
std::string data_mc(argv[2]);
int nbtags=-1;
if( argc==4 ) {
nbtags = atoi(argv[3]);
}
TString data_dataset_tstr(data_dataset);
std::string PUType = "Run2011A";
float lumi = 2100.;
if( data_dataset=="HR11" ) {
PUType = "HR11";
lumi = 4200.;
} else if( data_dataset=="HR11_v2" ) {
PUType = "HR11_73pb";
lumi = 4600.;
} if( data_dataset_tstr.BeginsWith("Run2011B") ) {
PUType = "Run2011B";
}
DrawBase* db = new DrawBase("Golfcourse");
db->set_lumiNormalization(lumi);
std::string dataFileName = "HZZlljjRM_DATA_" + data_dataset + "_optLD_looseBTags_v2_ALL.root";
TFile* file_data = TFile::Open(dataFileName.c_str());
db->add_dataFile( file_data, "data" );
//db->set_isCMSArticle(true);
TGraph* graphObserved = get_observedLimit( data_dataset, data_mc, nbtags );
graphObserved->SetMarkerStyle(21);
graphObserved->SetMarkerSize(.85);
graphObserved->SetLineWidth(3.);
//graphObserved->SetMarkerColor(kGreen+4);
//graphObserved->SetMarkerSize(1.);
std::pair<TGraphAsymmErrors*,TGraphAsymmErrors*> graphs_expected = get_expectedLimit( data_dataset, data_mc, nbtags );
TGraphAsymmErrors* graphExpected68 = graphs_expected.first;
TGraphAsymmErrors* graphExpected95 = graphs_expected.second;
TGraphAsymmErrors* graphExpected68_forLegend = new TGraphAsymmErrors(*graphExpected68);
graphExpected68_forLegend->SetFillColor(kGreen);
graphExpected68->SetFillColor(kGreen);
graphExpected68->SetLineColor(kBlack);
graphExpected68->SetLineStyle(2);
graphExpected68->SetLineWidth(2);
graphExpected68->SetFillStyle(1001);//solid
graphExpected95->SetFillColor(kYellow);
graphExpected95->SetFillStyle(1001);//solid
float xmin = 180.;
float xmax = 620.;
float yMax = 8.;
if( data_dataset=="Run2011A_FULL" ) yMax = 10.;
if( nbtags!=-1 ) yMax=12.;
TH2D* axes = new TH2D("axes", "", 10, xmin, xmax, 10, 0., yMax );
axes->SetXTitle("m_{H} [GeV]");
axes->SetYTitle("#sigma_{95%} / #sigma_{SM}");
//TPaveText* labelCMS = get_labelCMS(db);
TPaveText* labelCMS = db->get_labelCMS();
TPaveText* labelSqrt = db->get_labelSqrt();
TLine* line_one = new TLine( xmin, 1., xmax, 1.);
line_one->SetLineColor(kRed);
line_one->SetLineWidth(2);
char legendTitle[200];
sprintf( legendTitle, "%d b-tag Category", nbtags );
TLegend* legend;
if( nbtags!=-1 )
legend = new TLegend( 0.35, 0.6, 0.85, 0.90, legendTitle );
else
legend = new TLegend( 0.35, 0.6, 0.85, 0.90);
legend->SetFillColor(10);
legend->SetFillStyle(1001);
legend->SetBorderSize(1);
legend->SetTextSize(0.034);
legend->SetTextFont(42);
legend->AddEntry( graphExpected68, "Bayesian Expected", "L" );
legend->AddEntry( graphExpected68_forLegend, "Expected #pm 1#sigma", "F" );
legend->AddEntry( graphExpected95, "Expected #pm 2#sigma", "F" );
legend->AddEntry( line_one, "SM", "L" );
TCanvas* c1 = new TCanvas("c1", "", 630, 600);
c1->SetGrid(true);
c1->cd();
axes->Draw("AXIS");
labelCMS->Draw("same");
labelSqrt->Draw("same");
graphExpected95->Draw("3same");
graphExpected68->Draw("3same");
graphExpected68->Draw("LXsame");
gPad->RedrawAxis();
line_one->Draw("same");
legend->Draw("same");
char canvasName[500];
if( nbtags>=0 )
sprintf( canvasName, "datacards_%s_fit%s/upperLimitExpected_%s_%dbtag.eps", data_dataset.c_str(), data_mc.c_str(), data_dataset.c_str(), nbtags );
else
sprintf( canvasName, "datacards_%s_fit%s/upperLimitExpected_%s.eps", data_dataset.c_str(), data_mc.c_str(), data_dataset.c_str() );
c1->SaveAs(canvasName);
c1->Clear();
// now also observed:
TLegend* legend2;
if( nbtags!=-1 )
legend2 = new TLegend( 0.35, 0.6, 0.85, 0.90, legendTitle );
else
legend2 = new TLegend( 0.35, 0.6, 0.85, 0.90);
legend2->SetFillColor(10);
legend2->SetFillStyle(1001);
legend2->SetBorderSize(1);
legend2->SetTextSize(0.034);
legend2->SetTextFont(42);
legend2->AddEntry( graphObserved, "Bayesian Observed", "LP" );
legend2->AddEntry( graphExpected68, "Bayesian Expected", "L" );
legend2->AddEntry( graphExpected68_forLegend, "Expected #pm 1#sigma", "F" );
legend2->AddEntry( graphExpected95, "Expected #pm 2#sigma", "F" );
legend2->AddEntry( line_one, "SM", "L" );
axes->Draw();
labelCMS->Draw("same");
labelSqrt->Draw("same");
graphExpected95->Draw("3same");
graphExpected68->Draw("3same");
graphExpected68->Draw("LXsame");
gPad->RedrawAxis();
line_one->Draw("same");
graphObserved->Draw("PLsame");
legend2->Draw("same");
if( nbtags>=0 )
sprintf( canvasName, "datacards_%s_fit%s/upperLimit_%s_%dbtag.eps", data_dataset.c_str(), data_mc.c_str(), data_dataset.c_str(), nbtags );
else
sprintf( canvasName, "datacards_%s_fit%s/upperLimit_%s.eps", data_dataset.c_str(), data_mc.c_str(), data_dataset.c_str() );
c1->SaveAs(canvasName);
char expectedLimitFileName[300];
if( nbtags>=0 )
sprintf( expectedLimitFileName, "datacards_%s_fit%s/expectedLimit_%s_%dbtag.txt", data_dataset.c_str(), data_mc.c_str(), data_dataset.c_str(), nbtags );
else
sprintf( expectedLimitFileName, "datacards_%s_fit%s/expectedLimit_%s.txt", data_dataset.c_str(), data_mc.c_str(), data_dataset.c_str() );
ofstream ofs_expected(expectedLimitFileName);
ofs_expected << "mH\tmedian\tlow95\tlow68\tup68\tup95" << std::endl;
for( unsigned imass=0; imass<graphExpected95->GetN(); ++imass ) {
Double_t mass, expectedUL;
graphExpected95->GetPoint( imass, mass, expectedUL );
float up95 = graphExpected95->GetErrorYhigh( imass );
float up68 = graphExpected68->GetErrorYhigh( imass );
float low95 = graphExpected95->GetErrorYlow( imass );
float low68 = graphExpected68->GetErrorYlow( imass );
ofs_expected << mass << "\t" << expectedUL << "\t" << low95 << "\t" << low68 << "\t" << up68 << "\t" << up95 << std::endl;
}
ofs_expected.close();
char observedLimitFileName[300];
if( nbtags>=0 )
sprintf( observedLimitFileName, "datacards_%s_fit%s/observedLimit_%s_%dbtag.txt", data_dataset.c_str(), data_mc.c_str(), data_dataset.c_str(), nbtags );
else
sprintf( observedLimitFileName, "datacards_%s_fit%s/observedLimit_%s.txt", data_dataset.c_str(), data_mc.c_str(), data_dataset.c_str() );
ofstream ofs_observed(observedLimitFileName);
ofs_observed << "mH\tobservedLimit" << std::endl;
for( unsigned imass=0; imass<graphObserved->GetN(); ++imass ) {
Double_t mass, observedUL;
graphObserved->GetPoint( imass, mass, observedUL );
ofs_observed << mass << "\t" << observedUL << std::endl;
}
ofs_observed.close();
return 0;
}
