void makeTTree(){
// Declaring
Double_t num;
Double_t xNumBins, yNumBins;
// Setting up Canvas to put plot the 2D histogram (from Tamii) and the 2 Bracnh Tree (created by this program)
TCanvas *canvas = new TCanvas("canvas","Canvas");
canvas->Divide(2,1);
canvas->cd(1);
// Opening up histogram file from tamii's analyzer
// Remember to do h2root before this program runs.
TFile *f1 = new TFile("run6106_test44.root");
TH2F *hist2D = (TH2F*)f1->Get("h159");
// Plotting the 2D histogram on the first part of the Canvas
hist2D->Draw("COLZ");
// Going through 2D hist and getting the total number of x and y bins.
xNumBins = hist2D->GetNbinsX();
yNumBins = hist2D->GetNbinsY();
// Creating a new file to save the 2 branch tree to.
TFile *t1 = new TFile("~/e329/root/13C/runs/run3014.root","recreate");
// This is the actual tree being created.
// !!! For you YingYing, instead of x vs theta, you would have theta(fp or target) vs Yfp !!!
TNtuple *DATA = new TNtuple("DATA","Xpos vs Theta","Xpos:Theta");
// This is the main nested for loop that goes through each bin in the 2D hist
// takes the number of counts in that (x,y)bin and creates that many events
// in the 2 branch tree
for (int binx = 0; binx < xNumBins+2; binx++){
for (int biny = 0; biny < yNumBins+2; biny++){
//getting the number of events in a particular (x,y)bin
num = hist2D->GetBinContent(binx,biny);
double x = hist2D->GetXaxis()->GetBinCenter(binx);
double y = hist2D->GetYaxis()->GetBinCenter(biny);
//cout << num << " at x= " << x << ", y= " << y << endl;
//Filling the Tree 'num' times with xbin and ybin events
for (int i = 0; i < num; i++){
DATA->Fill(x,y);
}
}
}
//Saving the Tree that was just created and filled
t1->Write();
//Ploting the Tree in the second part of the canvas.
canvas->cd(2);
DATA->Draw("Theta:Xpos>>(2000,-600,600,1000,-3,3)","","COLZ");
}
void parallelcoord() {
TNtuple *nt = NULL;
Double_t s1x, s1y, s1z;
Double_t s2x, s2y, s2z;
Double_t s3x, s3y, s3z;
r = new TRandom();;
new TCanvas("c1", "c1",0,0,800,700);
gStyle->SetPalette(1);
nt = new TNtuple("nt","Demo ntuple","x:y:z:u:v:w");
for (Int_t i=0; i<20000; i++) {
r->Sphere(s1x, s1y, s1z, 0.1);
r->Sphere(s2x, s2y, s2z, 0.2);
r->Sphere(s3x, s3y, s3z, 0.05);
generate_random(i);
nt->Fill(r1, r2, r3, r4, r5, r6);
generate_random(i);
nt->Fill(s1x, s1y, s1z, s2x, s2y, s2z);
generate_random(i);
nt->Fill(r1, r2, r3, r4, r5, r6);
generate_random(i);
nt->Fill(s2x-1, s2y-1, s2z, s1x+.5, s1y+.5, s1z+.5);
generate_random(i);
nt->Fill(r1, r2, r3, r4, r5, r6);
generate_random(i);
nt->Fill(s1x+1, s1y+1, s1z+1, s3x-2, s3y-2, s3z-2);
generate_random(i);
nt->Fill(r1, r2, r3, r4, r5, r6);
}
nt->Draw("x:y:z:u:v:w","","para",5000);
TParallelCoord* para = (TParallelCoord*)gPad->GetListOfPrimitives()->FindObject("ParaCoord");
para->SetDotsSpacing(5);
TParallelCoordVar* firstaxis = (TParallelCoordVar*)para->GetVarList()->FindObject("x");
firstaxis->AddRange(new TParallelCoordRange(firstaxis,0.846018,1.158469));
para->AddSelection("violet");
para->GetCurrentSelection()->SetLineColor(kViolet);
firstaxis->AddRange(new TParallelCoordRange(firstaxis,-0.169447,0.169042));
para->AddSelection("Orange");
para->GetCurrentSelection()->SetLineColor(kOrange+9);
firstaxis->AddRange(new TParallelCoordRange(firstaxis,-1.263024,-0.755292));
}
void Example2(){
gROOT->Reset();
gROOT->Clear();
gROOT->SetStyle("Plain");
gStyle->SetTextSize(0.01908148);
gStyle->SetTitleFontSize(0.07);
gStyle->SetOptTitle(1);
gStyle->SetOptStat(1110);
gStyle->SetOptFit(1111);
gStyle->SetTitleXOffset(1.1);
gStyle->SetTitleYOffset(1.55);
gStyle->SetPadTopMargin(0.15);
gStyle->SetPadBottomMargin(0.15);
gStyle->SetPadLeftMargin(0.15);
// select the one of the versus : Hf energy, Centrality, # Charged , # Tracks
int Vselect = 1;
// number of Trigger you will use ,
const int Ntr = 2;
//if you want to use more than two trigger please specify the Ntr2 for dividivg the canvas
const int Ntr2 = 1;
TFile* inf = new TFile("openhlt2.root");
string triggers[6] = {"L1Tech_BSC_minBias_threshold1.v0","L1Tech_BSC_minBias_threshold2.v0","L1_SingleJet30","L1_TripleJet30","L1_QuadJet15","L1_DoubleJet70"};
string vers[4] = {"hiHF","hiBin","Ncharged","hiNtracks"};
double bins [4] = {170,40,240,140};
double limits[4] = {170000,40,24000,1400};
TCanvas* c1 = new TCanvas("c1","c1",800,400);
c1->Divide(Ntr,Ntr2);
TNtuple* nt = (TNtuple*)inf->Get("HltTree");
TProfile* p1[Ntr];
for(unsigned int i =0; i<Ntr ; i++){
c1->cd(i+1);
p1[i] = new TProfile("p1",Form(";%s;%s",vers[Vselect].data(),triggers[i].data()),bins[1],0,limits[1]);
nt->SetAlias("trigger",triggers[i].data());
nt->SetAlias("versus",vers[Vselect].data());
nt->Draw("trigger:versus>>p1","","prof");
}
c1->Print(Form("%s_vsCent.gif",triggers[Vselect].data()));
}
double getUncertaintyValue(double m0,double m12, int channel, string valuename, TFile * input)
{
bool DEBUGuncertaintyValue=false;
/*
string buffer = doubletostr(m0)+doubletostr(m12)+inttostr(channel)+valuename;
map <std::string, double>::iterator iter;
iter=UncertaintyValueBuffer.find(buffer);
if (bufferValue && iter!=UncertaintyValueBuffer.end()) return iter->second;
*/
double returnvalue2 ;
double min=-10;
double max=+10;
//cout << "v" ;
string leaveName="";
if (valuename=="K") leaveName="K";
if (valuename=="crossSection") {leaveName="crossSection"; min=0; max=100000;};
if (valuename=="PDFUncertainty") leaveName="relUncPDF";
if (valuename=="ScaleUncertainty2Q") leaveName="relScaleUnc2Q";
if (valuename=="ScaleUncertainty12Q") leaveName="relScaleUncHalfQ";
if (leaveName=="") throw "no leave found for that value";
string commandstring=leaveName+">>h1";
string conditionstring= "finalState>" + doubletostr(channel-0.1) +"&& finalState<"+ doubletostr(channel+0.1) +"&& m0>" + doubletostr(m0-0.5) + " && m0<"+doubletostr(m0+0.5) +" && m12>" + doubletostr(m12-0.5) + " && m12<"+doubletostr(m12+0.5);
if (DEBUGuncertaintyValue){
cout << " commandstring " << commandstring << endl;
cout << " conditionstring " << conditionstring << endl;
cout << " leaveName " << leaveName << endl;
cout << " valuename :" << valuename << " channel: " << channel << " m0: " << m0 << " m12: " << m12 << endl;
}
TNtuple *ntuple = (TNtuple*)file_robin->Get("SignalUncertainties");
if (ntuple==0) throw "Ntuple not found";
if (DEBUGuncertaintyValue) cout << "(min,max) "<<min << " "<<max<<endl;
TH1F * h1 = new TH1F("h1","h1",100000,min,max);
ntuple->Draw(commandstring.c_str(),conditionstring.c_str());
if (DEBUGuncertaintyValue) cout << "mean " << h1->GetMean()<<endl;
returnvalue2 = fabs (h1->GetMean());
// UncertaintyValueBuffer[buffer]=returnvalue2;
delete h1;
return returnvalue2;
}
void rootFit(){
TCanvas *c1 = new TCanvas("c1","",600,600);
c1->Divide(1,2);
TNtuple *T = new TNtuple("T","","x:y:z");
T->ReadFile("histogramData.dat");
T->Draw("y:x");
Double_t *X = T->GetV1();
Double_t *Y = T->GetV2();
for(int loop = 0; loop < 120; loop++){
cout << X[loop] << " " << Y[loop] << endl;
}
c1->Clear();
TGraph *graphT = new TGraph(120,Y,X);
TGraph *graphB = new TGraph(120,Y,X);
c1->cd(1);
graphT->Draw("APL");
graphT->Fit("gaus+pol2","RME");
}
void unfoldPt(int mode=0)
{
// Matched Tracklets
TFile *inf = new TFile("match-10TeV-12.root");
TNtuple *nt = (TNtuple*)inf->FindObjectAny("nt");
// Test sample
TFile *infTest = new TFile("./TrackletTree-Run123596.root");
TNtuple *ntTest = (TNtuple*)infTest->FindObjectAny("TrackletTree12");
TFile *pdfFile;
if (mode==0) pdfFile = new TFile("pdf.root","recreate");
else pdfFile = new TFile("pdf.root");
double nPtBin=15;
double minPt=log(0.05);
double maxPt=log(10);
double nDphiBin=600;
double maxDphi=0.4;
char* mycut = Form("abs(eta)<2&&log(pt)>%f&&log(pt)<%f",minPt,maxPt);
char* mycut1=Form("abs(eta)<2&&log(pt)>%f&&log(pt)<%f&&abs(eta-eta1)<0.01&&abs(deta)<0.01",minPt,maxPt);
TH2F *h;
TH1F *hdphi = new TH1F("hdphi","",nDphiBin,0,maxDphi);
TH1F *hdphi2;
TH1F *hpt;
TH1F *hptH = new TH1F("hptH","",nPtBin,minPt,maxPt);
TH1F *hptUnfold = new TH1F("hptUnfold","",nPtBin,minPt,maxPt);
TH1F *hptMC = new TH1F("hptMC","",nPtBin,minPt,maxPt);
TH1F *hptTemp = new TH1F("hptTemp","",nPtBin,minPt,maxPt);
// Delta phi as a function of matched genparticle transverse momentum
TCanvas *c = new TCanvas("c","",600,600);
if (mode == 0) {
h = new TH2F("h","",nPtBin,minPt,maxPt,nDphiBin,0,maxDphi);
hdphi2 = new TH1F("hdphiMC","",nDphiBin,0,maxDphi);
hpt = new TH1F("hpt","",nPtBin,minPt,maxPt);
h->SetXTitle("ln(P_{T}) GeV/c");
h->SetYTitle("|#Delta#phi|");
nt->Draw("abs(dphi):log(pt)>>h",mycut1,"col");
// used to generate pdf
nt->Draw("abs(dphi)>>hdphiMC",mycut,"");
nt->Draw("log(pt)>>hpt",mycut,"");
h->Write();
hpt->Write();
hdphi2->Write();
} else {
h = (TH2F*) pdfFile->FindObjectAny("h");
hdphi2 = (TH1F*) pdfFile->FindObjectAny("hdphiMC");
hpt = (TH1F*) pdfFile->FindObjectAny("hpt");
}
// Delta phi fit
TCanvas *c2 = new TCanvas("c2","",600,600);
c2->SetLogy();
c2->SetLogx();
// dphi for unfolding and MC truth:
ntTest->Draw("abs(dphi)>>hdphi","abs(eta1)<2&&abs(deta)<0.1","",200000);
ntTest->Draw("log(pt)>>hptH",mycut,"",200000);
histFunction2D *myfun = new histFunction2D(h);
TF1 *test = new TF1("histFun",myfun,&histFunction2D::evaluate,0,maxDphi,nPtBin+1);
TF1 *test2 = new TF1("histFunMC",myfun,&histFunction2D::evaluate,0,maxDphi,nPtBin+1);
for (int i=0;i<nPtBin+1;i++)
{
test->SetParameter(i,1);
}
hdphi2->SetXTitle("|#Delta#phi|");
hdphi2->SetYTitle("Arbitrary Normalization");
hdphi2->Fit("histFunMC","M");
hdphi->SetXTitle("|#Delta#phi|");
hdphi->SetYTitle("Arbitrary Normalization");
hdphi->Fit("histFun","M");
hdphi->SetStats(0);
hdphi->Draw();
for (int i=0;i<nPtBin+1;i++) {
TF1 *testPlot = new TF1(Form("histFun%d",i),myfun,&histFunction2D::evaluate,0,maxDphi,nPtBin+1);
testPlot->SetParameter(i,test->GetParameter(i));
testPlot->SetLineColor(i+2);
testPlot->Draw("same");
}
int total=0,totalMC=0;
for (int i=0;i<nPtBin;i++){
if (test->GetParameter(i)==0) continue;
hptUnfold->SetBinContent(i+1,fabs(test->GetParameter(i)));
hptUnfold->SetBinError(i+1,test->GetParError(i));
hptMC->SetBinContent(i+1,fabs(test2->GetParameter(i)));
hptMC->SetBinError(i+1,test2->GetParError(i));
total+=fabs(test->GetParameter(i));
totalMC+=fabs(test2->GetParameter(i));
}
hptUnfold->SetEntries(total);
hptMC->SetEntries(totalMC);
TCanvas *c3 = new TCanvas("c3","",600,600);
hpt->Sumw2();
hptH->Sumw2();
//hptMC->Sumw2();
double normMC=0;
double norm=0;
double normTruth=0;
hptUnfold->SetMarkerColor(2);
hptUnfold->SetMarkerStyle(4);
// hptUnfold->Scale(1./hptUnfold->GetEntries());
TH1F *hptCorrected = (TH1F*)hptUnfold->Clone();
hptCorrected->SetName("hptCorrected");
hptMC->Divide(hpt);
hptCorrected->Divide(hptMC);
for (int i=0;i<nPtBin;i++){
if (hptMC->GetBinContent(i)<=0.001)hptCorrected->SetBinContent(i,0);
}
hptCorrected->Scale(1./(hptCorrected->GetSum()));
hptCorrected->SetMarkerStyle(20);
hpt->Scale(1./hpt->GetEntries());
if (hptH->GetEntries())hptH->Scale(1./hptH->GetEntries());
hptTemp->SetXTitle("ln(P_{T}) GeV/c");
hptTemp->SetYTitle("Arbitrary Normalization");
hptTemp->Draw();
hptH->SetXTitle("ln(P_{T}) GeV/c");
hptH->SetYTitle("Arbitrary Normalization");
hptH->Draw("hist");
hptH->SetLineColor(4);
hpt->Draw("hist same ");
hptCorrected->Draw("same");
TH1F *hptUnfoldRatio = (TH1F*)hptUnfold->Clone();
hptUnfoldRatio->SetName("hptUnfoldRatio");
hptUnfoldRatio->Scale(1./hptUnfoldRatio->GetSum());
//hptUnfoldRatio->Divide(hptH);
TH1F *hptCorrectedRatio = (TH1F*)hptCorrected->Clone();
hptCorrectedRatio->SetName("hptCorrectedRatio");
hptCorrectedRatio->SetMarkerColor(2);
//hptCorrectedRatio->Divide(hptH);
TCanvas *c4 = new TCanvas("c4","",600,600);
TLine *l = new TLine(-2.5,1,2.5,1);
hptUnfoldRatio->Draw();
hptMC->Draw("same");
hptCorrectedRatio->Draw("same");
l->Draw("same");
}
void canvas_write()
{
//just in case this script is executed multiple times
delete gROOT->GetListOfFiles()->FindObject("hsimple.root");
delete gROOT->GetListOfCanvases()->FindObject("c1");
gBenchmark->Start("ntuple1");
//
// Connect ROOT histogram/ntuple demonstration file
// generated by example hsimple.C.
TFile *f1 = new TFile("hsimple.root");
//
// Create a canvas, with 4 pads
//
TCanvas *c1 = new TCanvas("c1","The Ntuple canvas",200,10,700,780);
TPad *pad1 = new TPad("pad1","This is pad1",0.02,0.52,0.48,0.98,21);
TPad *pad2 = new TPad("pad2","This is pad2",0.52,0.52,0.98,0.98,21);
TPad *pad3 = new TPad("pad3","This is pad3",0.02,0.02,0.48,0.48,21);
TPad *pad4 = new TPad("pad4","This is pad4",0.52,0.02,0.98,0.48,1);
pad1->Draw();
pad2->Draw();
pad3->Draw();
pad4->Draw();
//
// Change default style for the statistics box
gStyle->SetStatW(0.30);
gStyle->SetStatH(0.20);
gStyle->SetStatColor(42);
//
// Display a function of one ntuple column imposing a condition
// on another column.
pad1->cd();
pad1->SetGrid();
pad1->SetLogy();
pad1->GetFrame()->SetFillColor(15);
TNtuple *ntuple = (TNtuple*)f1->Get("ntuple");
ntuple->SetLineColor(1);
ntuple->SetFillStyle(1001);
ntuple->SetFillColor(45);
ntuple->Draw("3*px+2","px**2+py**2>1");
ntuple->SetFillColor(38);
ntuple->Draw("2*px+2","pz>2","same");
ntuple->SetFillColor(5);
ntuple->Draw("1.3*px+2","(px^2+py^2>4) && py>0","same");
pad1->RedrawAxis();
//
// Display the profile of two columns
// The profile histogram produced is saved in the current directory with
// the name hprofs
pad2->cd();
pad2->SetGrid();
pad2->GetFrame()->SetFillColor(32);
ntuple->Draw("pz:px>>hprofs","","goffprofs");
TProfile *hprofs = (TProfile*)gDirectory->Get("hprofs");
hprofs->SetMarkerColor(5);
hprofs->SetMarkerSize(0.7);
hprofs->SetMarkerStyle(21);
hprofs->Fit("pol2");
// Get pointer to fitted function and modify its attributes
TF1 *fpol2 = hprofs->GetFunction("pol2");
fpol2->SetLineWidth(4);
fpol2->SetLineColor(2);
//
// Display a scatter plot of two columns with a selection.
// Superimpose the result of another cut with a different marker color
pad3->cd();
pad3->GetFrame()->SetFillColor(38);
pad3->GetFrame()->SetBorderSize(8);
ntuple->SetMarkerColor(1);
ntuple->Draw("py:px","pz>1");
ntuple->SetMarkerColor(2);
ntuple->Draw("py:px","pz<1","same");
//
// Display a 3-D scatter plot of 3 columns. Superimpose a different selection.
pad4->cd();
ntuple->Draw("pz:py:px","(pz<10 && pz>6)+(pz<4 && pz>3)");
ntuple->SetMarkerColor(4);
ntuple->Draw("pz:py:px","pz<6 && pz>4","same");
ntuple->SetMarkerColor(5);
ntuple->Draw("pz:py:px","pz<4 && pz>3","same");
TPaveText *l4 = new TPaveText(-0.9,0.5,0.9,0.95);
l4->SetFillColor(42);
l4->SetTextAlign(12);
l4->AddText("You can interactively rotate this view in 2 ways:");
l4->AddText(" - With the RotateCube in clicking in this pad");
l4->AddText(" - Selecting View with x3d in the View menu");
l4->Draw();
//
c1->cd();
c1->Update();
gStyle->SetStatColor(19);
gBenchmark->Show("ntuple1");
TSQLFile* fsql1 = new TSQLFile(dbname, "recreate", username, userpass);
if (fsql1->IsZombie()) { delete fsql1; return; }
// changing TSQLFile configuration, you may improve speed
// of reading or writing object to/from sql database
// fsql1->SetUseSuffixes(kFALSE);
// fsql1->SetArrayLimit(1000);
// fsql1->SetUseIndexes(1);
// fsql1->SetTablesType("ISAM");
// fsql1->SetUseTransactions(kFALSE);
// Unncomment this line to see all SQL commands in log file
// fsql1->StartLogFile("canvas.log");
gBenchmark->Start("writeSQL");
c1->Write("Canvas");
gBenchmark->Show("writeSQL");
delete fsql1;
}
void TestEnergy() {
TFile *file = TFile::Open("PPCollisionUps1sMilNoTune.root");
TFile *file2 = TFile::Open("PPCollisionMilNoTune.root");
TNtuple* PPTupleUps = (TNtuple*)file->Get("PPTuple");
TNtuple* PPTupleND = (TNtuple*)file2->Get("PPTuple");
TH1D* NCharUps = new TH1D("NCharUps", "Sum of Energy at mid rapdity", 30000, 0, 300);
PPTupleUps->Draw("(ETmid-mu1pT-mu2pT)>>NCharUps", "NChar>2 && abs(deta1) < 1.93 && abs(deta2) < 1.93 && mu1pT > 4 && mu2pT > 4");
// NCharUps->Scale(3.35e-6);
double sum, percent = 0, centAr[21];
int c, centa[21], i;
sum = 0;
centAr[0] = 180;
centAr[20] = 0;
c = 1;
//Find Activity Ranges
double min = 0, average[20], bins;
i = 0;
//Activity Range Calculations for Track Count
TH1D* Tracks = new TH1D("Tracks", "Number of Tracks", 10000, 0, 300);
PPTupleND->Draw("ETmid>>Tracks", "NChar > 0");
double MinBiasEvents;
MinBiasEvents = Tracks->GetEntries();
NCharUps->Draw();
Tracks->Draw();
Tracks->Scale(1./Tracks->GetEntries());
int TrackCent[21];
percent = .02;
TrackCent[0] = 300;
TrackCent[20] = 0;
c = 1;
double Ranges[12];
int counter = 1;
Ranges[0] = 0;
//Loop To Get Activity Range Values
for (i=0; percent <= .02; percent += .02) {
sum = 0;
cout << c << " ";
for(i=0; sum < percent && i != 10000; i++) {
sum += Tracks->GetBinContent(10000-i); }
cout << 100*percent - 2 << "-" << 100*percent << "%" << " " << MinBiasEvents*sum << " " << i << " " << Tracks->GetBinCenter(10000-i) << "\n"; // Use to check Activity Range Values
Ranges[counter] = sum;
counter++;
TrackCent[c] = Tracks->GetBinCenter(10000-i);
c++;}
percent = .08;
for (i=0; percent <= .08; percent += .02) {
sum = 0;
cout << c << " ";
for(i=0; sum < percent || percent == 1; i++) {
sum += Tracks->GetBinContent(10000-i); }
cout << 100*percent - 2 << "-" << 100*percent << "%" << " " << MinBiasEvents*sum << " " << i << " " << Tracks->GetBinCenter(10000-i) << "\n"; // Use to check Activity Range Values
Ranges[counter] = sum;
counter++;
TrackCent[c] = Tracks->GetBinCenter(10000-i);
c++;}
percent = .20;
for (i=0; percent <= .20; percent += .04) {
sum = 0;
cout << c << " ";
for(i=0; sum < percent || percent == 1; i++) {
sum += Tracks->GetBinContent(10000-i); }
cout << 100*percent - 4 << "-" << 100*percent << "%" << " " << MinBiasEvents*sum << " " << i << " " << Tracks->GetBinCenter(10000-i) << "\n"; // Use to check Activity Range Values
Ranges[counter] = sum;
counter++;
TrackCent[c] = Tracks->GetBinCenter(10000-i);
c++;}
percent = .30;
// for (i=0; percent <= .30; percent += .05) {
// sum = 0;
// cout << c << "\n";
// for(i=0; sum < percent || percent == 1; i++) {
// sum += Tracks->GetBinContent(10000-i); }
// cout << 100*percent - 5 << "-" << 100*percent << "%" << " " << sum << " " << i << " " << Tracks->GetBinCenter(10000-i) << "\n"; // Use to check Activity Range Values
// TrackCent[c] = Tracks->GetBinCenter(10000-i) + .5;
// c++; }
// percent = .40;
for (i=0; percent <= 1; percent += .10) {
sum = 0;
cout << c << " ";
for(i=0; sum <= percent && i != 10000; i++) {
sum += Tracks->GetBinContent(10000-i); }
cout << 100*percent - 10 << "-" << 100*percent << "%" << " " << MinBiasEvents*sum << " " << i << " " << Tracks->GetBinCenter(10000-i) << "\n"; // Use to check Activity Range Values
Ranges[counter] = sum;
counter++;
TrackCent[c] = Tracks->GetBinCenter(10000-i);
c++; }
cout << "\n" << "Activity Range Values from Array" << "\n";
for(c = 0; c < 11; c++) {
cout << c << ") " << TrackCent[c] << "\n"; }
min = 0;
double TrackAverage[20];
cout << "\n" << NCharUps->GetBinCenter(30000) << "\n";
i = 0;
double TotalUps = 0;
//cout << "\n" << "Activity Bin Averages" << "\n";
//Loop To Get Average In Each Activity Region
for(c = 0; NCharUps->GetBinCenter(30000-i) > TrackCent[c+1] && NCharUps->GetBinCenter(30000-i) <= TrackCent[c]; c++) {
sum = 0;
bins = 0;
for(i = min; (NCharUps->GetBinCenter(30000-i) > TrackCent[c+1] && NCharUps->GetBinCenter(30000-i) <= TrackCent[c]) && i != 30000; i++) {
sum += NCharUps->GetBinContent(30000-i)*(NCharUps->GetBinCenter(30000-i));
bins += NCharUps->GetBinContent(30000-i); }
TrackAverage[c] = sum/bins;
TotalUps += bins;
cout << "Point " << c << ": " << bins << " +- " << sqrt(bins) << " Upsilons" << "\n";
min = i; }
cout << NCharUps->GetBinCenter(100) << "\n";
// cout << 10*c << "-" << 10*(c+1) << "%" << " " << TrackAverage[c] << "\n"; }
cout << "Total number of Upsilons: " << TotalUps << "\n";
cout << "\n" << "Corrected X/Y Track values" << "\n";
double TrackYpoints[20];
for(i = 0; i < 12; i++) {
cout << (Ranges[i+1] - Ranges[i])*MinBiasEvents << "\n"; }
//Take Average Values and Divide by ND Average to Get X points
// for(c = 0; c < 4; c++) {
// TrackAverage[c] = TrackAverage[c]/Tracks->GetMean();
// TrackYpoints[c] = (50./NCharUps->Integral(0,25000))*NCharUps->Integral(TrackCent[c+1], TrackCent[c]-1 );
// cout << "(" <<TrackAverage[c] << "," << TrackYpoints[c] << ")" << "\n"; }
//for(c = 4; c < 7; c++) {
// TrackAverage[c] = TrackAverage[c]/Tracks->GetMean();
// TrackYpoints[c] = (25./NCharUps->Integral(0,25000))*NCharUps->Integral(TrackCent[c+1], TrackCent[c]-1 );
// cout << "(" <<TrackAverage[c] << "," << TrackYpoints[c] << ")" << "\n"; }
// for(c = 7; c < 10; c++) {
// TrackAverage[c] = TrackAverage[c]/Tracks->GetMean();
// TrackYpoints[c] = (20./NCharUps->Integral(0,25000))*NCharUps->Integral(TrackCent[c+1], TrackCent[c]-1 );
// cout << "(" <<TrackAverage[c] << "," << TrackYpoints[c] << ")" << "\n"; }
TrackAverage[0] = TrackAverage[0]/Tracks->GetMean();
TrackYpoints[0] = (50./NCharUps->Integral(0,30000))*NCharUps->Integral(100*TrackCent[1], 100*(TrackCent[0]-1) );
cout << "(" <<TrackAverage[0] << "," << TrackYpoints[0] << ")" << "\n";
TrackAverage[1] = TrackAverage[1]/Tracks->GetMean();
TrackYpoints[1] = (16.67/NCharUps->Integral(0,30000))*NCharUps->Integral(100*TrackCent[2], 100*TrackCent[1]-100 );
cout << "(" <<TrackAverage[1] << "," << TrackYpoints[1] << ")" << "\n";
TrackAverage[2] = TrackAverage[2]/Tracks->GetMean();
TrackYpoints[2] = (8.33/NCharUps->Integral(0,30000))*NCharUps->Integral(100*TrackCent[3], 100*TrackCent[2]-100 );
cout << "(" <<TrackAverage[2] << "," << TrackYpoints[2] << ")" << "\n";
for(c = 3; c < 14; c++) {
TrackAverage[c] = TrackAverage[c]/Tracks->GetMean();
TrackYpoints[c] = (10./NCharUps->Integral(0,30000))*NCharUps->Integral(100*TrackCent[c+1], 100*TrackCent[c]-100 );
cout << "(" <<TrackAverage[c] << "," << TrackYpoints[c] << ")" << "\n"; }
TF1* line = new TF1("line", "x", 0, 4.5);
TF1* line2 = new TF1("line2", "1.8*x", 0, 4.5);
line2->SetLineColor(kWhite);
sum = 0;
double scaledSumE = 0, scaleSumT = 0;
scaleSumT = NCharUps->Integral(0,30000);
TCanvas* can2 = new TCanvas("can2", "Centrality");
can2->cd();
line->SetLineColor(1);
line2->GetYaxis()->SetTitle("#varUpsilon(1S)/<#varUpsilon(1S)>");
line2->GetXaxis()->SetTitle("#Sigma E_{T}^{|#eta| < 2.4}/<#Sigma E_{E}^{|#eta| < 2.4}>");
line2->SetTitle("#varUpsilon(1S) Cross Section vs Track Multiplicity");
line2->Draw();
line->SetLineStyle(3);
line->Draw("same");
for(c = 0; c < 18; c++) { cout << TrackCent[c] << " Bin Average: " << 10.32*TrackAverage[c] << "\n";}
double Test, Testaverage, Testsum, Testbin, count = 0, TestY = 0;
Test = NCharUps->Integral(38,100);
for(i = 38; i < 100; i++) {
Testsum += NCharUps->GetBinContent(i)*NCharUps->GetBinCenter(i);
Testbin += NCharUps->GetBinContent(i); }
Testaverage = Testsum/Testbin;
TestY = (10./NCharUps->Integral(0,30000))*NCharUps->Integral(38, 100);
cout << "\n" << "\n" << TestY << "\n" << "\n";
TH1D* modelT = new TH1D("modelT", "Pythia model", 5000, 0, 5);
//Fill Histogram with points from Model
for(i = 0; i < 20; i++) {
//Track Values
modelT->SetBinContent(1000*TrackAverage[i], TrackYpoints[i]);
modelT->SetBinError(1000*TrackAverage[i], .01); }
modelT->SetMarkerStyle(20);
modelT->SetMarkerColor(kBlue);
modelT->SetLineColor(kBlue);
modelT->Draw("sameE");
//Histogram for STAR Data Points
TH1D* data = new TH1D("data", "CMS Data", 4000, 0, 4);
data->SetMarkerStyle(20);
data->SetMarkerColor(kRed);
data->SetLineColor(kRed);
data->SetBinContent(3262, 6.67);
data->SetBinError(3262, .26);
data->SetBinContent(2010, 3.12);
data->SetBinError(2010, .15);
data->SetBinContent(1240, 1.4);
data->SetBinError(1240, .06);
data->SetBinContent(630, .240);
data->SetBinError(630, .01);
data->Draw("sameE");
TLegend* leg = new TLegend(.1,.74,.30,.9);
leg->SetHeader("For |#eta| < 2.4");
leg->AddEntry(modelT->DrawCopy("same"), "Pythia 8 Model", "l");
leg->AddEntry(data->DrawCopy("same"), "CMS data", "l");
leg->Draw("same");
return; }
int main( int argc, char* argv[] )
{
cout << endl;
cout << "\t8888888b. d8b 888 8888888b. 888 888 " << endl;
cout << "\t888 Y88b Y8P 888 888 Y88b 888 888 " << endl;
cout << "\t888 888 888 888 888 888 888 " << endl;
cout << "\t888 d88P 8888b. 88888b. 888 .d88888 888 d88P 888 .d88b. 888888 " << endl;
cout << "\t8888888P\" \"88b 888 \"88b 888 d88\" 888 8888888P\" 888 d88\"\"88b 888 " << endl;
cout << "\t888 T88b .d888888 888 888 888 888 888 888 888 888 888 888 " << endl;
cout << "\t888 T88b 888 888 888 d88P 888 Y88b 888 888 888 Y88..88P Y88b. " << endl;
cout << "\t888 T88b \"Y888888 88888P\" 888 \"Y88888 888 888 \"Y88P\" \"Y888 " << endl;
cout << "\t 888 " << endl;
cout << "\t 888 " << endl;
cout << "\t 888 " << endl;
cout << endl << endl;
cout << "Usage:" << endl;
cout << "\t" << argv[0] << "\tSomeFile.root\t" << "phys_param1\tphys_param2\toutput_directory" << endl;
cout << endl << "\teg:\t" << argv[0] << "\tLLcontourData.root\tdeltaGamma\tPhi_s\toutputdir"<<endl;
cout << endl;
cout << "6th (Optional) Option:"<<endl;
cout << "\t\t\tCV\t\t(Plot the CV of 'nuisence' Physics Parameters)"<<endl;
cout << "\t\t\tRelCV\t\t(Plot the variation in the CV of the 'nuisence' Physics Parameters)"<<endl;
cout << "\t\t\tExtraCV\t\t(Plot all of the CV, errors and pulls for each 'nuisence' Physics Parameter)"<<endl;
cout << "\t\t\tNOFC\t\t(Don't process FC data in a file if any is there)"<<endl;
cout << endl;
if( (argc != 5) && (argc != 6) ) exit(-1);
// Use UUID based seed from ROOT, just used for unique identification of ROOT objects
TRandom3* rand_gen = new TRandom3(0);
// Setup the Canvas and such
EdStyle* RapidFit_Style = new EdStyle();
RapidFit_Style->SetStyle();
// By Design
TString outputdir = argv[4];
TString param1string = argv[2];
TString param2string = argv[3];
// Make OutputDir
gSystem->mkdir( outputdir );
// Open the File
TFile * input = TFile::Open( argv[1] );
TNtuple* allresults;
input->GetObject("RapidFitResult", allresults);
if(!allresults){
input->GetObject("RapidFitResult/RapidFitResult",allresults);
if(!allresults){
cout << "Couldn't find ntuple RapidFitResult in TFile" << endl;
exit(1);
}
}
// Switches for different plotting
bool CV_Drift = false;
bool Want_Physics_Params=false;
bool Want_Extra_Physics_Param_Info=false;
bool want_FC = true;
bool high_res = true; // False method may only call plot fully once... still in development
if( argc == 6 )
{
if( string(argv[5]) == "CV" ) Want_Physics_Params = true;
if( string(argv[5]) == "RelCV" ) { Want_Physics_Params = true; CV_Drift = true; }
if( string(argv[5]) == "ExtraCV" ) { Want_Physics_Params = true; Want_Extra_Physics_Param_Info = true; }
if( string(argv[5]) == "NOFC" ) want_FC = false;
}
// Strings that are universally defined
TString Double_Tolerance="0.000001";
TString Fit_Status = "Fit_Status";
TString NLL = "NLL";
TString notgen = "-9999.";
TString error_suffix = "_error";
TString value_suffix = "_value";
TString pull_suffix = "_pull";
TString gen_suffix = "_gen";
TString Copy_Option = "fast";
// Strings that are relevent to this plot
// This is currently given by the user, but in time we can write an algorithm to determine this
TString param1_gen = param1string + gen_suffix;
TString param1_val = param1string + value_suffix;
TString param1_err = param1string + error_suffix;
TString param2_gen = param2string + gen_suffix;
TString param2_val = param2string + value_suffix;
TString param2_err = param2string + error_suffix;
// Get a list of ALL parameters within the file, this is given for free in the algorithms I wrote above
// Get a list of all branches in allresults
vector<TString> all_parameters = get_branch_names( allresults );
// Get a list of all branches in allresults with '_value' in their name
vector<TString> all_parameter_values = filter_names( all_parameters, value_suffix );
vector<TString> all_parameter_errors = filter_names( all_parameters, error_suffix );
vector<TString> all_parameter_pulls = filter_names( all_parameters, pull_suffix );
// Now to read in the Global Minima
// Store the Global fit corrdinate and value
Float_t nll=0, Global_Best_NLL=0, x_point=0, y_point=0;
// Store the value of the 'nuisence' parameters as well
Float_t* best_fit_values = new Float_t[all_parameter_values.size()];
// Construct an array to hold the best values for the rest of the parameters
Float_t* best_fit_temp_values = new Float_t[all_parameter_values.size()];
allresults->SetBranchAddress(NLL,&nll);
// Tell ROOT where to store the values
for( unsigned short int i=0; i < all_parameter_values.size(); ++i )
{
allresults->SetBranchAddress(all_parameter_values[i],&best_fit_temp_values[i]);
}
// Actually store the values in resident memory of the program
cout << endl << "BEST FIT RESULTS AS DETERMINED FROM THE STANDARD FIT:" << endl;
allresults->GetEntry(0);
Global_Best_NLL = nll;
for( unsigned short int i=0; i < all_parameter_values.size(); ++i )
{
cout << all_parameter_values[i] << ":\t" << best_fit_temp_values[i] << endl;
best_fit_values[i] = best_fit_temp_values[i];
if( string(all_parameter_values[i].Data()).compare(param1_val.Data()) == 0 ) x_point = best_fit_temp_values[i];
if( string(all_parameter_values[i].Data()).compare(param2_val.Data()) == 0 ) y_point = best_fit_temp_values[i];
}
cout << endl;
// General Cuts to be applied for various plots
// Fit_Status == 3
TString Fit_Cut = "(abs(" + Fit_Status + "-3.0)<"+Double_Tolerance+")";
// param1_gen == notgen && param1_err == 0
TString Param_1_Cut = "(abs(" + param1_gen + "-" + notgen +")<" + Double_Tolerance + ")&&(abs("+ param1_err + "-0.0)<"+ Double_Tolerance + ")";
// param2_gen == notgen && param2_err == 0
TString Param_2_Cut = "(abs(" + param2_gen + "-" + notgen + ")<"+ Double_Tolerance + ")&&(abs(" +param2_err +"-0.0)<" + Double_Tolerance + ")";
// Combine the individual Cuts
TString Fit_Cut_String = Param_1_Cut + "&&" + Param_2_Cut + "&&" + Fit_Cut;
// Toys have a defined generation Value, Fits to Data DO NOT
// param1_gen != notgen
TString p1isatoy = "(abs(" + param1_gen + "-" + notgen + ")>" + Double_Tolerance + ")";
// param2_gen != notgen
TString p2isatoy = "(abs(" + param2_gen + "-" + notgen + ")>" + Double_Tolerance + ")";
// Combine the individual Cuts
TString Toy_Cut_String = p1isatoy + "&&" + p2isatoy;
// Check for Toys in the file and wether I should run the FC code
allresults->Draw( NLL, Toy_Cut_String, "goff" );
bool Has_Toys = allresults->GetSelectedRows() > 0;
cout << endl << "NUMBER OF TOYS IN FILE:\t" << allresults->GetSelectedRows() << endl;
if( int(allresults->GetEntries() - allresults->GetSelectedRows()) == 0 )
{
cerr << "SERIOUS ERROR:\tSOMETHING HAS REALLY GOTTEN SCREWED UP!" << endl;
exit(-3498);
}
// Fit values for the global fit are now stored in:
//
// Global_Best_NLL, best_fit_values, x_point, y_point
// Tell the user
cout << "GLOBAL DATA BEST FIT NLL:\t" << setprecision(10) << Global_Best_NLL << "\tAT:\tX:" << setprecision(10) << x_point << "\tY:\t" <<setprecision(10)<< y_point << endl;
// Check wether the minima as defined from the Global fit is the true minima within the phase-space
//Check_Minima( allresults, Fit_Cut_String, &Global_Best_NLL, NLL, Double_Tolerance, param1_val, param2_val );
TString NLL_Min; // Of course ROOT doesn't have USEFUL constructors!
NLL_Min+=Global_Best_NLL;
// Plot the distribution of successfully fitted grid points for the PLL scan
// NB: For FC this will likely saturate due to multiple layers of fits
cout << endl << "FOUND UNIQUE GRID POINTS, PLOTTING" << endl;
LL2D_Grid( allresults, Fit_Cut_String, param1string, param2string, rand_gen, "LL", outputdir );
// Construct a plot string for the NLL plot and plot it
// PLL part of Draw_String
TString PLL = "(" + NLL + "-" + NLL_Min + ")";
// Gridding part of Draw_String
TString Param1_Param2 = ":" + param1_val + ":" + param2_val;
// Draw String for PLL
TString NLL_DrawString = PLL + Param1_Param2;
cout << endl << "PLOTTING NLL VARIATION" << endl;
// PLL plot
TH2* pllhist=NULL;
TGraph2D* pllgraph=NULL;
if( high_res ) {
pllhist = Plot_From_Cut( allresults, NLL_DrawString, Fit_Cut_String, rand_gen, param1string, param2string );
} else {
pllgraph = Plot_From_Cut_lo( allresults, NLL_DrawString, Fit_Cut_String, rand_gen, param1string, param2string );
}
// Array storing the addresses of all of the Physics Plots still in memory
TH2** All_Physics_Plots = new TH2*[all_parameter_values.size()];
TH2** All_Physics_Errors = new TH2*[all_parameter_values.size()];
TH2** All_Physics_Pulls = new TH2*[all_parameter_values.size()];
// Making use of switch
if( Want_Physics_Params )
{
// Physics Plots
Physics_Plots( all_parameter_values, best_fit_values, allresults, rand_gen, Param1_Param2, CV_Drift, All_Physics_Plots, Fit_Cut_String);
cout << endl << "Finalising CV Plots" << endl << endl;
Finalize_Physics_Plots( All_Physics_Plots, all_parameter_values, param1string, param2string, outputdir, CV_Drift );
if( Want_Extra_Physics_Param_Info )
{
// Physics Plots
//
// Passing false as Highly unlikely that I will 'ever' want to watch error/pull drift rather than the absolute value
Float_t* null_pointer=NULL;
Physics_Plots( all_parameter_errors, null_pointer, allresults, rand_gen, Param1_Param2, false, All_Physics_Errors, Fit_Cut_String);
Physics_Plots( all_parameter_pulls, null_pointer, allresults, rand_gen, Param1_Param2, false, All_Physics_Pulls, Fit_Cut_String);
cout << endl << "Finalising Extra CV Plots" << endl << endl;
Finalize_Physics_Plots( All_Physics_Errors, all_parameter_errors, param1string, param2string, outputdir, false );
Finalize_Physics_Plots( All_Physics_Pulls, all_parameter_pulls, param1string, param2string, outputdir, false );
}
}
TFile* new_FC_Output = NULL;
TTree* FC_Output = new TTree( "FC_Output", "FC_Output" );;
TH2* FC_Plot = NULL;
// Making use of switch
if( Has_Toys && want_FC )
{
// FC Plot
cout << "FOUND TOYS IN FILE, PLOTTING FC" <<endl;
TString FC_Tuple_File( outputdir+ "/FC_Tuple.root" );
new_FC_Output = new TFile( FC_Tuple_File, "RECREATE" );
FC_Plot = FC_TOYS( allresults, Fit_Cut_String, param1string, param2string, NLL, Fit_Cut, Global_Best_NLL, FC_Output, Double_Tolerance, rand_gen );
FC_Output->Write();
//LL2D_Grid( FC_Output, Fit_Cut, param1_val, param2_val, rand_gen, "FC" );
}
// Contours to be used in plotting
int cont_num = 3;
double* pllconts = new double[unsigned(cont_num)];
pllconts[0] = 1.15; pllconts[1] = 2.36;
pllconts[2] = 3.0;// pllconts[3] = 4.61;
double* fcconts = new double[unsigned(cont_num)];
fcconts[0] = 0.68; fcconts[1] = 0.9;
fcconts[2] = 0.95;// fcconts[3] = 0.99;
double* confs = new double[unsigned(cont_num)];
confs[0] = 68.0; confs[1] = 90.0;
confs[2] = 95.0;// confs[3] = 99.0;
cout <<endl<< "SAVING GRAPHS" << endl;
if( high_res )
{
Plot_Styled_Contour( pllhist, cont_num, pllconts, confs, outputdir, "Likelihood Profile" );
} else {
//Plot_Styled_Contour2( pllgraph, cont_num, pllconts, confs, outputdir, "Likelihood Profile" );
}
if( Has_Toys && want_FC ) // If FC was generated
{
// Thinking of implementing a PLL Plot for the FC as it's easier to plot that (and looks more impressive)
//TH2* FC_PLL = Invert_PLL( FC_Plot );
Plot_Styled_Contour( FC_Plot, cont_num, fcconts, confs, outputdir, "FeldmanCousins Profile" );
//Plot_Styled_Contour( FC_PLL, cont_num, fcconts, confs, outputdir, "FeldmanCousins Profile PLL" );
//TString FC_Tuple_File( outputdir+ "FC_Tuple.root" );
//TFile* new_FC_Output = new TFile( FC_Tuple_File, "RECREATE" );
//FC_Output->Write();
Plot_Both( pllhist, FC_Plot, cont_num, fcconts, pllconts, confs, outputdir );
FC_Stats( FC_Output, param1string, param2string, rand_gen, outputdir );
if( new_FC_Output != NULL ) new_FC_Output->Close();
}
return 0;
}
void PFcorr(bool isMC=false) {
gStyle->SetOptStat(0);
gStyle->SetTitleOffset(1.8,"Y");
TString filename = "../test/pftuple";
if(isMC) filename += "MC";
filename += ".root";
TFile *f = new TFile(filename.Data());
TNtuple *nt = (TNtuple*) f->Get("pfCandidateAnalyzer/nt");
TCanvas *c1 = new TCanvas("c1","c1",800,800);
c1->Divide(2,2);
TString hadron = "tkptmax>10";
//hadron += " && type==1";
nt->SetAlias("trksel","(algo<=7 && nhits>=5 && relpterr<=0.05 && abs(nd0)<3 && abs(ndz)<3)");
TString seltrk = " && trksel";
TString fakehadron = hadron + " && fake";
Float_t axisrange=500.;
if(!isMC) axisrange=350.;
c1->cd(1);
nt->Draw(Form("tkptsum:eetsum+hetsum>>h1(50,0,%f,50,0,%f)",axisrange,axisrange),hadron.Data(),"goff");
h1->SetTitle("PF candidate with p_{T}>10 GeV/c track element; PF calo cluster E_{T} sum (ECAL+HCAL); Track p_{T} sum");
h1->Draw("colz");
if(isMC) {
nt->Draw(Form("tkptsum:eetsum+hetsum>>h1f(50,0,%f,50,0,%f)",axisrange,axisrange),fakehadron.Data(),"goff");
TH2F* h1 = h1;
h1f->Divide(h1); h1f->Scale(100.);
h1f->Draw("boxsame");
}
gPad->SetLogz();
c1->cd(2);
nt->Draw(Form("tkptsum:eetsum+hetsum>>h2(50,0,%f,50,0,%f)",axisrange,axisrange),(hadron+seltrk).Data(),"goff");
h2->SetTitle("PF candidate with p_{T}>10 GeV/c track element; PF calo cluster E_{T} sum (ECAL+HCAL); SELECTED Track p_{T} sum");
h2->Draw("colz");
if(isMC) {
nt->Draw(Form("tkptsum:eetsum+hetsum>>h2f(50,0,%f,50,0,%f)",axisrange,axisrange),(fakehadron+seltrk).Data(),"goff");
h2f->Draw("boxsame");
}
gPad->SetLogz();
c1->cd(3);
nt->Draw(Form("tkptmax:eetsum+hetsum>>h3(50,0,%f,50,0,%f)",axisrange,axisrange),hadron.Data(),"goff");
h3->SetTitle("PF candidate with p_{T}>10 GeV/c track element; PF calo cluster E_{T} sum (ECAL+HCAL); Track with MAX p_{T}");
h3->Draw("colz");
if(isMC) {
nt->Draw(Form("tkptmax:eetsum+hetsum>>h3f(50,0,%f,50,0,%f)",axisrange,axisrange),fakehadron.Data(),"goff");
h3f->Draw("boxsame");
}
gPad->SetLogz();
c1->cd(4);
nt->Draw(Form("tkptmax:eetsum+hetsum>>h4(50,0,%f,50,0,%f)",axisrange,axisrange),(hadron+seltrk).Data(),"goff");
h4->SetTitle("PF candidate with p_{T}>10 GeV/c track element; PF calo cluster E_{T} sum (ECAL+HCAL); SELECTED Track with MAX p_{T}");
h4->Draw("colz");
if(isMC) {
nt->Draw(Form("tkptmax:eetsum+hetsum>>h4f(50,0,%f,50,0,%f)",axisrange,axisrange),(fakehadron+seltrk).Data(),"goff");
h4f->Draw("boxsame");
}
gPad->SetLogz();
}
void parallelcoordtrans() {
Double_t x,y,z,u,v,w,a,b,c;
Double_t s1x, s1y, s1z;
Double_t s2x, s2y, s2z;
Double_t s3x, s3y, s3z;
r = new TRandom();;
TCanvas *c1 = new TCanvas("c1", "c1",0,0,900,1000);
c1->Divide(1,2);
if (gVirtualX && !gVirtualX->InheritsFrom("TGCocoa")) {
std::cout<<"This macro works only on MacOS X with --enable-cocoa\n";
delete c1;
delete r;
return;
}
TNtuple *nt = new TNtuple("nt","Demo ntuple","x:y:z:u:v:w:a:b:c");
int n=0;
for (Int_t i=0; i<1500; i++) {
r->Sphere(s1x, s1y, s1z, 0.1);
r->Sphere(s2x, s2y, s2z, 0.2);
r->Sphere(s3x, s3y, s3z, 0.05);
generate_random(i);
nt->Fill(r1, r2, r3, r4, r5, r6, r7, r8, r9);
n++;
generate_random(i);
nt->Fill(s1x, s1y, s1z, s2x, s2y, s2z, r7, r8, r9);
n++;
generate_random(i);
nt->Fill(r1, r2, r3, r4, r5, r6, r7, s3y, r9);
n++;
generate_random(i);
nt->Fill(s2x-1, s2y-1, s2z, s1x+.5, s1y+.5, s1z+.5, r7, r8, r9);
n++;
generate_random(i);
nt->Fill(r1, r2, r3, r4, r5, r6, r7, r8, r9);
n++;
generate_random(i);
nt->Fill(s1x+1, s1y+1, s1z+1, s3x-2, s3y-2, s3z-2, r7, r8, r9);
n++;
generate_random(i);
nt->Fill(r1, r2, r3, r4, r5, r6, s3x, r8, s3z );
n++;
}
TParallelCoordVar* pcv;
c1->cd(1);
// ||-Coord plot without transparency
nt->Draw("x:y:z:u:v:w:a:b:c","","para");
TParallelCoord* para1 = (TParallelCoord*)gPad->GetListOfPrimitives()->FindObject("ParaCoord");
para1->SetLineColor(25);
pcv = (TParallelCoordVar*)para1->GetVarList()->FindObject("x"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para1->GetVarList()->FindObject("y"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para1->GetVarList()->FindObject("z"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para1->GetVarList()->FindObject("a"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para1->GetVarList()->FindObject("b"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para1->GetVarList()->FindObject("c"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para1->GetVarList()->FindObject("u"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para1->GetVarList()->FindObject("v"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para1->GetVarList()->FindObject("w"); pcv->SetHistogramHeight(0.);
// ||-Coord plot with transparency
TColor *col26 = gROOT->GetColor(26); col26->SetAlpha(0.01);
c1->cd(2);
nt->Draw("x:y:z:u:v:w:a:b:c","","para");
TParallelCoord* para2 = (TParallelCoord*)gPad->GetListOfPrimitives()->FindObject("ParaCoord");
para2->SetLineColor(26);
pcv = (TParallelCoordVar*)para2->GetVarList()->FindObject("x"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para2->GetVarList()->FindObject("y"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para2->GetVarList()->FindObject("z"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para2->GetVarList()->FindObject("a"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para2->GetVarList()->FindObject("b"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para2->GetVarList()->FindObject("c"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para2->GetVarList()->FindObject("u"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para2->GetVarList()->FindObject("v"); pcv->SetHistogramHeight(0.);
pcv = (TParallelCoordVar*)para2->GetVarList()->FindObject("w"); pcv->SetHistogramHeight(0.);
}
void ntuple1() {
//Small tree analysis script
// To see the output of this macro, click begin_html <a href="gif/ntuple1.gif">here</a> end_html
//Author:: Rene Brun
//just in case this script is executed multiple times
delete gROOT->GetListOfFiles()->FindObject("hsimple.root");
delete gROOT->GetListOfCanvases()->FindObject("c1");
gBenchmark->Start("ntuple1");
//
// Connect ROOT histogram/ntuple demonstration file
// generated by example $ROOTSYS/tutorials/hsimple.C.
TFile *f1 = TFile::Open("hsimple.root");
if (!f1) return;
//
// Create a canvas, with 4 pads
//
TCanvas *c1 = new TCanvas("c1","The Ntuple canvas",200,10,700,780);
TPad *pad1 = new TPad("pad1","This is pad1",0.02,0.52,0.48,0.98,21);
TPad *pad2 = new TPad("pad2","This is pad2",0.52,0.52,0.98,0.98,21);
TPad *pad3 = new TPad("pad3","This is pad3",0.02,0.02,0.48,0.48,21);
TPad *pad4 = new TPad("pad4","This is pad4",0.52,0.02,0.98,0.48,1);
pad1->Draw();
pad2->Draw();
pad3->Draw();
pad4->Draw();
//
// Change default style for the statistics box
gStyle->SetStatW(0.30);
gStyle->SetStatH(0.20);
gStyle->SetStatColor(42);
//
// Display a function of one ntuple column imposing a condition
// on another column.
pad1->cd();
pad1->SetGrid();
pad1->SetLogy();
pad1->GetFrame()->SetFillColor(15);
TNtuple *ntuple = (TNtuple*)f1->Get("ntuple");
ntuple->SetLineColor(1);
ntuple->SetFillStyle(1001);
ntuple->SetFillColor(45);
ntuple->Draw("3*px+2","px**2+py**2>1");
ntuple->SetFillColor(38);
ntuple->Draw("2*px+2","pz>2","same");
ntuple->SetFillColor(5);
ntuple->Draw("1.3*px+2","(px^2+py^2>4) && py>0","same");
pad1->RedrawAxis();
//
// Display the profile of two columns
// The profile histogram produced is saved in the current directory with
// the name hprofs
pad2->cd();
pad2->SetGrid();
pad2->GetFrame()->SetFillColor(32);
ntuple->Draw("pz:px>>hprofs","","goffprofs");
TProfile *hprofs = (TProfile*)gDirectory->Get("hprofs");
hprofs->SetMarkerColor(5);
hprofs->SetMarkerSize(0.7);
hprofs->SetMarkerStyle(21);
hprofs->Fit("pol2");
// Get pointer to fitted function and modify its attributes
TF1 *fpol2 = hprofs->GetFunction("pol2");
fpol2->SetLineWidth(4);
fpol2->SetLineColor(2);
//
// Display a scatter plot of two columns with a selection.
// Superimpose the result of another cut with a different marker color
pad3->cd();
pad3->GetFrame()->SetFillColor(38);
pad3->GetFrame()->SetBorderSize(8);
ntuple->SetMarkerColor(1);
ntuple->Draw("py:px","pz>1");
ntuple->SetMarkerColor(2);
ntuple->Draw("py:px","pz<1","same");
//
// Display a 3-D scatter plot of 3 columns. Superimpose a different selection.
pad4->cd();
ntuple->Draw("pz:py:px","(pz<10 && pz>6)+(pz<4 && pz>3)");
ntuple->SetMarkerColor(4);
ntuple->Draw("pz:py:px","pz<6 && pz>4","same");
ntuple->SetMarkerColor(5);
ntuple->Draw("pz:py:px","pz<4 && pz>3","same");
TPaveText *l4 = new TPaveText(-0.9,0.5,0.9,0.95);
l4->SetFillColor(42);
l4->SetTextAlign(12);
l4->AddText("You can interactively rotate this view in 2 ways:");
l4->AddText(" - With the RotateCube in clicking in this pad");
l4->AddText(" - Selecting View with x3d in the View menu");
l4->Draw();
//
c1->cd();
c1->Update();
gStyle->SetStatColor(19);
gBenchmark->Show("ntuple1");
}
void doFit_asymptotic(int which = 2,
int numCat = 5,
/*double splitVal1 = 0.54,
double splitVal2 = 0.92,
double splitVal3 = 0.865,
double splitVal4 = 0,
double splitVal5 = 0.71,*/
/*double splitVal1 = 0.89,
double splitVal2 = 0.72,
double splitVal3 = 0.55,
double splitVal4 = 0.05,
double splitVal5 = -100,*/
double splitVal1 = 0.05,
double splitVal2 = 0.55,
double splitVal3 = 0.74,
double splitVal4 = 0.89,
double splitVal5 = -100,
//TString fileName = "appOutput_SM_Oct14.root",
//TString modelDir = "/afs/cern.ch/user/f/fabstoec/scratch0/optimizeMVACats/MVAmodel/"
//TString fileName = "Tmva_AppOutput_SMDipho_2012Jan16_wrongBR.root",
//TString fileName = "Tmva_AppOutput_SMDipho_2012Jan16.root",
//TString fileName = "Tmva_AppOutput_SMDipho_2012Jan16_NewVBF.root",
//TString fileName = "Tmva_AppOutput_SMDipho_2012Jan16_NewVBF_CorrScaleFactor.root",
TString fileName = "Tmva_AppOutput_SMDipho_2012Jan16_NewVBF_120.root ",
TString modelDir = "/afs/cern.ch/user/m/mingyang/optimizeMVACats/MVAmodel/"
) {
if(numCat > 6) return;//set maximum number of categories
//===============1.remove the printout from roofit=========================
RooMsgService::instance().setSilentMode(true);
RooMsgService::instance().getStream(1).removeTopic(RooFit::Caching);
RooMsgService::instance().getStream(0).removeTopic(RooFit::Minimization);
RooMsgService::instance().getStream(1).removeTopic(RooFit::Minimization);
RooMsgService::instance().getStream(0).removeTopic(RooFit::Plotting);
RooMsgService::instance().getStream(1).removeTopic(RooFit::Plotting);
RooMsgService::instance().getStream(1).removeTopic(RooFit::Fitting);
RooMsgService::instance().getStream(0).removeTopic(RooFit::Eval);
RooMsgService::instance().getStream(1).removeTopic(RooFit::Eval);
//============2.define nonfit variables==========================
//--------input file-------------------
TString modelName = modelDir+fileName;
//--------cross section-----
double theXS = 1.0;
double maxXS = 10.0;
//--------the signal strength modifier range ------
double muMin = 0.;
double muMax = maxXS/theXS;
double theMu = 0.;//set the initial value of Mu to 0 (background only hypothesis)
//--------parameters--------------------------------
double nsig;
double nbgini;
double nbg;
double exp;
double nbg_update;
double exp_update;
//--------set up category bourndary variables--------
int startCat = 0;
int endCat = numCat+1;
double* catVals = new double[numCat+1];//ming:array of mva category cut values
double allVals[7];//ming:all the boundary values
allVals[0] = splitVal1;
allVals[1] = splitVal2;
allVals[2] = splitVal3;
allVals[3] = splitVal4;
allVals[4] = splitVal5;
//allVals[5] = 1.;
//allVals[6] = -0.5;
allVals[5] = 1.;
allVals[6] = -1;
double allValsSorted[7];
for(int i=0; i<7; ++i) {//make allValsSorted increase with the order
allValsSorted[i]=allVals[i];
int tSpot = i;
for(int j = i-1; j>=0; --j) {
if(allValsSorted[j] > allValsSorted[tSpot]) {
// switch
double tempVal = allValsSorted[j];
allValsSorted[j] = allValsSorted[tSpot];
allValsSorted[tSpot] = tempVal;
tSpot--;
} else break;
}
}
for(int i=6-numCat; i<=6; ++i)
catVals[i-6+numCat] = allValsSorted[i];//catVals from -1 to 1 increase with the order
//==========3.read in the input tree==============
TFile* modFile = new TFile(modelName.Data());
TNtuple* tup = (TNtuple*) modFile->FindObjectAny("MITMVAtuple");
//============fit=============
//-----------set the independent variable----------------
RooRealVar* mass = new RooRealVar("mass","",100.,180.);
mass->setRange(100.,180.);
mass->setBins(10000,"cache");//bins for numrical integration
mass->setBins(320);//bins for fitting and plotting
//-----------set the variable to make dataset-------------
RooRealVar* weight = new RooRealVar("weight","",0.,100.);
RooRealVar* proc = new RooRealVar("proc" ,"",0.,10.);
RooRealVar* mva = new RooRealVar("mva" ,"",-10.,10.);
RooRealVar* vbftag = new RooRealVar("vbftag" ,"",0.,1.);
//----------prepare the dataset---------------------------
TString* dataNames = new TString[numCat+1];
TString* sigNames = new TString[numCat+1];
RooDataHist** sigCat = new RooDataHist*[numCat+1];
RooDataSet** dataCat = new RooDataSet*[numCat+1];
RooDataHist** dataHCat = new RooDataHist*[numCat+1];
TString baseCut = "mass > 100 && mass < 180 ";
TString baseBG = baseCut + TString(" && proc > 3 && proc < 11");//MC background
TString baseSIG = baseCut + TString(" && proc < 4 ");//MC signal
TString baseObsData = baseCut + TString(" && proc==11");//obs data for count
int* numObsData= new int[numCat+1];
//----------prepare the pdf-------------------------------
//signal model
RooAbsPdf** sigpdfcat_part1 = new RooAbsPdf*[numCat+1];
RooAbsPdf** sigpdfcat_part2 = new RooAbsPdf*[numCat+1];
RooAbsPdf** sigpdfcat = new RooAbsPdf*[numCat+1];
RooRealVar** sigMean_part1 = new RooRealVar*[numCat+1];
RooRealVar** sigWidth_part1 = new RooRealVar*[numCat+1];
RooRealVar** sigMean_part2 = new RooRealVar*[numCat+1];
RooRealVar** sigWidth_part2 = new RooRealVar*[numCat+1];
RooRealVar** sigRatio = new RooRealVar*[numCat+1];
double* nominalSignal = new double[numCat+1];
TH1D** sigH = new TH1D*[numCat+1];//ming:used to get nominalSignal and input to RooDataHist
TH1D** ObsDataH = new TH1D*[numCat+1];//obs data for count
//background model
//exp
RooExponential** bgpdfcat_exp = new RooExponential*[numCat+1];
RooRealVar** bgpdfval_exp = new RooRealVar*[numCat+1];
//bs
RooBernstein** bgpdfcat_bs = new RooBernstein*[numCat+1];
RooConstVar* bgpdfval0_bs = new RooConstVar;
RooRealVar** bgpdfval1_bs = new RooRealVar*[numCat+1];
RooRealVar** bgpdfval2_bs = new RooRealVar*[numCat+1];
RooRealVar** bgpdfval3_bs = new RooRealVar*[numCat+1];
RooRealVar** bgpdfval4_bs = new RooRealVar*[numCat+1];
//total model
RooAddPdf** totpdfcat = new RooAddPdf*[numCat+1];
RooRealVar** nsigcat = new RooRealVar*[numCat+1];
RooRealVar** nbgcat = new RooRealVar*[numCat+1];
//----------nll for the mu given the dataset---------------
RooNLLVar** totNllExt = new RooNLLVar*[numCat+1];//total Nll
//--------draw option------------------
/*bool drawSigModel = false;
bool drawBkgModel = false;
bool draw95CLlimitModel = false;
bool drawcan = false;*/
bool drawSigModel = true;
bool drawBkgModel = true;
bool draw95CLlimitModel = true;
bool drawcan = false;
RooPlot** frame = new RooPlot*[20];//define an array of pointer;frame[i] is a pointer
TCanvas* thisCan = new TCanvas("thisCan","MyCanvas",1200,(numCat+1)*300);
TCanvas* extraCan = new TCanvas("extraCan","extraCan",800,600);
thisCan->Divide(3,numCat+1);
gStyle->SetMarkerSize(0.5);
//---------count option------------------
bool enableCount = true;
//============category boundaries===============
std::stringstream mvaCut;
std::stringstream mvaCutLabel;
TString SIGstring;
TString BGstring;
TString ObsDatastring;
for(int i=0; i<numCat+1; ++i) {
if(i!= numCat) {
mvaCut.str("");
mvaCut << " && mva > "<<catVals[i]<<" && mva < "<<catVals[i+1];//cut values for cat i
std::cout<<mvaCut.str().c_str()<<std::endl;
mvaCutLabel.str("");
mvaCutLabel << " mva > "<<catVals[i]<<" && mva < "<<catVals[i+1];//cut values for cat i
}
if(i== numCat) {
mvaCutLabel.str("");
mvaCutLabel << " Dijet-TAG ";
}
//-----obsData for count-----
//read in the obsdata mass hist for category i
std::stringstream pSS;
pSS.str("");
pSS << "ObsDataH" <<i;
ObsDataH[i] = new TH1D(pSS.str().c_str(),"",320,100.,180.);//0.25 GeV per bin
TString theDrawString0 = TString("mass>>")+TString(pSS.str().c_str());
if(i!=numCat){
ObsDatastring = baseObsData+TString(mvaCut.str().c_str())+TString(" && vbftag==0");
}
if(i==numCat){
ObsDatastring = baseObsData+TString(" && vbftag==1 && mva>0.05");
}
extraCan->cd();
tup->Draw(theDrawString0.Data(),ObsDatastring.Data());
numObsData[i] = ObsDataH[i]->GetEntries();//number of events in the signal mass hist
//-----signal model-----
//read in the signal mass hist for category i
pSS.str("");
pSS << "sigH" <<i;
sigH[i] = new TH1D(pSS.str().c_str(),"",320,100.,180.);//0.25 GeV per bin
TString theDrawString = TString("mass>>")+TString(pSS.str().c_str());
//TString SIGstring = TString("weight*(")+baseSIG+TString(mvaCut.str().c_str())+TString(")");//signal cut along with cat cut
if(i!=numCat){
SIGstring = TString("weight*(")+baseSIG+TString(mvaCut.str().c_str())+TString(" && vbftag==0")+TString(")");
}
if(i==numCat){
SIGstring = TString("weight*(")+baseSIG+TString(" && vbftag==1")+TString(" && mva>0.05")+TString(")");
}
extraCan->cd();
tup->Draw(theDrawString.Data(),SIGstring.Data());
//sigH[i] = (TH1D*)gPad->GetPrimitive(pSS.str().c_str());
nominalSignal[i] = sigH[i]->GetSumOfWeights();//number of events in the signal mass hist
//obtain the signal RooDataHist to be fit for category i
pSS.str("");
pSS << "sigdata" << i;
sigNames[i] = TString(pSS.str().c_str());
sigCat[i] = new RooDataHist( sigNames[i].Data(),"",*mass,sigH[i]);//hist used to extract signal model for category i
//set fit parameter
pSS.str("");
pSS << "nsigcat" << i;
nsigcat[i] = new RooRealVar(pSS.str().c_str(),"",0.);//initialize number of signal events
nsigcat[i]->setVal(nominalSignal[i]*theMu);//set nsigcat[i] to constant
pSS.str("");
pSS<<"sigMean_part1"<<i;
sigMean_part1[i] = new RooRealVar(pSS.str().c_str(),"",125.,100.,180.);
sigMean_part1[i] ->removeRange();
pSS.str("");
pSS<<"sigWidth_part1"<<i;
sigWidth_part1[i] = new RooRealVar(pSS.str().c_str(),"",1.5,-5.,5.);
sigWidth_part1[i] ->removeRange();
pSS.str("");
pSS<<"sigMean_part2"<<i;
sigMean_part2[i] = new RooRealVar(pSS.str().c_str(),"",125.,100.,180.);
sigMean_part2[i] ->removeRange();
pSS.str("");
pSS<<"sigWidth_part2"<<i;
sigWidth_part2[i] = new RooRealVar(pSS.str().c_str(),"",2.5,-5.,5.);
sigWidth_part2[i] ->removeRange();
pSS.str("");
pSS<<"sigRatio"<<i;
sigRatio[i] = new RooRealVar(pSS.str().c_str(),"",0.5,0.1,2.);
sigRatio[i]->removeRange();
//signal pdf
pSS.str("");
pSS << "sigpdfcat_part1" << i;
sigpdfcat_part1[i] = new RooGaussian ( pSS.str().c_str(),"",*mass,*sigMean_part1[i],*sigWidth_part1[i]);
pSS.str("");
pSS << "sigpdfcat_part2" << i;
sigpdfcat_part2[i] = new RooGaussian ( pSS.str().c_str(),"",*mass,*sigMean_part2[i],*sigWidth_part2[i]);
pSS.str("");
pSS << "sigpdfcat" << i;
sigpdfcat[i] = new RooAddPdf(pSS.str().c_str(),"",*sigpdfcat_part1[i],*sigpdfcat_part2[i],*sigRatio[i]);//ratio*s1+(1-ratio)*s2
//fit
sigpdfcat[i]->fitTo(*sigCat[i]);
//fix signal model parameters
sigMean_part1[i] ->setConstant();
sigWidth_part1[i] ->setConstant();
sigMean_part2[i] ->setConstant();
sigWidth_part2[i] ->setConstant();
sigRatio[i] ->setConstant();
if( drawSigModel ) {
frame[3*i+1]= mass->frame();
pSS.str("");
pSS << "125 GeV Higgs MC and Model (5.089 fb-1) ";
frame[3*i+1]->SetTitle(pSS.str().c_str());
sigCat[i]->plotOn(frame[3*i+1]);
sigpdfcat[i]->plotOn(frame[3*i+1]);
thisCan->cd(3*i+1);
frame[3*i+1]->Draw();
TLatex* text1=new TLatex(3.5,23.5,mvaCutLabel.str().c_str());
text1->SetNDC();
text1->SetTextAlign(13);
text1->SetX(0.4);//(0.940);
text1->SetY(0.8);
text1->SetTextFont(42);
text1->SetTextSize(0.065);// dflt=28
text1->Draw();
std::stringstream NSigLabel;
NSigLabel.str("");
NSigLabel <<"NSig = "<<nominalSignal[i];
printf("nsig:%d:\n",nominalSignal[i]);
TLatex* text2=new TLatex(3.5,23.5,NSigLabel.str().c_str());
text2->SetNDC();
text2->SetTextAlign(13);
text2->SetX(0.4);//(0.940);
text2->SetY(0.7);
text2->SetTextFont(42);
text2->SetTextSize(0.065);// dflt=28
text2->Draw();
}
//-----background model-----
//obtain the backgroud RooDataHist to be fit for category i
pSS.str("");
pSS << "data_cat" << i;
dataNames[i] = TString(pSS.str().c_str());
if(i!=numCat){
BGstring = baseBG +TString(mvaCut.str().c_str())+TString(" && vbftag==0");
}
if(i==numCat){
BGstring = baseBG +TString(" && vbftag==1");
}
dataCat[i] = new RooDataSet (dataNames[i].Data(),"",tup,RooArgSet(*mass,*weight,*proc,*mva,*vbftag),BGstring.Data(), "weight");//MC bkg dataset used to extract background model for cat i
//set fit parameter and pdf
pSS.str("");
pSS << "nbgcat" << i;
nbgini=dataCat[i]->sumEntries();
nbgcat[i] = new RooRealVar(pSS.str().c_str(),"",nbgini,0,50000);//number of background events;initial value total number of events in the mc background dataset
nbgcat[i]->removeRange();
switch(which){
case 1:
{
pSS.str("");
pSS << "e" <<i;
bgpdfval_exp[i] = new RooRealVar(pSS.str().c_str(),"",0.,-100.,100.);//exponet parameter
bgpdfval_exp[i]->removeRange();
pSS.str("");
pSS << "bgpdfcat_exp" << i;
bgpdfcat_exp[i] = new RooExponential(pSS.str().c_str(),"",*mass,*bgpdfval_exp[i]);
bgpdfcat_exp[i]->fitTo(*dataCat[i]);
if( drawBkgModel ) {
frame[3*i+2]= mass->frame();
pSS.str("");
//pSS << "MC Bkg Data And Model 4thBSPol (5.089 fb-1) "<<mvaCut.str().c_str();
pSS << "MC Bkg Data And Model exp";
frame[3*i+2]->SetTitle(pSS.str().c_str());
dataCat[i]->plotOn(frame[3*i+2]);
bgpdfcat_exp[i]->plotOn(frame[3*i+2]);
thisCan->cd(3*i+2);
frame[3*i+2]->Draw();
std::stringstream NBkgLabel;
NBkgLabel.str("");
NBkgLabel <<"NBkg = "<<nbgini;
TLatex* text3=new TLatex(3.5,23.5,NBkgLabel.str().c_str());
text3->SetNDC();
text3->SetTextAlign(13);
text3->SetX(0.6);//(0.940);
text3->SetY(0.7);
text3->SetTextFont(42);
text3->SetTextSize(0.065);// dflt=28
text3->Draw();
}
//-----geneate asimov dataset from background model-----
pSS.str("");
pSS << "dataHCat" << i;
dataHCat[i] = bgpdfcat_exp[i]->generateBinned(*mass,dataCat[i]->sumEntries(),RooFit::Asimov(),RooFit::Name(pSS.str().c_str()));
//---to get the total pdf---
pSS.str("");
pSS << "totpdfcat" <<i;
totpdfcat[i] = new RooAddPdf(pSS.str().c_str(),"",RooArgList(*sigpdfcat[i],*bgpdfcat_exp[i]),RooArgList(*nsigcat[i],*nbgcat[i]));//build the sig plus bkg model
totpdfcat[i]->fitTo(*dataHCat[i],RooFit::Extended(true));
break;
}
case 2:
{
pSS.str("");
pSS << "c0";
bgpdfval0_bs= new RooConstVar(pSS.str().c_str(),"",1.0);//exponet parameter
pSS.str("");
pSS << "c1" <<i;
bgpdfval1_bs[i] = new RooRealVar(pSS.str().c_str(),"",0.,0,10000.);//exponet parameter
//bgpdfval1_bs[i]->removeRange();
pSS.str("");
pSS << "c2" <<i;
bgpdfval2_bs[i] = new RooRealVar(pSS.str().c_str(),"",0.,0,10000.);//exponet parameter
//bgpdfval2_bs[i]->removeRange();
pSS.str("");
pSS << "c3" <<i;
bgpdfval3_bs[i] = new RooRealVar(pSS.str().c_str(),"",0.,0.,10000.);//exponet parameter
//bgpdfval3_bs[i]->removeRange();
pSS.str("");
pSS << "c4" <<i;
bgpdfval4_bs[i] = new RooRealVar(pSS.str().c_str(),"",0.,0.,10000.);//exponet parameter
//bgpdfval4_bs[i]->removeRange();
pSS.str("");
pSS << "bgpdfcat_bs" << i;
bgpdfcat_bs[i] = new RooBernstein(pSS.str().c_str(),"",*mass,RooArgList(*bgpdfval0_bs,*bgpdfval1_bs[i],*bgpdfval2_bs[i],*bgpdfval3_bs[i],*bgpdfval4_bs[i]));
bgpdfcat_bs[i]->fitTo(*dataCat[i]);
//draw the sig RooDataHist and sig model
if( drawBkgModel ) {
frame[3*i+2]= mass->frame();
pSS.str("");
//pSS << "MC Bkg Data And Model 4thBSPol (5.089 fb-1) "<<mvaCut.str().c_str();
pSS << "MC Bkg Data And Model 4thBSPol";
frame[3*i+2]->SetTitle(pSS.str().c_str());
dataCat[i]->plotOn(frame[3*i+2]);
bgpdfcat_bs[i]->plotOn(frame[3*i+2]);
thisCan->cd(3*i+2);
frame[3*i+2]->Draw();
std::stringstream NBkgLabel;
NBkgLabel.str("");
NBkgLabel <<"NBkg = "<<nbgini;
TLatex* text3=new TLatex(3.5,23.5,NBkgLabel.str().c_str());
text3->SetNDC();
text3->SetTextAlign(13);
text3->SetX(0.6);//(0.940);
text3->SetY(0.7);
text3->SetTextFont(42);
text3->SetTextSize(0.065);// dflt=28
text3->Draw();
}
//-----geneate asimov dataset from background model-----
pSS.str("");
pSS << "dataHCat" << i;
dataHCat[i] = bgpdfcat_bs[i]->generateBinned(*mass,dataCat[i]->sumEntries(),RooFit::Asimov(),RooFit::Name(pSS.str().c_str()));
//---to get the total pdf---
pSS.str("");
pSS << "totpdfcat" <<i;
totpdfcat[i] = new RooAddPdf(pSS.str().c_str(),"",RooArgList(*sigpdfcat[i],*bgpdfcat_bs[i]),RooArgList(*nsigcat[i],*nbgcat[i]));//build the sig plus bkg model
totpdfcat[i]->fitTo(*dataHCat[i],RooFit::Extended(true));
break;
}
}
totNllExt[i] = (RooNLLVar*) totpdfcat[i]->createNLL(*dataHCat[i],RooFit::Extended(true));//calculate nll for each category
}
// ===========95% C.L.upper limit on theMu===========
//-----NLL for background only model theMu=0-----
double minNll = 0.;
for(int i=startCat; i<endCat; ++i) minNll += totNllExt[i]->getVal();//ming:the total Nll for theMu=0 (background only hypothesis)
std::cout<<" start = "<<minNll<<std::endl;
//-----Target NLL for 95% C.L.upper limit on theMu-----
//double cl = 0.95;
double targetNll = minNll + 1.92 ; //0.5*pow(ROOT::Math::normal_quantile(1.-0.5*(1.-cl),1.0), 2.);
//-----set the tolerance for the 95% C.L.upper limit on theMu-----
double tRelAcc = 0.001;
double tAbsAcc = 0.0005;
//-----initial value for the eErr and theMu-----
double rErr = 0.5*(muMax - muMin);
theMu = 0.5*(muMax + muMin);
//-----interate theMu till the rErr is less than either absolute value 0.0005 or the relative error 0.001
while ( rErr > std::max(tRelAcc * theMu, tAbsAcc) ) {
double nextNll = 0.;
for(int i=startCat; i<endCat; ++i) {
nsigcat[i]->setVal(nominalSignal[i]*theMu);//update nsigcat with new theMu
totpdfcat[i]->fitTo(*dataHCat[i],RooFit::Extended(true));//refit the totpdfcat with updated theMu
nextNll += totNllExt[i]->getVal();//totNllExt update with the totpdfcat
std::cout<<" for mu="<<theMu<<" nll = "<<nextNll<<" ( "<<targetNll<<" )"<<std::endl;
}
if(nextNll < targetNll)
muMin = theMu;
else
muMax = theMu;
rErr = 0.5*(muMax - muMin);
theMu = 0.5*(muMax + muMin);
}
double tR_XS = theMu *theXS;//ming: the 95% C.L.limit on signal strength modifier
double tR_Er = rErr *theXS;//ming: the error on the limit
std::cout<<std::endl<<"95% C.L. Limit Mu="<<setprecision(5)<<" [ RES ] ( "<<tR_XS<<" +- "<<tR_Er<<" ) x sigma (FP/SM)"<<std::endl;
std::stringstream label95Mu;
label95Mu.str("");
label95Mu << "95% C.L. Limit Mu="<<setprecision(5)<<tR_XS<<" +- "<<tR_Er;
if(draw95CLlimitModel){
for(int i=startCat; i<endCat; ++i) {
frame[3*i+3]= mass->frame();
std::stringstream pSS;
pSS.str("");
pSS << "Asimov Data and 95CL limit Mu Model";
frame[3*i+3]->SetTitle(pSS.str().c_str());
dataHCat[i]->plotOn(frame[3*i+3]);
totpdfcat[i]->plotOn(frame[3*i+3]);
thisCan->cd(3*i+3);
frame[3*i+3]->Draw();
TLatex* text4=new TLatex(3.5,23.5,label95Mu.str().c_str());
text4->SetNDC();
text4->SetTextAlign(13);
text4->SetX(0.2);//(0.940);
text4->SetY(0.8);
text4->SetTextFont(42);
text4->SetTextSize(0.065);// dflt=28
text4->Draw();
}
}
if(drawcan){
std::stringstream CanName;
CanName.str("");
CanName << "/afs/cern.ch/user/m/mingyang/optimizeMVACats/plot/"<<numCat<<"cat_95CLlimitMu_"<<setprecision(5)<<tR_XS<<".eps";
thisCan->SaveAs(CanName.str().c_str());
}
for(int i=0; i<numCat+1; ++i){
if(enableCount){
printf("cat:%d NumObsData:%d\n",i,numObsData[i]);
}
}
return;
}
void fragmentYieldsPlot() {
gStyle->SetOptStat(0000000000); //remove the for this graphs totally redundant statbox
int ZNumGiven;
cout << "Enter fragment Z-number (eg. 1): ";
cin >> ZNumGiven;
TCanvas *c1 = new TCanvas("fragmentYieldsPlot", "Total yield of fragments zero to ten degrees as function of depth");
TString fragmentNameChoices[6] = {"H","He","Li","Be","B","C"};
TString fragmentName = fragmentNameChoices[ZNumGiven-1];
std::cout << fragmentName << endl;
TH1F* dummyHisto = new TH1F("dummyHisto", fragmentName + " yields 0-10 degrees" ,100, 0.0,40); //Dummyhisto fix for missing TNtuple methods.
dummyHisto->SetXTitle("Depth (cm)");
dummyHisto->SetYTitle("N/N0");
ifstream in;
TString experimentalDataPath = "experimentalData/iaeaBenchmark/yields/TDK" + fragmentName + ".dat";
ifstream in;
//Pull in ascii/exfor-style data
in.open(experimentalDataPath);
Float_t f1,f2;
Int_t nlines = 0;
TFile *f = new TFile("fragmentAngularDistribution.root","RECREATE");
TNtuple *ntuple = new TNtuple("ntuple","Data from ascii file","x:y");
Char_t DATAFLAG[4];
Int_t NDATA;
Char_t n1[15], n2[15];
in >> DATAFLAG >> NDATA ; // Read EXFOR line: 'DATA 6'
in >> n1 >> n2; // Read column titles: 'Energy He B [...]'
cout <<n1<<" "<<n2<<"\n";
while (1) {
in >> f1 >> f2;
if (!in.good()) break;
if (nlines < 500 ) printf("%f %f\n",f1,f2);
ntuple->Fill(f1,f2);
nlines++;
}
std::cout << "Imported " << nlines << " lines from data-file" << endl;
TNtuple *simData = new TNtuple("ntuple","Data from ascii file","depth:H:He:Li:Be:B:C");
// gROOT->SetStyle("clearRetro");
//this will be used as base for pulling the experimental data
TString dir = gSystem->UnixPathName(gInterpreter->GetCurrentMacroName());
dir.ReplaceAll("fragmentAngularDistribution.C","");
dir.ReplaceAll("/./","/");
ifstream in;
simData->Fill(0.0,0.0,0.0,0.0,0.0,0.0,1.0);
for(int j = 1; j <= 40;j=j=j+1){
TString pDepth, fragment, Znum, normToOneAtZeroAngle;
pDepth = Form("%i",j);
/*
cout << "Enter phantom depth (eg. 27.9, see experimentalData directory for choices): ";
cin >> pDepth;
*/
TString simulationDataPath = "IAEA_" + pDepth + ".root";
//Let's pull in the simulation-data
//TFile *MCData = TFile::Open("IAEA_" + pDepth + ".root");
TFile *MCData = TFile::Open(simulationDataPath);
TNtuple *fragments = (TNtuple*) MCData->Get("fragmentNtuple");
//Block bellow pulls out the simulation's metadata from the metadata ntuple.
TNtuple *metadata = (TNtuple*) MCData->Get("metaData");
Float_t events, detectorDistance,waterThickness,beamEnergy,energyError,phantomCenterDistance;
metadata->SetBranchAddress("events",&events);
metadata->SetBranchAddress("waterThickness",&waterThickness);
metadata->SetBranchAddress("detectorDistance",&detectorDistance);
metadata->SetBranchAddress("beamEnergy",&beamEnergy);
metadata->SetBranchAddress("energyError",&energyError);
metadata->SetBranchAddress("phantomCenterDistance",&phantomCenterDistance);
metadata->GetEntry(0); //there is just one row to consider.
//ALL UNITS ARE cm!
Double_t scatteringDistance = detectorDistance - phantomCenterDistance; //temporarily hard-coded, should be distance from target-center to detector
Double_t degrees = 10.0;
Double_t r, rMin, rMax, graphMaximum = 0.0;
Double_t norming = events*.999;
TString rMinString;
TString rMaxString;
rMinString = "0.00";
rMaxString = Form("%f", scatteringDistance*TMath::ATan(degrees*TMath::DegToRad()));
Double_t H = ((Double_t*) fragments->GetEntries("(Z == " + TString::Format("%i",1) + " && sqrt(posY^2 + posZ^2) < " + rMaxString + "&& sqrt(posY*posY + posZ*posZ) > " + rMinString + ")")) / norming;
Double_t He = ((Double_t*) fragments->GetEntries("(Z == " + TString::Format("%i",2) + " && sqrt(posY^2 + posZ^2) < " + rMaxString + "&& sqrt(posY*posY + posZ*posZ) > " + rMinString + ")")) / norming;
Double_t Li = ((Double_t*) fragments->GetEntries("(Z == " + TString::Format("%i",3) + " && sqrt(posY^2 + posZ^2) < " + rMaxString + "&& sqrt(posY*posY + posZ*posZ) > " + rMinString + ")")) / norming;
Double_t Be = ((Double_t*) fragments->GetEntries("(Z == " + TString::Format("%i",4) + " && sqrt(posY^2 + posZ^2) < " + rMaxString + "&& sqrt(posY*posY + posZ*posZ) > " + rMinString + ")")) / norming;
Double_t B = ((Double_t*) fragments->GetEntries("(Z == " + TString::Format("%i",5) + " && sqrt(posY^2 + posZ^2) < " + rMaxString + "&& sqrt(posY*posY + posZ*posZ) > " + rMinString + ")")) / norming;
Double_t C = ((Double_t*) fragments->GetEntries("(Z == " + TString::Format("%i",6) + " && sqrt(posY^2 + posZ^2) < " + rMaxString + "&& sqrt(posY*posY + posZ*posZ) > " + rMinString + ")")) / norming;
simData->Fill(waterThickness,H,He,Li,Be,B,C);
}
simData->Scan();
simData->SetMarkerStyle(2); //filled dot
simData->SetMarkerColor(kBlue);
graphMaximum = TMath::Max(graphMaximum, simData->GetMaximum(fragmentName));
graphMaximum = TMath::Max(graphMaximum, ntuple->GetMaximum("y"));
dummyHisto->SetMaximum(graphMaximum + .05*graphMaximum);
dummyHisto->Draw();
simData->Draw(fragmentName + ":depth","","p,same");
ntuple->SetMarkerStyle(22); //triangle
ntuple->SetMarkerColor(kRed);
ntuple->Draw("y:x","","p,same");
c1->SaveAs("fragmentYieldsFor" + fragmentName + ".png");
}