void evtime() {
vector<int> runs;
vector<int> marks;
vector<int> mcols;
runs.push_back(13893);
marks.push_back(2);
mcols.push_back(2);
runs.push_back(14009);
marks.push_back(24);
mcols.push_back(4);
runs.push_back(14085);
marks.push_back(25);
mcols.push_back(3);
runs.push_back(14234);
marks.push_back(5);
mcols.push_back(3);
runs.push_back(14434);
marks.push_back(28);
mcols.push_back(3);
string pre = "run";
string suf = "evt.root";
double tmax = 160;
double emax = 180;
new TCanvas;
TH1* ph = new TH2F("hevtime", "Event vs. time; Time [sec]; Event",
tmax, 0, tmax, emax, 0, emax);
ph->SetStats(0);
ph->Draw("axis");
TLegend* pleg = new TLegend(0.65,0.15,0.85,0.37);
pleg->SetBorderSize(0);
for ( unsigned int isam=0; isam<runs.size(); ++isam ) {
int run = runs[isam];
int icol = dsindex(run);
int col = colormap(icol);
ostringstream ssrun;
ssrun << run;
string srun = ssrun.str();
ostringstream sst0;
sst0 << t0map(run);
string fname = pre + srun + suf;
TFile* pfile = TFile::Open(fname.c_str(), "READ");
TTree* ptree = dynamic_cast<TTree*>(pfile->Get("DXDisplay/EventTree"));
ptree->SetMarkerStyle(marks[isam]);
ptree->SetMarkerColor(col);
cout << run << " " << col << " " << sst0.str() << endl;
if ( ptree == 0 ) {
cout << "Tree not found" << endl;
pfile->ls();
return;
}
string sarg = "event:tlo-";
sarg += sst0.str();
sarg += ">>hevtime";
ptree->Draw(sarg.c_str(), "", "same");
pleg->AddEntry(ptree, srun.c_str(), "p");
}
pleg->Draw();
}
void striptree(TString fileName="", Int_t nAPVs=4)
{
//===========================================================================
// Change the inputs
//===========================================================================
//TString fileName = "Raw_Data_July1_Ped_300V";
//TString fileName = "Raw_Data_July1_Source_300V";
//TString fileName = "Raw_Data_July1_Ped_200V";
//TString fileName = "Raw_Data_Pedestal_300V";
// TString fileName = "Raw_Data_Source_300V";
// TString fileName = "Raw_Data_Sept_3_1";
// TString fileName = "Raw_Data_test_3_7";
// TString fileName = "Raw_Data_Albox_2011_03_31_1";
//-- TString fileName = "Raw_Data_04_01_AL_center_1";
// TString fileName = "Raw_Data_04_01_AL_7820_1";
//-- TString fileName = "Raw_Data_7817_04_01_1";
// TString fileName = "Raw_Data_7817_04_01_bkg_1";
//int nAPVs = 4;
//TString fileName = "Raw_Data_July1_Source_200V";
//int nAPVs = 1;
int nEvents = -1; // -1 means all
TString dat = fileName;
TString eps = fileName + "-events.eps";
TString root = fileName + "-events.root";
TFile* file = new TFile(root, "RECREATE");
//===========================================================================
// Read the data and make a 2D scatter plot
//===========================================================================
ifstream in(dat);
if (!in) {
cout<< "File " << dat << " not found" <<endl;
return;
}
TString comments = "vertical --> APV0, APV1, ... of event 1, ...";
TString s;
while (1) {
s.ReadLine(in);
if (s.BeginsWith(comments))
break;
}
gStyle->SetOptStat(10);
TString title = fileName+" ADC Counts vs Channel";
TString title32 = fileName+" ADC Counts vs Channel for 32 ch";
TH2D *h2d = new TH2D("h2d", title.Data(), nAPVs*128, 0, nAPVs*128, 200, 0, 200);
TH2D *h2d32 = new TH2D("h2d32", title.Data(), 16, 0, 16, 200, 0, 200);
TProfile *profile = new TProfile("profile", title32.Data(), nAPVs*128, 0, nAPVs*128);
int event, apv, channel, adc;
// TTree* tree = new TTree("tree", "tree");
// tree->Branch("event", &event, "event/I");
// tree->Branch("apv", &apv, "apv/I");
// tree->Branch("channel", &channel, "channel/I");
// tree->Branch("adc", &adc, "adc/I");
Int_t raw[512];
TTree* etree = new TTree("etree", "etree");
etree->Branch("raw", &raw, "raw[512]/I"); // etree->Draw("raw:Iteration$","Entry$==0")
etree->SetMarkerStyle(6);
etree->SetMarkerColor(2);
int n = 0;
while (1) {
in >> s;
if (!in.good())
break;
if (s.BeginsWith("]DATA]")) // last line
break;
n++;
if ((nEvents != -1) && (n > nEvents))
break;
event = atoi(s.Data());
if (event%100 == 0)
cout << "Processing event " << event << endl;
for (int i=0; i<2; i++)
in >> s; // time
Int_t ichannel = 0;
for (apv=1; apv<=nAPVs; apv++) {
in >> s; // header + analog APV data + one tick mark
int sequenceNumber = 0;
TString subString = "";
int length = s.Length();
for (int j=0; j<length; j++) {
char c = s[j];
if (c != ',') {
subString += c;
} else {
if (sequenceNumber >= 12) {
channel = sequenceNumber - 12;
adc = atoi(subString.Data());
h2d->Fill((apv - 1) * 128 + channel + 0.5, adc);
h2d32->Fill(((apv - 1) * 128 + channel)/32 + 0.5, adc);
profile->Fill((apv - 1) * 128 + channel + 0.5, adc);
//tree->Fill();
raw[ichannel] = adc;
++ichannel;
}
subString = "";
sequenceNumber++;
}
}
}
etree->Fill();
}
in.close();
TCanvas *canvas = new TCanvas;
canvas->Divide(1,2);
canvas->cd();
canvas->cd(1); h2d->Draw();
canvas->cd(2); profile->Draw();
canvas->SaveAs(eps);
// //-- TFile file(root, "RECREATE");
// h2d->Write();
// profile->Write();
// tree->Write();
// //file.Close();
cout<< "\nWrite " << etree->GetEntries() << " of tree " << etree->GetName() << " into file " << file->GetName() <<endl;
cout<< "To plot strip content use e.g. etree->Draw(\"raw:Iteration$\",\"Entry$==0\")" <<endl;
file->Write();
}
void process()
{
Int_t raw[512]; // buffer for input signal and bkg trees
// buffers for output trees
Int_t sig[512];
Int_t cmsig[512];
Int_t cm[16];
// pedestal
const char* fbkg_name = "Raw_Data_FZ320P_05_MSSD_2_250V_K237_Pedestal.dat-events.root";
TFile* fbkg = TFile::Open(fbkg_name);
if (!fbkg) cout<< "File not found: " << fbkg <<endl<<exitl;
TTree* tree = (TTree*) fbkg->Get("etree");
tree->SetBranchAddress("raw", &raw);
TH2* h2d = (TH2*) fbkg->Get("h2d");
new TCanvas;
h2d->Draw();
TProfile* profile = (TProfile*) fbkg->Get("profile");
//new TCanvas;
//profile->Draw();
Int_t pedestal[512];
for (int i=0; i<512; i++) {
// pedestal[i] = profile->GetBinContent(i+1) - 0.5;
// pedestal[i] = profile->GetBinContent(i+1) + 0.5;
pedestal[i] = profile->GetBinContent(i+1);
}
// cout << "\nPedestals for every channel\n" << endl;
// for (int i=0; i<512; i++) {
// cout << pedestal[i] << " ";
// if (i>0 && (i+1)%128==0)
// cout << endl;
// }
cout<< "processing bkg" <<endl;
// output file with tree
const char* obfname = "FZ320P_05_MSSD_2-bkg.root";
TFile* obfile = TFile::Open(obfname, "recreate");
TTree* btree = new TTree("btree", "btree");
btree->Branch("sig", &sig, "sig[512]/I");
btree->Branch("cmsig", &cmsig, "cmsig[512]/I");
btree->Branch("cm", &cm, "cm[16]/I");
btree->SetMarkerStyle(6);
btree->SetMarkerColor(2);
for (int jentry=0; jentry<tree->GetEntries(); ++jentry)
{
tree->GetEvent(jentry);
// sig
for (int i=0; i<512; ++i) {
sig[i] = raw[i] - pedestal[i];
}
// calc common mode
Int_t group32[32];
Int_t index32[32];
for (int igroup=0; igroup<16; ++igroup) {
for (int istrip=0; istrip<32; ++istrip) // istrip is number inside group of 32
{
group32[istrip] = sig[igroup*32 + istrip];
}
// sort array group32 in ascending order
TMath::Sort(32, group32, index32, kFALSE);
Int_t median = group32[index32[14]];
cm[igroup] = median;
}
// subtract common mode
for (int istrip=0; istrip<512; ++istrip) {
Int_t igroup = istrip/32;
cmsig[istrip] = sig[istrip] - cm[igroup];
}
// Fill sig, cmsig, cm
btree->Fill();
}
obfile->Write();
/////////////////////////////////////////////////
//
// signal tree
//
/////////////////////////////////////////////////
cout<< "processing signal" <<endl;
TChain* chain = new TChain("etree");
chain->Add("Raw_Data_FZ320P_05_MSSD_250V_K237_Position_1.dat-events.root");
chain->Add("Raw_Data_FZ320P_05_MSSD_250V_K237_Position_2.dat-events.root");
chain->Add("Raw_Data_FZ320P_05_MSSD_2_250V_K237_Position_3.dat-events.root");
chain->Add("Raw_Data_FZ320P_05_MSSD_2_250V_K237_Position_4.dat-events.root");
chain->SetBranchAddress("raw", &raw);
// output file with tree
const char* osfname = "FZ320P_05_MSSD_2-signal.root";
TFile* osfile = TFile::Open(osfname, "recreate");
TTree* stree = new TTree("stree", "stree");
stree->Branch("sig", &sig, "sig[512]/I");
stree->Branch("cmsig", &cmsig, "cmsig[512]/I");
stree->Branch("cm", &cm, "cm[16]/I");
stree->SetMarkerStyle(6);
stree->SetMarkerColor(2);
for (int jentry=0; jentry<chain->GetEntries(); ++jentry)
{
chain->GetEvent(jentry);
// sig
for (int i=0; i<512; ++i) {
sig[i] = raw[i] - pedestal[i];
}
// calc common mode
Int_t group32[32];
Int_t index32[32];
for (int igroup=0; igroup<16; ++igroup) {
for (int istrip=0; istrip<32; ++istrip) // istrip is number inside group of 32
{
group32[istrip] = sig[igroup*32 + istrip];
}
// sort array group32 in ascending order
TMath::Sort(32, group32, index32, kFALSE);
Int_t median = group32[index32[14]];
cm[igroup] = median;
}
// subtract common mode
for (int istrip=0; istrip<512; ++istrip) {
Int_t igroup = istrip/32;
cmsig[istrip] = sig[istrip] - cm[igroup];
}
// Fill sig, cmsig, cm
stree->Fill();
}
osfile->Write();
////////////////////////////////////////////////////////
//
// process trees
//
///////////////////////////////////////////////////////
cout<< "results" <<endl;
Double_t a, mean, sigma;
TH1F* h_sigma_bkg = new TH1F("h_sigma_bkg","CM subtr. noise for groups", 16,0,16);
TH1F* h_mean_sig = new TH1F("h_mean_sig","CM subtr. signal for groups", 16,0,16);
TH1F* h_SN = new TH1F("h_SN","Signal to Noise Ratio for groups", 16,0,16);
new TCanvas;
btree->Draw("cmsig","Iteration$>=0&&Iteration$<32");
fitgr(0,0, "Q", "goff", btree->GetHistogram());
pargaus(a,mean,sigma,"htemp");
//cout<< "mean = " << mean << " sigma = " << sigma <<endl;
//-- png("FZ320P_05_MSSD_2-bkg-ex");
new TCanvas;
// for (int igroup=0; igroup<16; ++igroup) {
for (int igroup=0; igroup<15; ++igroup) {
Int_t ch1 = igroup*32;
Int_t ch2 = (igroup+1)*32;
btree->Draw("cmsig",Form("Iteration$>=%d&&Iteration$<%d",ch1,ch2),"");
fitgr(0,0, "", "", btree->GetHistogram());
pargaus(a,mean,sigma,"htemp");
// h_sigma_bkg->Fill(igroup, sigma);
h_sigma_bkg->SetBinContent(igroup+1, sigma);
}
new TCanvas;
h_sigma_bkg->Draw();
//-- png("FZ320P_05_MSSD_2-bkg-allgroups");
// signal
new TCanvas;
stree->Draw("cmsig","cmsig>8 &&Iteration$>=0&&Iteration$<32");
//-- png("FZ320P_05_MSSD_2-sig-ex");
new TCanvas;
// for (int igroup=0; igroup<16; ++igroup) {
for (int igroup=0; igroup<15; ++igroup) {
Int_t ch1 = igroup*32;
Int_t ch2 = (igroup+1)*32;
stree->Draw("cmsig",Form("cmsig>8 &&Iteration$>=%d&&Iteration$<%d",ch1,ch2),"");
gPad->Update();
gPad->Modified();
mean = stree->GetHistogram()->GetMean();
h_mean_sig->SetBinContent(igroup+1, mean);
}
new TCanvas;
h_mean_sig->Draw();
//-- png("FZ320P_05_MSSD_2-signal-allgroups");
for (int igroup=0; igroup<16; ++igroup) {
Double_t signal32 = h_mean_sig->GetBinContent(igroup+1);
Double_t noise32 = h_sigma_bkg->GetBinContent(igroup+1);
Double_t snr = 0;
if (noise32 > 0) snr = signal32 / noise32;
h_SN->SetBinContent(igroup+1, snr);
}
new TCanvas;
h_SN->Draw();
//-- png("FZ320P_05_MSSD_2-SN-allgroups");
}
void pulseConvert(const char* ifname)
{
TFile* ifile = TFile::Open(ifname);
if (!ifile) {
cout<< "File not found: " << ifname <<endl;
return;
}
TTree* itree = (TTree*) ifile->Get("pulse");
if (!itree) {
cout<< "Error: could not find tree \"pulse\"" <<endl;
return;
}
Int_t event, tc1, tc2;
Float_t b1_t[1024], b1_c[4096], b2_t[1024], b2_c[4096];
Float_t* b1_c1 = b1_c;
Float_t* b1_c2 = b1_c + 1024;
Float_t* b1_c3 = b1_c + 2048;
Float_t* b1_c4 = b1_c + 3072;
Float_t* b2_c1 = b2_c;
Float_t* b2_c2 = b2_c + 1024;
Float_t* b2_c3 = b2_c + 2048;
Float_t* b2_c4 = b2_c + 3072;
itree->SetBranchAddress("event", &event);
itree->SetBranchAddress("tc1", &tc1);
itree->SetBranchAddress("tc2", &tc2);
itree->SetBranchAddress("b1_t", &b1_t);
itree->SetBranchAddress("b2_t", &b2_t);
itree->SetBranchAddress("b1_c", &b1_c);
itree->SetBranchAddress("b2_c", &b2_c);
TFile* ofile = TFile::Open(Form("%s.pulse.root",ifname), "recreate");
// TTree* otree = new TTree("pulse", "old pulse tree");
TTree* otree = new TTree("p", "new pulse tree");
otree->SetMarkerStyle(6);
otree->SetMarkerColor(2);
otree->SetLineColor(2);
// otree->Branch("event", &event, "event/I");
// otree->Branch("tc1", &tc1, "tc1/I");
// otree->Branch("b1_t", b1_t, "b1_t[1024]/F");
// otree->Branch("b1_c1", b1_c1, "b1_c1[1024]/F");
// otree->Branch("b1_c2", b1_c2, "b1_c2[1024]/F");
// otree->Branch("b1_c3", b1_c3, "b1_c3[1024]/F");
// otree->Branch("b1_c4", b1_c4, "b1_c4[1024]/F");
// otree->Branch("tc2", &tc2, "tc2/I");
// otree->Branch("b2_t", b2_t, "b2_t[1024]/F");
// otree->Branch("b2_c1", b2_c1, "b2_c1[1024]/F");
// otree->Branch("b2_c2", b2_c2, "b2_c2[1024]/F");
// otree->Branch("b2_c3", b2_c3, "b2_c3[1024]/F");
// otree->Branch("b2_c4", b2_c4, "b2_c4[1024]/F");
otree->Branch("event", &event, "event/I");
otree->Branch("tc1", &tc1, "tc1/I");
otree->Branch("t1", b1_t, "t1[1024]/F");
otree->Branch("c1", b1_c1, "c1[1024]/F");
otree->Branch("c2", b1_c2, "c2[1024]/F");
otree->Branch("c3", b1_c3, "c3[1024]/F");
otree->Branch("c4", b1_c4, "c4[1024]/F");
otree->Branch("tc2", &tc2, "tc2/I");
otree->Branch("t2", b2_t, "t2[1024]/F");
otree->Branch("c5", b2_c1, "c5[1024]/F");
otree->Branch("c6", b2_c2, "c6[1024]/F");
otree->Branch("c7", b2_c3, "c7[1024]/F");
otree->Branch("c8", b2_c4, "c8[1024]/F");
for (Long64_t jentry=0; jentry<itree->GetEntries(); jentry++)
{
if (jentry % 1000 == 0) cout<< "jentry = " << jentry <<endl;
itree->LoadTree(jentry);
itree->GetEntry(jentry);
otree->Fill();
}
cout<< "Write " << otree->GetEntries() << " events into file " << ofile->GetName() <<endl;
ofile->Write();
}
void csv(TString input="tmva.csvoutput.txt", TString par1="par2", TString par2="par3", TString par3="", TString value="eventEffScaled_5") {
std::cout << "Usage:" << std::endl
<< ".x scripts/csv.C with default arguments" << std::endl
<< ".x scripts/csv.C(filename, par1, par2, value)" << std::endl
<< std::endl
<< " Optional arguments:" << std::endl
<< " filename path to CSV file" << std::endl
<< " par1 name of X-parameter branch" << std::endl
<< " par2 name of Y-parameter branch (if empty, efficiency is drawn as a function of par1)" << std::endl
<< " value name of result (efficiency) branch" << std::endl
<< std::endl;
TTree *tree = new TTree("data", "data");
tree->ReadFile(input);
gStyle->SetPalette(1);
gStyle->SetPadRightMargin(0.14);
TCanvas *canvas = new TCanvas("csvoutput", "CSV Output", 1200, 900);
tree->SetMarkerStyle(kFullDotMedium);
tree->SetMarkerColor(kRed);
if(par2.Length() > 0) {
//tree->Draw(Form("%s:%s", par2.Data(), par1.Data()));
if(par3.Length() > 0)
tree->Draw(Form("%s:%s:%s:%s", par1.Data(), par2.Data(), par3.Data(), value.Data()), "", "COLZ"); //, "", "Z");
else
tree->Draw(Form("%s:%s:%s", par2.Data(), par1.Data(), value.Data()), "", "COLZ"); //, "", "Z");
TH1 *histo = tree->GetHistogram();
if(!histo)
return;
histo->SetTitle(Form("%s with different classifier parameters", value.Data()));
histo->GetXaxis()->SetTitle(Form("Classifier parameter %s", par1.Data()));
histo->GetYaxis()->SetTitle(Form("Classifier parameter %s", par2.Data()));
if(par3.Length() > 0)
histo->GetZaxis()->SetTitle(Form("Classifier parameter %s", par3.Data()));
else
histo->GetZaxis()->SetTitle("");
if(par3.Length() == 0) {
float x = 0;
float y = 0;
float val = 0;
double maxVal = tree->GetMaximum(value);
double minVal = tree->GetMinimum(value);
tree->SetBranchAddress(par1, &x);
tree->SetBranchAddress(par2, &y);
tree->SetBranchAddress(value, &val);
TLatex l;
l.SetTextSize(0.03);
Long64_t nentries = tree->GetEntries();
for(Long64_t entry=0; entry < nentries; ++entry) {
tree->GetEntry(entry);
l.SetTextColor(textColor(val, maxVal, minVal));
l.DrawLatex(x, y, Form("%.3f", val*100));
}
}
}
else {
tree->Draw(Form("%s:%s", value.Data(), par1.Data()));
TH1 *histo = tree->GetHistogram();
if(!histo)
return;
histo->SetTitle(Form("%s with different classifier parameters", value.Data()));
histo->GetXaxis()->SetTitle(Form("Classifier parameter %s", par1.Data()));
histo->GetYaxis()->SetTitle(value);
}
}
void rs101_limitexample()
{
// --------------------------------------
// An example of setting a limit in a number counting experiment with uncertainty on background and signal
// to time the macro
TStopwatch t;
t.Start();
// --------------------------------------
// The Model building stage
// --------------------------------------
RooWorkspace* wspace = new RooWorkspace();
wspace->factory("Poisson::countingModel(obs[150,0,300], sum(s[50,0,120]*ratioSigEff[1.,0,3.],b[100]*ratioBkgEff[1.,0.,3.]))"); // counting model
// wspace->factory("Gaussian::sigConstraint(ratioSigEff,1,0.05)"); // 5% signal efficiency uncertainty
// wspace->factory("Gaussian::bkgConstraint(ratioBkgEff,1,0.1)"); // 10% background efficiency uncertainty
wspace->factory("Gaussian::sigConstraint(gSigEff[1,0,3],ratioSigEff,0.05)"); // 5% signal efficiency uncertainty
wspace->factory("Gaussian::bkgConstraint(gSigBkg[1,0,3],ratioBkgEff,0.2)"); // 10% background efficiency uncertainty
wspace->factory("PROD::modelWithConstraints(countingModel,sigConstraint,bkgConstraint)"); // product of terms
wspace->Print();
RooAbsPdf* modelWithConstraints = wspace->pdf("modelWithConstraints"); // get the model
RooRealVar* obs = wspace->var("obs"); // get the observable
RooRealVar* s = wspace->var("s"); // get the signal we care about
RooRealVar* b = wspace->var("b"); // get the background and set it to a constant. Uncertainty included in ratioBkgEff
b->setConstant();
RooRealVar* ratioSigEff = wspace->var("ratioSigEff"); // get uncertain parameter to constrain
RooRealVar* ratioBkgEff = wspace->var("ratioBkgEff"); // get uncertain parameter to constrain
RooArgSet constrainedParams(*ratioSigEff, *ratioBkgEff); // need to constrain these in the fit (should change default behavior)
RooRealVar * gSigEff = wspace->var("gSigEff"); // global observables for signal efficiency
RooRealVar * gSigBkg = wspace->var("gSigBkg"); // global obs for background efficiency
gSigEff->setConstant();
gSigBkg->setConstant();
// Create an example dataset with 160 observed events
obs->setVal(160.);
RooDataSet* data = new RooDataSet("exampleData", "exampleData", RooArgSet(*obs));
data->add(*obs);
RooArgSet all(*s, *ratioBkgEff, *ratioSigEff);
// not necessary
modelWithConstraints->fitTo(*data, RooFit::Constrain(RooArgSet(*ratioSigEff, *ratioBkgEff)));
// Now let's make some confidence intervals for s, our parameter of interest
RooArgSet paramOfInterest(*s);
ModelConfig modelConfig(wspace);
modelConfig.SetPdf(*modelWithConstraints);
modelConfig.SetParametersOfInterest(paramOfInterest);
modelConfig.SetNuisanceParameters(constrainedParams);
modelConfig.SetObservables(*obs);
modelConfig.SetGlobalObservables( RooArgSet(*gSigEff,*gSigBkg));
modelConfig.SetName("ModelConfig");
wspace->import(modelConfig);
wspace->import(*data);
wspace->SetName("w");
wspace->writeToFile("rs101_ws.root");
// First, let's use a Calculator based on the Profile Likelihood Ratio
//ProfileLikelihoodCalculator plc(*data, *modelWithConstraints, paramOfInterest);
ProfileLikelihoodCalculator plc(*data, modelConfig);
plc.SetTestSize(.05);
ConfInterval* lrinterval = plc.GetInterval(); // that was easy.
// Let's make a plot
TCanvas* dataCanvas = new TCanvas("dataCanvas");
dataCanvas->Divide(2,1);
dataCanvas->cd(1);
LikelihoodIntervalPlot plotInt((LikelihoodInterval*)lrinterval);
plotInt.SetTitle("Profile Likelihood Ratio and Posterior for S");
plotInt.Draw();
// Second, use a Calculator based on the Feldman Cousins technique
FeldmanCousins fc(*data, modelConfig);
fc.UseAdaptiveSampling(true);
fc.FluctuateNumDataEntries(false); // number counting analysis: dataset always has 1 entry with N events observed
fc.SetNBins(100); // number of points to test per parameter
fc.SetTestSize(.05);
// fc.SaveBeltToFile(true); // optional
ConfInterval* fcint = NULL;
fcint = fc.GetInterval(); // that was easy.
RooFitResult* fit = modelWithConstraints->fitTo(*data, Save(true));
// Third, use a Calculator based on Markov Chain monte carlo
// Before configuring the calculator, let's make a ProposalFunction
// that will achieve a high acceptance rate
ProposalHelper ph;
ph.SetVariables((RooArgSet&)fit->floatParsFinal());
ph.SetCovMatrix(fit->covarianceMatrix());
ph.SetUpdateProposalParameters(true);
ph.SetCacheSize(100);
ProposalFunction* pdfProp = ph.GetProposalFunction(); // that was easy
MCMCCalculator mc(*data, modelConfig);
mc.SetNumIters(20000); // steps to propose in the chain
mc.SetTestSize(.05); // 95% CL
mc.SetNumBurnInSteps(40); // ignore first N steps in chain as "burn in"
mc.SetProposalFunction(*pdfProp);
mc.SetLeftSideTailFraction(0.5); // find a "central" interval
MCMCInterval* mcInt = (MCMCInterval*)mc.GetInterval(); // that was easy
// Get Lower and Upper limits from Profile Calculator
cout << "Profile lower limit on s = " << ((LikelihoodInterval*) lrinterval)->LowerLimit(*s) << endl;
cout << "Profile upper limit on s = " << ((LikelihoodInterval*) lrinterval)->UpperLimit(*s) << endl;
// Get Lower and Upper limits from FeldmanCousins with profile construction
if (fcint != NULL) {
double fcul = ((PointSetInterval*) fcint)->UpperLimit(*s);
double fcll = ((PointSetInterval*) fcint)->LowerLimit(*s);
cout << "FC lower limit on s = " << fcll << endl;
cout << "FC upper limit on s = " << fcul << endl;
TLine* fcllLine = new TLine(fcll, 0, fcll, 1);
TLine* fculLine = new TLine(fcul, 0, fcul, 1);
fcllLine->SetLineColor(kRed);
fculLine->SetLineColor(kRed);
fcllLine->Draw("same");
fculLine->Draw("same");
dataCanvas->Update();
}
// Plot MCMC interval and print some statistics
MCMCIntervalPlot mcPlot(*mcInt);
mcPlot.SetLineColor(kMagenta);
mcPlot.SetLineWidth(2);
mcPlot.Draw("same");
double mcul = mcInt->UpperLimit(*s);
double mcll = mcInt->LowerLimit(*s);
cout << "MCMC lower limit on s = " << mcll << endl;
cout << "MCMC upper limit on s = " << mcul << endl;
cout << "MCMC Actual confidence level: "
<< mcInt->GetActualConfidenceLevel() << endl;
// 3-d plot of the parameter points
dataCanvas->cd(2);
// also plot the points in the markov chain
RooDataSet * chainData = mcInt->GetChainAsDataSet();
assert(chainData);
std::cout << "plotting the chain data - nentries = " << chainData->numEntries() << std::endl;
TTree* chain = RooStats::GetAsTTree("chainTreeData","chainTreeData",*chainData);
assert(chain);
chain->SetMarkerStyle(6);
chain->SetMarkerColor(kRed);
chain->Draw("s:ratioSigEff:ratioBkgEff","nll_MarkovChain_local_","box"); // 3-d box proportional to posterior
// the points used in the profile construction
RooDataSet * parScanData = (RooDataSet*) fc.GetPointsToScan();
assert(parScanData);
std::cout << "plotting the scanned points used in the frequentist construction - npoints = " << parScanData->numEntries() << std::endl;
// getting the tree and drawing it -crashes (very strange....);
// TTree* parameterScan = RooStats::GetAsTTree("parScanTreeData","parScanTreeData",*parScanData);
// assert(parameterScan);
// parameterScan->Draw("s:ratioSigEff:ratioBkgEff","","goff");
TGraph2D *gr = new TGraph2D(parScanData->numEntries());
for (int ievt = 0; ievt < parScanData->numEntries(); ++ievt) {
const RooArgSet * evt = parScanData->get(ievt);
double x = evt->getRealValue("ratioBkgEff");
double y = evt->getRealValue("ratioSigEff");
double z = evt->getRealValue("s");
gr->SetPoint(ievt, x,y,z);
// std::cout << ievt << " " << x << " " << y << " " << z << std::endl;
}
gr->SetMarkerStyle(24);
gr->Draw("P SAME");
delete wspace;
delete lrinterval;
delete mcInt;
delete fcint;
delete data;
// print timing info
t.Stop();
t.Print();
}
