readExclusion() {
TFile * file = new TFile("theExclusion_M115_EGMLOOSE006.root");
HypoTestInverterResult * r = dynamic_cast<HypoTestInverterResult*>( file->Get("result_r") );
double upperLimit = r->UpperLimit();
double ulError = r->UpperLimitEstimatedError();
std::cout << "The computed upper limit is: " << upperLimit << " +/- " << ulError << std::endl;
const int nEntries = r->ArraySize();
TCanvas *c0 = new TCanvas("c0","coucou",600,600);
c0->SetFillColor(0);
TString plotTitle = "CL Scan for workspace";
HypoTestInverterPlot *plot = new HypoTestInverterPlot("HTI_Result_Plot",plotTitle,r);
plot->Draw("CLb 2CL"); // plot all and Clb
c0->Print("limit_plot.gif");
const int nEntries = r->ArraySize();
cout << "N entries = " << nEntries << endl;
TCanvas * c2 = new TCanvas();
c2->Divide( 2, TMath::Ceil(nEntries/2));
for (int i=0; i<nEntries; i++) {
c2->cd(i+1);
SamplingDistPlot * pl = plot->MakeTestStatPlot(i);
pl->SetLogYaxis(true);
pl->Draw();
}
}
readExclusion_M130(){
TString massPointString = IntToString(massPoint);
TFile * file = new TFile("theExclusion_M"+massPointString+"_"+nomPlot+".root");
HypoTestInverterResult * r = dynamic_cast<HypoTestInverterResult*>( file->Get("result_r") );
double upperLimit = r->UpperLimit();
double ulError = r->UpperLimitEstimatedError();
std::cout << "The computed upper limit is: " << upperLimit << " +/- " << ulError << std::endl;
const int nEntries = r->ArraySize();
TCanvas *c0 = new TCanvas("c0","coucou",600,600);
c0->SetFillColor(0);
TString plotTitle = "CL Scan for workspace";
HypoTestInverterPlot *plot = new HypoTestInverterPlot("HTI_Result_Plot",plotTitle,r);
plot->Draw("CLb 2CL");//("CLb 2CL"); // plot all and Clb
c0->Print("limit_plot_M"+massPointString+".gif");
const int nEntries = r->ArraySize();
cout << "N entries = " << nEntries << endl;
TCanvas * c2 = new TCanvas();
c2->Divide( 2, TMath::Ceil(nEntries/2));
for (int i=0; i<nEntries; i++) {
c2->cd(i+1);
SamplingDistPlot * pl = plot->MakeTestStatPlot(i);
pl->SetLogYaxis(true);
pl->Draw();
}
std::cout << "The computed upper limit is: " << upperLimit << " +/- " << ulError << std::endl;
std::cout << "The expected limi is : " << r->GetExpectedUpperLimit(0) << endl;
float expected = r->GetExpectedUpperLimit(0);
float observed = r->UpperLimit();
float observedError = r->UpperLimitEstimatedError();
float expected1sP = r->GetExpectedUpperLimit(1);
float expected2sP = r->GetExpectedUpperLimit(2);
float expected1sM = r->GetExpectedUpperLimit(-1);
float expected2sM = r->GetExpectedUpperLimit(-2);
cout << "ZZZZ graph->SetPoint(" <<number << "," << massPoint<< "," << expected << ");" << endl;
cout << "ZZZZ grae->SetPoint(" <<number << "," << massPoint<< "," << expected << ");" << endl;
cout << "ZZZZ grae->SetPointError(" << number << ",0,0," << (expected-expected1sM) << "," << (expected1sP-expected) << ");" << endl;
cout << "ZZZZ grae2->SetPoint(" <<number << "," << massPoint<< "," << expected << ");" << endl;
cout << "ZZZZ grae2->SetPointError(" << number << ",0,0," << (expected-expected2sM) << "," << (expected2sP-expected) << ");" << endl;
cout << "ZZZZ gre->SetPoint(" <<number << "," << massPoint<< "," << observed << ");" << endl;
cout << "ZZZZ gre->SetPointError(" <<number << ",0," << observedError <<");" << endl;
}
void
RooStats::HypoTestInvTool::AnalyzeResult( HypoTestInverterResult * r,
int calculatorType,
int testStatType,
bool useCLs,
int npoints,
const char * fileNameBase ){
// analyze result produced by the inverter, optionally save it in a file
double lowerLimit = 0;
double llError = 0;
#if defined ROOT_SVN_VERSION && ROOT_SVN_VERSION >= 44126
if (r->IsTwoSided()) {
lowerLimit = r->LowerLimit();
llError = r->LowerLimitEstimatedError();
}
#else
lowerLimit = r->LowerLimit();
llError = r->LowerLimitEstimatedError();
#endif
double upperLimit = r->UpperLimit();
double ulError = r->UpperLimitEstimatedError();
//std::cout << "DEBUG : [ " << lowerLimit << " , " << upperLimit << " ] " << std::endl;
if (lowerLimit < upperLimit*(1.- 1.E-4) && lowerLimit != 0)
std::cout << "The computed lower limit is: " << lowerLimit << " +/- " << llError << std::endl;
std::cout << "The computed upper limit is: " << upperLimit << " +/- " << ulError << std::endl;
// compute expected limit
std::cout << "Expected upper limits, using the B (alternate) model : " << std::endl;
std::cout << " expected limit (median) " << r->GetExpectedUpperLimit(0) << std::endl;
std::cout << " expected limit (-1 sig) " << r->GetExpectedUpperLimit(-1) << std::endl;
std::cout << " expected limit (+1 sig) " << r->GetExpectedUpperLimit(1) << std::endl;
std::cout << " expected limit (-2 sig) " << r->GetExpectedUpperLimit(-2) << std::endl;
std::cout << " expected limit (+2 sig) " << r->GetExpectedUpperLimit(2) << std::endl;
printf("\n\n owen: (-2s,-1s,m,1s,2s) %5.2f %5.2f %5.2f %5.2f %5.2f\n\n",
r->GetExpectedUpperLimit(-2),
r->GetExpectedUpperLimit(-1),
r->GetExpectedUpperLimit(0),
r->GetExpectedUpperLimit(1),
r->GetExpectedUpperLimit(2) ) ;
// write result in a file
if (r != NULL && mWriteResult) {
// write to a file the results
const char * calcType = (calculatorType == 0) ? "Freq" : (calculatorType == 1) ? "Hybr" : "Asym";
const char * limitType = (useCLs) ? "CLs" : "Cls+b";
const char * scanType = (npoints < 0) ? "auto" : "grid";
if (mResultFileName.IsNull()) {
mResultFileName = TString::Format("%s_%s_%s_ts%d_",calcType,limitType,scanType,testStatType);
//strip the / from the filename
if (mMassValue.size()>0) {
mResultFileName += mMassValue.c_str();
mResultFileName += "_";
}
TString name = fileNameBase;
name.Replace(0, name.Last('/')+1, "");
mResultFileName += name;
}
TFile * fileOut = new TFile(mResultFileName,"RECREATE");
r->Write();
fileOut->Close();
}
// plot the result ( p values vs scan points)
std::string typeName = "";
if (calculatorType == 0 )
typeName = "Frequentist";
if (calculatorType == 1 )
typeName = "Hybrid";
else if (calculatorType == 2 || calculatorType == 3) {
typeName = "Asymptotic";
mPlotHypoTestResult = false;
}
const char * resultName = r->GetName();
TString plotTitle = TString::Format("%s CL Scan for workspace %s",typeName.c_str(),resultName);
HypoTestInverterPlot *plot = new HypoTestInverterPlot("HTI_Result_Plot",plotTitle,r);
// plot in a new canvas with style
TString c1Name = TString::Format("%s_Scan",typeName.c_str());
TCanvas * c1 = new TCanvas(c1Name);
c1->SetLogy(false);
plot->Draw("CLb 2CL"); // plot all and Clb
// if (useCLs)
// plot->Draw("CLb 2CL"); // plot all and Clb
// else
// plot->Draw(""); // plot all and Clb
const int nEntries = r->ArraySize();
// plot test statistics distributions for the two hypothesis
if (mPlotHypoTestResult) {
TCanvas * c2 = new TCanvas();
if (nEntries > 1) {
int ny = TMath::CeilNint(TMath::Sqrt(nEntries));
int nx = TMath::CeilNint(double(nEntries)/ny);
c2->Divide( nx,ny);
}
for (int i=0; i<nEntries; i++) {
if (nEntries > 1) c2->cd(i+1);
SamplingDistPlot * pl = plot->MakeTestStatPlot(i);
pl->SetLogYaxis(true);
pl->Draw();
}
}
}
void RA2bHypoTestInvDemo(const char * fileName =0,
const char * wsName = "combined",
const char * modelSBName = "ModelConfig",
const char * modelBName = "",
const char * dataName = "obsData",
int calculatorType = 0,
int testStatType = 3,
bool useCls = true ,
int npoints = 5,
double poimin = 0,
double poimax = 5,
int ntoys=1000,
int mgl = -1,
int mlsp = -1,
const char * outFileName = "test")
{
/*
Other Parameter to pass in tutorial
apart from standard for filename, ws, modelconfig and data
type = 0 Freq calculator
type = 1 Hybrid
testStatType = 0 LEP
= 1 Tevatron
= 2 Profile Likelihood
= 3 Profile Likelihood one sided (i.e. = 0 if mu < mu_hat)
useCLs scan for CLs (otherwise for CLs+b)
npoints: number of points to scan , for autoscan set npoints = -1
poimin,poimax: min/max value to scan in case of fixed scans
(if min >= max, try to find automatically)
ntoys: number of toys to use
extra options are available as global paramters of the macro. They are:
plotHypoTestResult plot result of tests at each point (TS distributions)
useProof = true;
writeResult = true;
nworkers = 4;
*/
if (fileName==0) {
fileName = "results/example_combined_GaussExample_model.root";
std::cout << "Use standard file generated with HistFactory :" << fileName << std::endl;
}
TFile * file = new TFile(fileName);
RooWorkspace * w = dynamic_cast<RooWorkspace*>( file->Get(wsName) );
HypoTestInverterResult * r = 0;
std::cout << w << "\t" << fileName << std::endl;
if (w != NULL) {
r = RunInverter(w, modelSBName, modelBName, dataName, calculatorType, testStatType, npoints, poimin, poimax, ntoys, useCls );
if (!r) {
std::cerr << "Error running the HypoTestInverter - Exit " << std::endl;
return;
}
}
else
{
// case workspace is not present look for the inverter result
std::cout << "Reading an HypoTestInverterResult with name " << wsName << " from file " << fileName << std::endl;
r = dynamic_cast<HypoTestInverterResult*>( file->Get(wsName) ); //
if (!r) {
std::cerr << "File " << fileName << " does not contain a workspace or an HypoTestInverterResult - Exit "
<< std::endl;
file->ls();
return;
}
}
printf("\n\n") ;
HypoTestResult* htr = r->GetResult(0) ;
printf(" Data value for test stat : %7.3f\n", htr->GetTestStatisticData() ) ;
printf(" CLsplusb : %9.4f\n", r->CLsplusb(0) ) ;
printf(" CLb : %9.4f\n", r->CLb(0) ) ;
printf(" CLs : %9.4f\n", r->CLs(0) ) ;
printf("\n\n") ;
cout << flush ;
double upperLimit = r->UpperLimit();
double ulError = r->UpperLimitEstimatedError();
std::cout << "The computed upper limit is: " << upperLimit << " +/- " << ulError << std::endl;
const int nEntries = r->ArraySize();
const char * typeName = (calculatorType == 0) ? "Frequentist" : "Hybrid";
const char * resultName = (w) ? w->GetName() : r->GetName();
TString plotTitle = TString::Format("%s CL Scan for workspace %s",typeName,resultName);
HypoTestInverterPlot *plot = new HypoTestInverterPlot("HTI_Result_Plot",plotTitle,r);
TCanvas* c1 = new TCanvas() ;
plot->Draw("CLb 2CL"); // plot all and Clb
c1->Update() ;
c1->SaveAs("cls-canv1.png") ;
c1->SaveAs("cls-canv1.pdf") ;
if (plotHypoTestResult) {
TCanvas * c2 = new TCanvas();
c2->Divide( 2, TMath::Ceil(nEntries/2));
for (int i=0; i<nEntries; i++) {
c2->cd(i+1);
SamplingDistPlot * pl = plot->MakeTestStatPlot(i);
pl->SetLogYaxis(true);
pl->Draw();
}
c2->Update() ;
c2->SaveAs("cls-canv2.png") ;
c2->SaveAs("cls-canv2.pdf") ;
}
std::cout << " expected limit (median) " << r->GetExpectedUpperLimit(0) << std::endl;
std::cout << " expected limit (-1 sig) " << r->GetExpectedUpperLimit(-1) << std::endl;
std::cout << " expected limit (+1 sig) " << r->GetExpectedUpperLimit(1) << std::endl;
// save 2d histograms bin to file
TH2F *result = new TH2F("result","result",22,100,1200,23,50,1200);
TH2F *exp_res = new TH2F("exp_res","exp_res",22,100,1200,23,50,1200);
TH2F *exp_res_minus = new TH2F("exp_res_minus","exp_res_minus",22,100,1200,23,50,1200);
TH2F *exp_res_plus = new TH2F("exp_res_plus","exp_res_plus",22,100,1200,23,50,1200);
result->Fill(mgl,mlsp,upperLimit);
exp_res->Fill(mgl,mlsp,r->GetExpectedUpperLimit(0));
exp_res_minus->Fill(mgl,mlsp,r->GetExpectedUpperLimit(-1));
exp_res_plus->Fill(mgl,mlsp,r->GetExpectedUpperLimit(1));
TFile *f = new TFile(outFileName,"RECREATE");
f->cd();
result->Write();
exp_res->Write();
exp_res_minus->Write();
exp_res_plus->Write();
f->Close();
if (w != NULL && writeResult) {
// write to a file the results
const char * calcType = (calculatorType == 0) ? "Freq" : "Hybr";
const char * limitType = (useCls) ? "CLs" : "Cls+b";
const char * scanType = (npoints < 0) ? "auto" : "grid";
TString resultFileName = TString::Format("%s_%s_%s_ts%d_",calcType,limitType,scanType,testStatType);
resultFileName += fileName;
TFile * fileOut = new TFile(resultFileName,"RECREATE");
r->Write();
fileOut->Close();
}
}
void
RooStats::HypoTestInvTool::AnalyzeResult( HypoTestInverterResult * r,
int calculatorType,
int testStatType,
bool useCLs,
int npoints,
const char * fileNameBase ){
// analyize result produced by the inverter, optionally save it in a file
double upperLimit = r->UpperLimit();
double ulError = r->UpperLimitEstimatedError();
std::cout << "The computed upper limit is: " << upperLimit << " +/- " << ulError << std::endl;
// compute expected limit
std::cout << " expected limit (median) " << r->GetExpectedUpperLimit(0) << std::endl;
std::cout << " expected limit (-1 sig) " << r->GetExpectedUpperLimit(-1) << std::endl;
std::cout << " expected limit (+1 sig) " << r->GetExpectedUpperLimit(1) << std::endl;
std::cout << " expected limit (-2 sig) " << r->GetExpectedUpperLimit(-2) << std::endl;
std::cout << " expected limit (+2 sig) " << r->GetExpectedUpperLimit(2) << std::endl;
// write result in a file
if (r != NULL && mWriteResult) {
// write to a file the results
const char * calcType = (calculatorType == 0) ? "Freq" : (calculatorType == 1) ? "Hybr" : "Asym";
const char * limitType = (useCLs) ? "CLs" : "Cls+b";
const char * scanType = (npoints < 0) ? "auto" : "grid";
TString resultFileName = TString::Format("%s_%s_%s_ts%d_",calcType,limitType,scanType,testStatType);
//strip the / from the filename
if (mMassValue.size()>0) {
resultFileName += mMassValue.c_str();
resultFileName += "_";
}
TString name = fileNameBase;
name.Replace(0, name.Last('/')+1, "");
resultFileName += name;
TFile * fileOut = new TFile(resultFileName,"RECREATE");
r->Write();
fileOut->Close();
}
// plot the result ( p values vs scan points)
std::string typeName = "";
if (calculatorType == 0 )
typeName = "Frequentist";
if (calculatorType == 1 )
typeName = "Hybrid";
else if (calculatorType == 2 ) {
typeName = "Asymptotic";
mPlotHypoTestResult = false;
}
const char * resultName = r->GetName();
TString plotTitle = TString::Format("%s CL Scan for workspace %s",typeName.c_str(),resultName);
HypoTestInverterPlot *plot = new HypoTestInverterPlot("HTI_Result_Plot",plotTitle,r);
plot->Draw("CLb 2CL"); // plot all and Clb
const int nEntries = r->ArraySize();
// plot test statistics distributions for the two hypothesis
if (mPlotHypoTestResult) {
TCanvas * c2 = new TCanvas();
if (nEntries > 1) {
int ny = TMath::CeilNint( sqrt(nEntries) );
int nx = TMath::CeilNint(double(nEntries)/ny);
c2->Divide( nx,ny);
}
for (int i=0; i<nEntries; i++) {
if (nEntries > 1) c2->cd(i+1);
SamplingDistPlot * pl = plot->MakeTestStatPlot(i);
pl->SetLogYaxis(true);
pl->Draw();
}
}
}
void StandardTestStatDistributionDemo(const char* infile = "",
const char* workspaceName = "combined",
const char* modelConfigName = "ModelConfig",
const char* dataName = "obsData"){
// the number of toy MC used to generate the distribution
int nToyMC = 1000;
// The parameter below is needed for asymptotic distribution to be chi-square,
// but set to false if your model is not numerically stable if mu<0
bool allowNegativeMu=true;
/////////////////////////////////////////////////////////////
// First part is just to access a user-defined file
// or create the standard example file if it doesn't exist
////////////////////////////////////////////////////////////
const char* filename = "";
if (!strcmp(infile,"")) {
filename = "results/example_combined_GaussExample_model.root";
bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code
// if file does not exists generate with histfactory
if (!fileExist) {
#ifdef _WIN32
cout << "HistFactory file cannot be generated on Windows - exit" << endl;
return;
#endif
// Normally this would be run on the command line
cout <<"will run standard hist2workspace example"<<endl;
gROOT->ProcessLine(".! prepareHistFactory .");
gROOT->ProcessLine(".! hist2workspace config/example.xml");
cout <<"\n\n---------------------"<<endl;
cout <<"Done creating example input"<<endl;
cout <<"---------------------\n\n"<<endl;
}
}
else
filename = infile;
// Try to open the file
TFile *file = TFile::Open(filename);
// if input file was specified byt not found, quit
if(!file ){
cout <<"StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl;
return;
}
/////////////////////////////////////////////////////////////
// Now get the data and workspace
////////////////////////////////////////////////////////////
// get the workspace out of the file
RooWorkspace* w = (RooWorkspace*) file->Get(workspaceName);
if(!w){
cout <<"workspace not found" << endl;
return;
}
// get the modelConfig out of the file
ModelConfig* mc = (ModelConfig*) w->obj(modelConfigName);
// get the modelConfig out of the file
RooAbsData* data = w->data(dataName);
// make sure ingredients are found
if(!data || !mc){
w->Print();
cout << "data or ModelConfig was not found" <<endl;
return;
}
mc->Print();
/////////////////////////////////////////////////////////////
// Now find the upper limit based on the asymptotic results
////////////////////////////////////////////////////////////
RooRealVar* firstPOI = (RooRealVar*) mc->GetParametersOfInterest()->first();
ProfileLikelihoodCalculator plc(*data,*mc);
LikelihoodInterval* interval = plc.GetInterval();
double plcUpperLimit = interval->UpperLimit(*firstPOI);
delete interval;
cout << "\n\n--------------------------------------"<<endl;
cout <<"Will generate sampling distribution at " << firstPOI->GetName() << " = " << plcUpperLimit <<endl;
int nPOI = mc->GetParametersOfInterest()->getSize();
if(nPOI>1){
cout <<"not sure what to do with other parameters of interest, but here are their values"<<endl;
mc->GetParametersOfInterest()->Print("v");
}
/////////////////////////////////////////////
// create thte test stat sampler
ProfileLikelihoodTestStat ts(*mc->GetPdf());
// to avoid effects from boundary and simplify asymptotic comparison, set min=-max
if(allowNegativeMu)
firstPOI->setMin(-1*firstPOI->getMax());
// temporary RooArgSet
RooArgSet poi;
poi.add(*mc->GetParametersOfInterest());
// create and configure the ToyMCSampler
ToyMCSampler sampler(ts,nToyMC);
sampler.SetPdf(*mc->GetPdf());
sampler.SetObservables(*mc->GetObservables());
sampler.SetGlobalObservables(*mc->GetGlobalObservables());
if(!mc->GetPdf()->canBeExtended() && (data->numEntries()==1)){
cout << "tell it to use 1 event"<<endl;
sampler.SetNEventsPerToy(1);
}
firstPOI->setVal(plcUpperLimit); // set POI value for generation
sampler.SetParametersForTestStat(*mc->GetParametersOfInterest()); // set POI value for evaluation
if (useProof) {
ProofConfig pc(*w, nworkers, "",false);
sampler.SetProofConfig(&pc); // enable proof
}
firstPOI->setVal(plcUpperLimit);
RooArgSet allParameters;
allParameters.add(*mc->GetParametersOfInterest());
allParameters.add(*mc->GetNuisanceParameters());
allParameters.Print("v");
SamplingDistribution* sampDist = sampler.GetSamplingDistribution(allParameters);
SamplingDistPlot plot;
plot.AddSamplingDistribution(sampDist);
plot.GetTH1F(sampDist)->GetYaxis()->SetTitle(Form("f(-log #lambda(#mu=%.2f) | #mu=%.2f)",plcUpperLimit,plcUpperLimit));
plot.SetAxisTitle(Form("-log #lambda(#mu=%.2f)",plcUpperLimit));
TCanvas* c1 = new TCanvas("c1");
c1->SetLogy();
plot.Draw();
double min = plot.GetTH1F(sampDist)->GetXaxis()->GetXmin();
double max = plot.GetTH1F(sampDist)->GetXaxis()->GetXmax();
TF1* f = new TF1("f",Form("2*ROOT::Math::chisquared_pdf(2*x,%d,0)",nPOI),min,max);
f->Draw("same");
c1->SaveAs("standard_test_stat_distribution.pdf");
}
