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C++ ToyMCSampler::AddTestStatistic方法代码示例

本文整理汇总了C++中ToyMCSampler::AddTestStatistic方法的典型用法代码示例。如果您正苦于以下问题:C++ ToyMCSampler::AddTestStatistic方法的具体用法?C++ ToyMCSampler::AddTestStatistic怎么用?C++ ToyMCSampler::AddTestStatistic使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在ToyMCSampler的用法示例。


在下文中一共展示了ToyMCSampler::AddTestStatistic方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的C++代码示例。

示例1: statTest

void statTest(double mu_pe, double mu_hyp, ModelConfig *mc , RooDataSet *data ){

    int nToyMC = 5;
    // set roofit seed
    RooRandom::randomGenerator()->SetSeed();

    cout << endl;
    cout << endl;
    cout << "Will generate " << nToyMC << " pseudo-experiments for : " << endl;
    cout << " - mu[pseudo-data] = " << mu_pe  << endl;
    cout << " - mu[stat-test]   = " << mu_hyp << endl;
    cout << endl;

    // Check number of POI (for Wald approx)
    RooArgSet *ParamOfInterest = (RooArgSet*) mc->GetParametersOfInterest();
    int nPOI = ParamOfInterest->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");
    }
    RooRealVar* firstPOI    = (RooRealVar*) ParamOfInterest->first(); 
    RooAbsPdf *simPdf = (mc->GetPdf());
    //PrintAllParametersAndValues( *mc->GetGlobalObservables() );
    //PrintAllParametersAndValues( *mc->GetObservables() );
    firstPOI->setVal(0.0); // FIXME

    //simPdf->fitTo( *data, Hesse(kTRUE), Minos(kTRUE), PrintLevel(1) );
    simPdf->fitTo( *data );

    // set up the sampler
    ToyMCSampler sampler;
    sampler.SetPdf(*mc->GetPdf());
    sampler.SetObservables(*mc->GetObservables());
    sampler.SetNToys(nToyMC);
    sampler.SetGlobalObservables(*mc->GetGlobalObservables());
    sampler.SetParametersForTestStat(*mc->GetParametersOfInterest());
    RooArgSet* poiset = dynamic_cast<RooArgSet*>(ParamOfInterest->Clone());


    // only unconditional fit
    MinNLLTestStat *minNll = new MinNLLTestStat(*mc->GetPdf());
    minNll->EnableDetailedOutput(true);
    sampler.AddTestStatistic(minNll);

    // enable PROOF if desired
    //ProofConfig pc(*w, 8, "workers=8", kFALSE);
    //sampler.SetProofConfig(&pc);

    // evaluate the test statistics - this is where most of our time will be spent
    cout << "Generating " << nToyMC << " toys...this will take a few minutes" << endl;
    TStopwatch *mn_t = new TStopwatch; 
    mn_t->Start();
    RooDataSet* sd = sampler.GetSamplingDistributions(*poiset);
    cout << "Toy generation complete :" << endl;
    // stop timing
    mn_t->Stop();
    cout << " total CPU time: " << mn_t->CpuTime() << endl;
    cout << " total real time: " << mn_t->RealTime() << endl; 

    // now sd contains all information about our test statistics, including detailed output
    // we might eg. want to explore the results either directly, or first converting to a TTree
    // do the conversion
    TFile f("mytoys.root", "RECREATE");
    TTree *toyTree = RooStats::GetAsTTree("toyTree", "TTree created from test statistics", *sd);
    // save result to file, but in general do whatever you like
    f.cd();
    toyTree->Write();
    f.Close();
/*
    TFile* tmpFile = new TFile("mytoys.root","READ");
    TTree* myTree = (TTree*)tmpFile->Get("toyTree");

    // get boundaries for histograms
    TIter nextLeaf( (myTree->GetListOfLeaves())->MakeIterator() );
    TObject* leafObj(0);
    map<TString, float> xMaxs;
    map<TString, float> xMins;
    for(int i(0); i<myTree->GetEntries(); i++) {
      myTree->GetEntry(i);
      nextLeaf = ( (myTree->GetListOfLeaves())->MakeIterator() );
      while( (leafObj = nextLeaf.Next()) ) {
        TString name(leafObj->GetName());
        float value(myTree->GetLeaf( leafObj->GetName() )->GetValue());
        if(value > xMaxs[name]) { xMaxs[name] = value; }
        if(value < xMins[name]) { xMins[name] = value; }
      } // loop over leaves
    } // loop over tree entries

    // plot everything in the tree
    myTree->GetEntry(0);
    nextLeaf = ( (myTree->GetListOfLeaves())->MakeIterator() );
    leafObj = 0;
    // make a histogram per leaf
    map<TString, TH1F*> hists;
    myTree->GetEntry(0);
    while( (leafObj = nextLeaf.Next()) ) {
      if(!leafObj) { continue; }
      //cout << leafObj->GetName() << endl;
      TString name(leafObj->GetName());
      // special ones : fit related things
//.........这里部分代码省略.........
开发者ID:panManfredini,项目名称:RooStatLikelihood,代码行数:101,代码来源:statTest.C


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