MakeModelAndMeasurementsFast.cxx

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// @(#)root/roostats:$Id:  cranmer $
// Author: Kyle Cranmer, Akira Shibata
/*************************************************************************
 * Copyright (C) 1995-2008, Rene Brun and Fons Rademakers.               *
 * All rights reserved.                                                  *
 *                                                                       *
 * For the licensing terms see $ROOTSYS/LICENSE.                         *
 * For the list of contributors see $ROOTSYS/README/CREDITS.             *
 *************************************************************************/
 
#include "RooStats/HistFactory/MakeModelAndMeasurementsFast.h"
 
// from roofit
#include "RooFit/ModelConfig.h"
 
// from this package
#include "RooStats/HistFactory/Measurement.h"
#include "RooStats/HistFactory/HistFactoryException.h"
 
#include "HFMsgService.h"
 
#include <TFile.h>
#include <TH1F.h>
#include <TCanvas.h>
#include <TStyle.h>
#include <TLine.h>
#include <TSystem.h>
 
#include <string>
#include <vector>
#include <map>
#include <fstream>
#include <sstream>
 
 
/** ********************************************************************************************
  \ingroup HistFactory
 
  <p>
  This is a package that creates a RooFit probability density function from ROOT histograms
  of expected distributions and histograms that represent the +/- 1 sigma variations
  from systematic effects. The resulting probability density function can then be used
  with any of the statistical tools provided within RooStats, such as the profile
  likelihood ratio, Feldman-Cousins, etc.  In this version, the model is directly
  fed to a likelihood ratio test, but it needs to be further factorized.</p>
 
  <p>
  The user needs to provide histograms (in picobarns per bin) and configure the job
  with XML.  The configuration XML is defined in the file `$ROOTSYS/config/HistFactorySchema.dtd`, but essentially
  it is organized as follows (see the examples in `${ROOTSYS}/tutorials/histfactory/`)</p>
 
  <ul>
  <li> a top level 'Combination' that is composed of:</li>
  <ul>
  <li> several 'Channels' (eg. ee, emu, mumu), which are composed of:</li>
  <ul>
  <li> several 'Samples' (eg. signal, bkg1, bkg2, ...), each of which has:</li>
  <ul>
  <li> a name</li>
  <li> if the sample is normalized by theory (eg N = L*sigma) or not (eg. data driven)</li>
  <li> a nominal expectation histogram</li>
  <li> a named 'Normalization Factor' (which can be fixed or allowed to float in a fit)</li>
  <li> several 'Overall Systematics' in normalization with:</li>
  <ul>
  <li> a name</li>
  <li> +/- 1 sigma variations (eg. 1.05 and 0.95 for a 5% uncertainty)</li>
  </ul>
  <li> several 'Histogram Systematics' in shape with:</li>
  <ul>
  <li> a name (which can be shared with the OverallSyst if correlated)</li>
  <li> +/- 1 sigma variational histograms</li>
  </ul>
  </ul>
  </ul>
  <li> several 'Measurements' (corresponding to a full fit of the model) each of which specifies</li>
  <ul>
  <li> a name for this fit to be used in tables and files</li>
  <li> what is the luminosity associated to the measurement in picobarns</li>
  <li> which bins of the histogram should be used</li>
  <li> what is the relative uncertainty on the luminosity </li>
  <li> what is (are) the parameter(s) of interest that will be measured</li>
  <li> which parameters should be fixed/floating (eg. nuisance parameters)</li>
  </ul>
  </ul>
  </ul>
*/
RooFit::OwningPtr<RooWorkspace>
RooStats::HistFactory::MakeModelAndMeasurementFast(RooStats::HistFactory::Measurement &measurement,
                                                   HistoToWorkspaceFactoryFast::Configuration const &cfg)
{
  std::unique_ptr<TFile> outFile;
  std::ofstream tableFile;
 
  auto& msgSvc = RooMsgService::instance();
  msgSvc.getStream(1).removeTopic(RooFit::ObjectHandling);
 
    cxcoutIHF << "Making Model and Measurements (Fast) for measurement: " << measurement.GetName() << std::endl;
 
    double lumiError = measurement.GetLumi()*measurement.GetLumiRelErr();
 
    cxcoutIHF << "using lumi = " << measurement.GetLumi() << " and lumiError = " << lumiError
         << " including bins between " << measurement.GetBinLow() << " and " << measurement.GetBinHigh() << std::endl;
 
    std::ostringstream parameterMessage;
    parameterMessage << "fixing the following parameters:"  << std::endl;
 
    for(std::vector<std::string>::iterator itr=measurement.GetConstantParams().begin(); itr!=measurement.GetConstantParams().end(); ++itr){
      parameterMessage << "   " << *itr << '\n';
    }
    cxcoutIHF << parameterMessage.str();
 
    std::string rowTitle = measurement.GetName();
 
    std::vector<std::unique_ptr<RooWorkspace>> channel_workspaces;
    std::vector<std::string>        channel_names;
 
    // Create the outFile - first check if the outputfile exists
    std::string prefix =  measurement.GetOutputFilePrefix();
    // parse prefix to find output directory -
    // assume there is a file prefix after the last "/" that we remove
    // to get the directory name.
    // We do by finding last occurrence of "/" and using as directory name what is before
    // if we do not have a "/" in the prefix there is no output directory to be checked or created
    size_t pos = prefix.rfind('/');
    if (pos != std::string::npos) {
       std::string outputDir = prefix.substr(0,pos);
       cxcoutDHF << "Checking if output directory : " << outputDir << " -  exists" << std::endl;
       if (gSystem->OpenDirectory( outputDir.c_str() )  == nullptr ) {
          cxcoutDHF << "Output directory : " << outputDir << " - does not exist, try to create" << std::endl;
          int success = gSystem->MakeDirectory( outputDir.c_str() );
          if( success != 0 ) {
             std::string fullOutputDir = std::string(gSystem->pwd()) + std::string("/") + outputDir;
             cxcoutEHF << "Error: Failed to make output directory: " <<  fullOutputDir << std::endl;
             throw hf_exc();
          }
       }
    }
 
    // This holds the TGraphs that are created during the fit
    std::string outputFileName = measurement.GetOutputFilePrefix() + "_" + measurement.GetName() + ".root";
    cxcoutIHF << "Creating the output file: " << outputFileName << std::endl;
    outFile = std::make_unique<TFile>(outputFileName.c_str(), "recreate");
 
    // Create the table file, which holds the table of fitted values and errors
    tableFile.open(measurement.GetOutputFilePrefix() + "_results.table", std::ios::out | std::ios::app);
 
    cxcoutIHF << "Creating the HistoToWorkspaceFactoryFast factory" << std::endl;
    HistoToWorkspaceFactoryFast factory{measurement, cfg};
 
    // Make the factory, and do some preprocessing
    // HistoToWorkspaceFactoryFast factory(measurement, rowTitle, outFile);
    cxcoutIHF << "Setting preprocess functions" << std::endl;
    factory.SetFunctionsToPreprocess( measurement.GetPreprocessFunctions() );
 
    // for results tables
    tableFile << " " << rowTitle << " &";
 
    // First: Loop to make the individual channels
    for( unsigned int chanItr = 0; chanItr < measurement.GetChannels().size(); ++chanItr ) {
 
      HistFactory::Channel& channel = measurement.GetChannels().at( chanItr );
      if( ! channel.CheckHistograms() ) {
   cxcoutEHF << "MakeModelAndMeasurementsFast: Channel: " << channel.GetName()
        << " has uninitialized histogram pointers" << std::endl;
   throw hf_exc();
      }
 
      // Make the workspace for this individual channel
      std::string ch_name = channel.GetName();
      cxcoutPHF << "Starting to process channel: " << ch_name << std::endl;
      channel_names.push_back(ch_name);
      std::unique_ptr<RooWorkspace> ws_single{factory.MakeSingleChannelModel( measurement, channel )};
 
      {
        // Make the output
        std::string ChannelFileName = measurement.GetOutputFilePrefix() + "_"
    + ch_name + "_" + rowTitle + "_model.root";
        cxcoutIHF << "Opening File to hold channel: " << ChannelFileName << std::endl;
        std::unique_ptr<TFile> chanFile{TFile::Open( ChannelFileName.c_str(), "RECREATE" )};
        chanFile->WriteTObject(ws_single.get());
        // Now, write the measurement to the file
        // Make a new measurement for only this channel
        RooStats::HistFactory::Measurement meas_chan( measurement );
        meas_chan.GetChannels().clear();
        meas_chan.GetChannels().push_back( channel );
        cxcoutIHF << "About to write channel measurement to file" << std::endl;
        meas_chan.writeToFile( chanFile.get() );
        cxcoutPHF << "Successfully wrote channel to file" << std::endl;
      }
 
      // Get the Parameter of Interest as a RooRealVar
      RooRealVar* poi = dynamic_cast<RooRealVar*>( ws_single->var(measurement.GetPOI()));
 
      // do fit unless exportOnly requested
      if(! measurement.GetExportOnly()){
   if(!poi) {
     cxcoutWHF << "Can't do fit for: " << measurement.GetName()
          << ", no parameter of interest" << std::endl;
   } else {
     if(ws_single->data("obsData")) {
       FitModelAndPlot(measurement.GetName(), measurement.GetOutputFilePrefix(), *ws_single,
             ch_name, "obsData",    *outFile, tableFile);
     } else {
       FitModelAndPlot(measurement.GetName(), measurement.GetOutputFilePrefix(), *ws_single,
             ch_name, "asimovData", *outFile, tableFile);
     }
   }
      }
 
      tableFile << " & ";
 
      channel_workspaces.emplace_back(std::move(ws_single));
    } // End loop over channels
 
    /***
   Second: Make the combined model:
   If you want output histograms in root format, create and pass it to the combine routine.
   "combine" : will do the individual cross-section measurements plus combination
    ***/
 
    // Use HistFactory to combine the individual channel workspaces
    std::unique_ptr<RooWorkspace> ws{factory.MakeCombinedModel(channel_names, channel_workspaces)};
 
    // Configure that workspace
    HistoToWorkspaceFactoryFast::ConfigureWorkspaceForMeasurement("simPdf", ws.get(), measurement);
 
    // Get the Parameter of interest as a RooRealVar
    RooRealVar* poi = dynamic_cast<RooRealVar*>( ws->var(measurement.GetPOI()));
 
    {
      std::string CombinedFileName = measurement.GetOutputFilePrefix() + "_combined_"
        + rowTitle + "_model.root";
      cxcoutPHF << "Writing combined workspace to file: " << CombinedFileName << std::endl;
      std::unique_ptr<TFile> combFile{TFile::Open( CombinedFileName.c_str(), "RECREATE" )};
      if( combFile == nullptr ) {
        cxcoutEHF << "Error: Failed to open file " << CombinedFileName << std::endl;
        throw hf_exc();
      }
      combFile->WriteTObject(ws.get());
      cxcoutPHF << "Writing combined measurement to file: " << CombinedFileName << std::endl;
      measurement.writeToFile( combFile.get() );
    }
 
    // Fit the combined model
    if(! measurement.GetExportOnly()){
      if(!poi) {
   cxcoutWHF << "Can't do fit for: " << measurement.GetName()
        << ", no parameter of interest" << std::endl;
      }
      else {
   if(ws->data("obsData")){
     FitModelAndPlot(measurement.GetName(), measurement.GetOutputFilePrefix(), *ws,"combined",
           "obsData",    *outFile, tableFile);
   }
   else {
     FitModelAndPlot(measurement.GetName(), measurement.GetOutputFilePrefix(), *ws,"combined",
           "asimovData", *outFile, tableFile);
   }
      }
    }
 
    tableFile << " \\\\ \n";
 
  msgSvc.getStream(1).addTopic(RooFit::ObjectHandling);
 
  return RooFit::Detail::owningPtr(std::move(ws));
}
 
 
///////////////////////////////////////////////
void RooStats::HistFactory::FitModelAndPlot(const std::string &MeasurementName, const std::string &FileNamePrefix,
                                            RooWorkspace &combined, std::string channel, std::string data_name,
                                            TFile &outFile, std::ostream &tableStream)
{
  using namespace RooFit;
 
  auto combined_config = static_cast<ModelConfig *>(combined.obj("ModelConfig"));
  if(!combined_config){
    cxcoutEHF << "Error: no ModelConfig found in Measurement: "
         << MeasurementName <<  std::endl;
    throw hf_exc();
  }
 
  RooAbsData* simData = combined.data(data_name);
  if(!simData){
    cxcoutEHF << "Error: Failed to get dataset: " << data_name
         << " in measurement: " << MeasurementName << std::endl;
    throw hf_exc();
  }
 
  const RooArgSet* POIs = combined_config->GetParametersOfInterest();
  if(!POIs) {
    cxcoutEHF << "Not Fitting Model for measurement: " << MeasurementName
         << ", no poi found" << std::endl;
    // Should I throw an exception here?
    return;
  }
 
  RooAbsPdf* model = combined_config->GetPdf();
  if( model==nullptr ) {
    cxcoutEHF << "Error: Failed to find pdf in ModelConfig: " << combined_config->GetName()
         << std::endl;
    throw hf_exc();
  }
 
  // Save a Snapshot
  RooArgSet PoiPlusNuisance;
  if( combined_config->GetNuisanceParameters() ) {
    PoiPlusNuisance.add( *combined_config->GetNuisanceParameters() );
  }
  PoiPlusNuisance.add( *combined_config->GetParametersOfInterest() );
  combined.saveSnapshot("InitialValues", PoiPlusNuisance);
 
  ///////////////////////////////////////
  // Do the fit
  cxcoutPHF << "\n---------------"
    << "\nDoing "<< channel << " Fit"
    << "\n---------------\n\n" << std::endl;
  const int printLevel = RooMsgService::instance().isActive(static_cast<TObject*>(nullptr), RooFit::HistFactory, RooFit::DEBUG) ? 1 : -1;
  model->fitTo(*simData, Minos(true), PrintLevel(printLevel));
 
  // If there are no parameters of interest,
  // we exit the function here
  if( POIs->empty() ) {
    cxcoutWHF << "WARNING: No POIs found in measurement: " << MeasurementName << std::endl;
    return;
  }
 
  // Loop over all POIs and print their fitted values
  for (auto const *poi : static_range_cast<RooRealVar *>(*POIs)) {
    cxcoutIHF << "printing results for " << poi->GetName()
         << " at " << poi->getVal()<< " high "
         << poi->getErrorLo() << " low "
         << poi->getErrorHi() << std::endl;
  }
 
  // But we only make detailed plots and tables
  // for the 'first' POI
  RooRealVar* poi = static_cast<RooRealVar *>(POIs->first());
 
  // Print the MINOS errors to the TableFile
  const auto oldPrecision = tableStream.precision();
  tableStream.precision(4);
  tableStream << " " << poi->getErrorLo() << " / " << poi->getErrorHi() << "  ";
  tableStream.precision(oldPrecision);
 
  // Make the Profile Likelihood Plot
  std::unique_ptr<RooAbsReal> nll{model->createNLL(*simData)};
  std::unique_ptr<RooAbsReal> profile{nll->createProfile(*poi)};
 
  std::unique_ptr<RooPlot> frame{poi->frame()};
 
  // Draw the likelihood curve
  FormatFrameForLikelihood(frame.get());
  {
    TCanvas profileLikelihoodCanvas{channel.c_str(), "",800,600};
    nll->plotOn(frame.get(), ShiftToZero(), LineColor(kRed), LineStyle(kDashed));
    profile->plotOn(frame.get());
    frame->SetMinimum(0);
    frame->SetMaximum(2.);
    frame->Draw();
    std::string profilePlotName = FileNamePrefix+"_"+channel+"_"+MeasurementName+"_profileLR.eps";
    profileLikelihoodCanvas.SaveAs( profilePlotName.c_str() );
  }
 
  // Now, we save our results to the 'output' file
  // (I'm not sure if users actually look into this file,
  // but adding additional information and useful plots
  // may make it more attractive)
 
  // Save to the output file
  TDirectory* channel_dir = outFile.mkdir(channel.c_str());
  if( channel_dir == nullptr ) {
    cxcoutEHF << "Error: Failed to make channel directory: " << channel << std::endl;
    throw hf_exc();
  }
  TDirectory* summary_dir = channel_dir->mkdir("Summary");
  if( summary_dir == nullptr ) {
    cxcoutEHF << "Error: Failed to make Summary directory for channel: "
         << channel << std::endl;
    throw hf_exc();
  }
  summary_dir->cd();
 
  // Save a graph of the profile likelihood curve
  RooCurve* curve=frame->getCurve();
  Int_t curve_N=curve->GetN();
  double* curve_x=curve->GetX();
 
  std::vector<double> x_arr(curve_N);
  std::vector<double> y_arr_nll(curve_N);
 
  for(int i=0; i<curve_N; i++){
    double f=curve_x[i];
    poi->setVal(f);
    x_arr[i]=f;
    y_arr_nll[i]=nll->getVal();
  }
 
  TGraph g{curve_N, x_arr.data(), y_arr_nll.data()};
  g.SetName( (FileNamePrefix +"_nll").c_str() );
  g.Write();
 
  // Finally, restore the initial values
  combined.loadSnapshot("InitialValues");
 
}
 
 
void RooStats::HistFactory::FitModel(RooWorkspace * combined, std::string data_name )
{
   using namespace RooFit;
 
    cxcoutIHF << "In Fit Model" << std::endl;
    ModelConfig * combined_config = (ModelConfig *) combined->obj("ModelConfig");
    if(!combined_config){
      cxcoutEHF << "no model config " << "ModelConfig" << " exiting" << std::endl;
      return;
    }
 
    RooAbsData* simData = combined->data(data_name);
    if(!simData){
      cxcoutEHF << "no data " << data_name << " exiting" << std::endl;
      return;
    }
 
    const RooArgSet * POIs=combined_config->GetParametersOfInterest();
    if(!POIs){
      cxcoutEHF << "no poi " << data_name << " exiting" << std::endl;
      return;
    }
 
    RooAbsPdf* model=combined_config->GetPdf();
    model->fitTo(*simData, Minos(true), PrintLevel(1));
 
  }
 
 
void RooStats::HistFactory::FormatFrameForLikelihood(RooPlot* frame, std::string /*XTitle*/,
                       std::string YTitle)
{
   using namespace RooFit;
 
    gStyle->SetCanvasBorderMode(0);
    gStyle->SetPadBorderMode(0);
    // gStyle->SetPadColor(0);
    // gStyle->SetCanvasColor(255);
    // gStyle->SetTitleFillColor(255);
    // gStyle->SetFrameFillColor(0);
    // gStyle->SetStatColor(255);
 
    RooAbsRealLValue* var = frame->getPlotVar();
    double xmin = var->getMin();
    double xmax = var->getMax();
 
    frame->SetTitle("");
    //      frame->GetXaxis()->SetTitle(XTitle.c_str());
    frame->GetXaxis()->SetTitle(var->GetTitle());
    frame->GetYaxis()->SetTitle(YTitle.c_str());
    frame->SetMaximum(2.);
    frame->SetMinimum(0.);
    TLine * line = new TLine(xmin,.5,xmax,.5);
    line->SetLineColor(kGreen);
    TLine * line90 = new TLine(xmin,2.71/2.,xmax,2.71/2.);
    line90->SetLineColor(kGreen);
    TLine * line95 = new TLine(xmin,3.84/2.,xmax,3.84/2.);
    line95->SetLineColor(kGreen);
    frame->addObject(line);
    frame->addObject(line90);
    frame->addObject(line95);
}