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.             *
 *************************************************************************/
 
 
 
 
// from std
#include <string>
#include <vector>
#include <map>
#include <iostream>
#include <sstream>
 
// from root
#include "TFile.h"
#include "TH1F.h"
#include "TDOMParser.h"
#include "TXMLAttr.h"
#include "TString.h"
#include "TCanvas.h"
#include "TStyle.h"
#include "TLine.h"
#include "TSystem.h"
 
 
// from roofit
#include "RooStats/ModelConfig.h"
 
// from this package
#include "Helper.h"
#include "RooStats/HistFactory/EstimateSummary.h"
#include "RooStats/HistFactory/Measurement.h"
#include "RooStats/HistFactory/HistoToWorkspaceFactoryFast.h"
#include "RooStats/HistFactory/HistFactoryException.h"
 
#include "RooStats/HistFactory/MakeModelAndMeasurementsFast.h"
 
using namespace RooFit;
//using namespace RooStats;
//using namespace HistFactory;
 
//using namespace std;
 
 
/** ********************************************************************************************
  \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>
  <ul>
  <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>
*/
RooWorkspace* RooStats::HistFactory::MakeModelAndMeasurementFast( RooStats::HistFactory::Measurement& measurement ) {
 
  // This will be returned
  RooWorkspace* ws = NULL;
  TFile* outFile = NULL;
  FILE*  tableFile=NULL;
 
  try {
 
    std::cout << "Making Model and Measurements (Fast) for measurement: " << measurement.GetName() << std::endl;
 
    double lumiError = measurement.GetLumi()*measurement.GetLumiRelErr();
 
    std::cout << "using lumi = " << measurement.GetLumi() << " and lumiError = " << lumiError
         << " including bins between " << measurement.GetBinLow() << " and " << measurement.GetBinHigh() << std::endl;
    std::cout << "fixing the following parameters:"  << std::endl;
 
    for(std::vector<std::string>::iterator itr=measurement.GetConstantParams().begin(); itr!=measurement.GetConstantParams().end(); ++itr){
      std::cout << "   " << *itr << std::endl;
    }
 
    std::string rowTitle = measurement.GetName();
    
    std::vector<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);
       std::cout << "Checking if output directory : " << outputDir << " -  exists" << std::endl;
       if (gSystem->OpenDirectory( outputDir.c_str() )  == 0 ) { 
          std::cout << "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; 
             std::cout << "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";
    std::cout << "Creating the output file: " << outputFileName << std::endl;
    outFile = new TFile(outputFileName.c_str(), "recreate");
 
    // Create the table file
    // This holds the table of fitted values and errors
    std::string tableFileName = measurement.GetOutputFilePrefix() + "_results.table";
    std::cout << "Creating the table file: " << tableFileName << std::endl;
    tableFile =  fopen( tableFileName.c_str(), "a"); 
 
    std::cout << "Creating the HistoToWorkspaceFactoryFast factory" << std::endl;
    HistoToWorkspaceFactoryFast factory( measurement );
    
    // Make the factory, and do some preprocessing
    // HistoToWorkspaceFactoryFast factory(measurement, rowTitle, outFile);
    std::cout << "Setting preprocess functions" << std::endl;
    factory.SetFunctionsToPreprocess( measurement.GetPreprocessFunctions() );
  
    // for results tables
    fprintf(tableFile, " %s &", rowTitle.c_str() );
  
    // 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() ) {
   std::cout << "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();
      std::cout << "Starting to process channel: " << ch_name << std::endl;
      channel_names.push_back(ch_name);
      RooWorkspace* ws_single = factory.MakeSingleChannelModel( measurement, channel );
      channel_workspaces.push_back(ws_single);
 
      // Make the output
      std::string ChannelFileName = measurement.GetOutputFilePrefix() + "_" 
   + ch_name + "_" + rowTitle + "_model.root";
      ws_single->writeToFile( ChannelFileName.c_str() );
    
      // 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 );
      std::cout << "Opening File to hold channel: " << ChannelFileName << std::endl;
      TFile* chanFile = TFile::Open( ChannelFileName.c_str(), "UPDATE" );
      std::cout << "About to write channel measurement to file" << std::endl;
      meas_chan.writeToFile( chanFile );
      std::cout << "Successfully wrote channel to file" << std::endl;
      chanFile->Close();
 
      // Get the Paramater of Interest as a RooRealVar
      RooRealVar* poi = dynamic_cast<RooRealVar*>( ws_single->var( (measurement.GetPOI()).c_str() ) );
 
      // do fit unless exportOnly requested
      if(! measurement.GetExportOnly()){
   if(!poi) {
     std::cout << "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);
     }
   }
      }
      
      fprintf(tableFile, " & " );
    } // 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
    ws = factory.MakeCombinedModel(channel_names, channel_workspaces);
 
    // Configure that workspace
    HistoToWorkspaceFactoryFast::ConfigureWorkspaceForMeasurement( "simPdf", ws, measurement );
 
    // Get the Parameter of interest as a RooRealVar
    RooRealVar* poi = dynamic_cast<RooRealVar*>( ws->var( (measurement.GetPOI()).c_str() ) );
    
    std::string CombinedFileName = measurement.GetOutputFilePrefix() + "_combined_"
      + rowTitle + "_model.root";
    std::cout << "Writing combined workspace to file: " << CombinedFileName << std::endl;
    ws->writeToFile( CombinedFileName.c_str() );
    std::cout << "Writing combined measurement to file: " << CombinedFileName << std::endl;
    TFile* combFile = TFile::Open( CombinedFileName.c_str(), "UPDATE" );
    if( combFile == NULL ) {
      std::cout << "Error: Failed to open file " << CombinedFileName << std::endl;
      throw hf_exc();
    }
    measurement.writeToFile( combFile );
    combFile->Close();
    
    // Fit the combined model
    if(! measurement.GetExportOnly()){
      if(!poi) {
   std::cout << "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);
   }
      }
    }
  
    fprintf(tableFile, " \\\\ \n");
 
    outFile->Close();
    delete outFile;
 
    fclose( tableFile );
 
  }
  catch(...) {
    if( tableFile ) fclose(tableFile);
    if(outFile) outFile->Close();
    throw;
  }
  
  return ws;
 
}
 
 
///////////////////////////////////////////////
void RooStats::HistFactory::FitModelAndPlot(const std::string& MeasurementName, 
                   const std::string& FileNamePrefix, 
                   RooWorkspace * combined, std::string channel, 
                   std::string data_name, 
                   TFile* outFile, FILE* tableFile  ) {
 
  if( outFile == NULL ) {
    std::cout << "Error: Output File in FitModelAndPlot is NULL" << std::endl;
    throw hf_exc();
  }
 
  if( tableFile == NULL ) {
    std::cout << "Error: tableFile in FitModelAndPlot is NULL" << std::endl;
    throw hf_exc();
  }
 
  if( combined == NULL ) {
    std::cout << "Error: Supplied workspace in FitModelAndPlot is NULL" << std::endl;
    throw hf_exc();
  }
 
  ModelConfig* combined_config = (ModelConfig *) combined->obj("ModelConfig");
  if(!combined_config){
    std::cout << "Error: no ModelConfig found in Measurement: "
         << MeasurementName <<  std::endl;
    throw hf_exc();
  }
 
  RooAbsData* simData = combined->data(data_name.c_str());
  if(!simData){
    std::cout << "Error: Failed to get dataset: " << data_name
         << " in measurement: " << MeasurementName << std::endl;
    throw hf_exc();
  }
    
  const RooArgSet* POIs = combined_config->GetParametersOfInterest();
  if(!POIs) {
    std::cout << "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==NULL ) {
    std::cout << "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
  std::cout << "\n\n---------------" << std::endl;
  std::cout << "---------------- Doing "<< channel << " Fit" << std::endl;
  std::cout << "---------------\n\n" << std::endl;
  model->fitTo(*simData, Minos(kTRUE), PrintLevel(1));
 
  // If there are no parameters of interest,
  // we exit the function here
  if( POIs->getSize()==0 ) {
    std::cout << "WARNING: No POIs found in measurement: " << MeasurementName << std::endl;
    return;
  }
 
  // Loop over all POIs and print their fitted values
  RooRealVar* poi = NULL; // (RooRealVar*) POIs->first();
  TIterator* params_itr = POIs->createIterator();
  TObject* poi_obj=NULL;
  while( (poi_obj=params_itr->Next()) ) {
    //poi = (RooRealVar*) poi_obj;
    poi = dynamic_cast<RooRealVar*>(poi_obj);
    std::cout << "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
  poi = dynamic_cast<RooRealVar*>(POIs->first());
 
  // Print the MINOS errors to the TableFile
  fprintf(tableFile, " %.4f / %.4f  ", poi->getErrorLo(), poi->getErrorHi());
 
  // Make the Profile Likelihood Plot
  RooAbsReal* nll = model->createNLL(*simData);
  RooAbsReal* profile = nll->createProfile(*poi);
  if( profile==NULL ) {
    std::cout << "Error: Failed to make ProfileLikelihood for: " << poi->GetName() 
         << " using model: " << model->GetName()
         << " and data: " << simData->GetName()
         << std::endl;
    throw hf_exc();
  }
 
  RooPlot* frame = poi->frame();
  if( frame == NULL ) {
    std::cout << "Error: Failed to create RooPlot frame for: " << poi->GetName() << std::endl;
    throw hf_exc();
  }
 
  // Draw the likelihood curve
  FormatFrameForLikelihood(frame);
  TCanvas* ProfileLikelihoodCanvas = new TCanvas( channel.c_str(), "",800,600);
  nll->plotOn(frame, ShiftToZero(), LineColor(kRed), LineStyle(kDashed));
  profile->plotOn(frame);
  frame->SetMinimum(0);
  frame->SetMaximum(2.);
  frame->Draw();
  std::string ProfilePlotName = FileNamePrefix+"_"+channel+"_"+MeasurementName+"_profileLR.eps";
  ProfileLikelihoodCanvas->SaveAs( ProfilePlotName.c_str() );
  delete ProfileLikelihoodCanvas;
 
  // 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 == NULL ) {
    std::cout << "Error: Failed to make channel directory: " << channel << std::endl;
    throw hf_exc();
  }
  TDirectory* summary_dir = channel_dir->mkdir("Summary");
  if( summary_dir == NULL ) {
    std::cout << "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_t* curve_x=curve->GetX();
 
  Double_t * x_arr = new Double_t[curve_N];
  Double_t * y_arr_nll = new Double_t[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();
  }
 
  delete frame;
 
  TGraph* g = new TGraph(curve_N, x_arr, y_arr_nll);
  g->SetName( (FileNamePrefix +"_nll").c_str() );
  g->Write(); 
  delete g;
  delete [] x_arr;
  delete [] y_arr_nll;
    
  // Finally, restore the initial values
  combined->loadSnapshot("InitialValues");
    
}
 
 
void RooStats::HistFactory::FitModel(RooWorkspace * combined, std::string data_name ) {
 
    std::cout << "In Fit Model" << std::endl;
    ModelConfig * combined_config = (ModelConfig *) combined->obj("ModelConfig");
    if(!combined_config){
      std::cout << "no model config " << "ModelConfig" << " exiting" << std::endl;
      return;
    }
    
    RooAbsData* simData = combined->data(data_name.c_str());
    if(!simData){
      std::cout << "no data " << data_name << " exiting" << std::endl;
      return;
    }
 
    const RooArgSet * POIs=combined_config->GetParametersOfInterest();
    if(!POIs){
      std::cout << "no poi " << data_name << " exiting" << std::endl;
      return;
    }
 
    RooAbsPdf* model=combined_config->GetPdf();
    model->fitTo(*simData, Minos(kTRUE), PrintLevel(1));
    
  }
 
 
void RooStats::HistFactory::FormatFrameForLikelihood(RooPlot* frame, std::string /*XTitle*/, 
                       std::string YTitle){
 
    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);
}