LumiReweightingStandAlone.h

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#ifndef PhysicsTools_Utilities_interface_LumiReWeighting_h
#define PhysicsTools_Utilities_interface_LumiReWeighting_h


#include "TH1.h"
#include "TH3.h"
#include "TFile.h"
#include "TRandom1.h"
#include "TRandom2.h"
#include "TRandom3.h"
#include "TStopwatch.h"
#include <string>
#include <vector>
#include <cmath>
#include <algorithm>

namespace reweight {


  // add a class to shift the mean of a poisson-like luminosity distribution by an arbitrary amount. 
  // Only valid for small (<1.5) shifts about the 2011 lumi distribution for now, because shifts are non-linear
  // Each PoissonMeanShifter does one shift, so defining multiples can give you an arbitrary collection

  class PoissonMeanShifter {

  public:

    PoissonMeanShifter() { };

    PoissonMeanShifter( float Shift ){

      // these are the polynomial or exponential coefficients for each bin of a 25-bin sequence that
      // convert the Distribution of the 2011 luminosity to something with a lower or higher peak luminosity.
      // The distributions aren't quite poisson because they model luminosity decreasing during a fill. This implies that
      // they do get wider as the mean increases, so the weights are not linear with increasing mean.

      static double p0_minus[20] = { 1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1. };
      static double p1_minus[20] = {
    -0.677786,
    -0.619614,
    -0.49465,
    -0.357963,
    -0.238359,
    -0.110002,
    0.0348629,
    0.191263,
    0.347648,
    0.516615,
    0.679646,
    0.836673,
    0.97764,
    1.135,
    1.29922,
    1.42467,
    1.55901,
    1.61762,
    1.67275,
    1.96008
      };
      static double p2_minus[20] = {
    0.526164,
    0.251816,
    0.11049,
    0.026917,
    -0.0464692,
    -0.087022,
    -0.0931581,
    -0.0714295,
    -0.0331772,
    0.0347473,
    0.108658,
    0.193048,
    0.272314,
    0.376357,
    0.4964,
    0.58854,
    0.684959,
    0.731063,
    0.760044,
    1.02386
      };

      static double p1_expoM[5] = {
    1.63363e-03,
    6.79290e-04,
    3.69900e-04,
    2.24349e-04,
    9.87156e-06
      };

      static double p2_expoM[5] = {
    2.64692,
    3.26585,
    3.53229,
    4.18035,
    5.64027
      };


      static double p0_plus[20] = { 1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1.,1. };
      static double p1_plus[20] = {
    -0.739059,
    -0.594445,
    -0.477276,
    -0.359707,
    -0.233573,
    -0.103458,
    0.0373401,
    0.176571,
    0.337617,
    0.499074,
    0.675126,
    0.840522,
    1.00917,
    1.15847,
    1.23816,
    1.44271,
    1.52982,
    1.46385,
    1.5802,
    0.988689
      };
      static double p2_plus[20] = {
    0.208068,
    0.130033,
    0.0850356,
    0.0448344,
    0.000749832,
    -0.0331347,
    -0.0653281,
    -0.0746009,
    -0.0800667,
    -0.0527636,
    -0.00402649,
    0.103338,
    0.261261,
    0.491084,
    0.857966,
    1.19495,
    1.75071,
    2.65559,
    3.35433,
    5.48835
      };

      static double p1_expoP[5] = {
    1.42463e-01,
    4.18966e-02,
    1.12697e-01,
    1.66197e-01,
    1.50768e-01
      };

      static double p2_expoP[5] = {
    1.98758,
    2.27217,
    2.26799,
    2.38455,
    2.52428
      };

      // initialize weights based on desired Shift



      for (int ibin=0;ibin<20;ibin++) {

    if( Shift < .0) {
      Pweight_[ibin] = p0_minus[ibin] + p1_minus[ibin]*Shift + p2_minus[ibin]*Shift*Shift;
    }
    else {
      Pweight_[ibin] = p0_plus[ibin] + p1_plus[ibin]*Shift + p2_plus[ibin]*Shift*Shift;
    }
      }

      // last few bins fit better to an exponential...

      for (int ibin=20;ibin<25;ibin++) {
    if( Shift < 0.) {
      Pweight_[ibin] = p1_expoM[ibin-20]*exp(p2_expoM[ibin-20]*Shift);
    }
    else {
      Pweight_[ibin] = p1_expoP[ibin-20]*exp(p2_expoP[ibin-20]*Shift);
    }
      } 

    };

    double ShiftWeight( int ibin ) {

      if(ibin<25 && ibin>=0) { return Pweight_[ibin]; }
      else { return 0;}

    };

    double ShiftWeight( float pvnum ) {

      int ibin = int(pvnum);

      if(ibin<25 && ibin>=0) { return Pweight_[ibin]; }
      else { return 0;}

    };

  private:

    double Pweight_[25];

  };


  class LumiReWeighting {
  public:

    LumiReWeighting ( ) { } ;

    LumiReWeighting( std::string generatedFile,
             std::string dataFile,
             std::string GenHistName,
             std::string DataHistName) :
      generatedFileName_( generatedFile), 
      dataFileName_     ( dataFile ), 
      GenHistName_      ( GenHistName ), 
      DataHistName_     ( DataHistName )
    {
      generatedFile_ = new TFile( generatedFileName_.c_str() ) ; //MC distribution
      dataFile_      = new TFile( dataFileName_.c_str() );       //Data distribution

      Data_distr_ = new TH1(  *(static_cast<TH1*>(dataFile_->Get( DataHistName_.c_str() )->Clone() )) );
      MC_distr_ = new TH1(  *(static_cast<TH1*>(generatedFile_->Get( GenHistName_.c_str() )->Clone() )) );

      // normalize both histograms first                                                                            

      Data_distr_->Scale( 1.0/ Data_distr_->Integral() );
      MC_distr_->Scale( 1.0/ MC_distr_->Integral() );

      weights_ = new TH1( *(Data_distr_)) ;

      // MC * data/MC = data, so the weights are data/MC:

      weights_->SetName("lumiWeights");

      TH1* den = new TH1(*(MC_distr_));

      weights_->Divide( den );  // so now the average weight should be 1.0

      std::cout << " Lumi/Pileup Reweighting: Computed Weights per In-Time Nint " << std::endl;

      int NBins = weights_->GetNbinsX();

      for(int ibin = 1; ibin<NBins+1; ++ibin){
        std::cout << "   " << ibin-1 << " " << weights_->GetBinContent(ibin) << std::endl;
      }

      weightOOT_init();

      FirstWarning_ = true;

    }

    
      LumiReWeighting( std::vector< float > MC_distr, std::vector< float > Lumi_distr){
    // no histograms for input: use vectors
  
    // now, make histograms out of them:

    // first, check they are the same size...

    if( MC_distr.size() != Lumi_distr.size() ){   

      std::cerr <<"ERROR: LumiReWeighting: input vectors have different sizes. Quitting... \n";
      return;

    }

    Int_t NBins = MC_distr.size();

    MC_distr_ = new TH1F("MC_distr","MC dist",NBins,-0.5, float(NBins)-0.5);
    Data_distr_ = new TH1F("Data_distr","Data dist",NBins,-0.5, float(NBins)-0.5);

    weights_ = new TH1F("luminumer","luminumer",NBins,-0.5, float(NBins)-0.5);
    TH1* den = new TH1F("lumidenom","lumidenom",NBins,-0.5, float(NBins)-0.5);

    for(int ibin = 1; ibin<NBins+1; ++ibin ) {
      weights_->SetBinContent(ibin, Lumi_distr[ibin-1]);
      Data_distr_->SetBinContent(ibin, Lumi_distr[ibin-1]);
      den->SetBinContent(ibin,MC_distr[ibin-1]);
      MC_distr_->SetBinContent(ibin,MC_distr[ibin-1]);
    }

    // check integrals, make sure things are normalized

    float deltaH = weights_->Integral();
    if(fabs(1.0 - deltaH) > 0.02 ) { //*OOPS*...
      weights_->Scale( 1.0/ deltaH );
      Data_distr_->Scale( 1.0/ deltaH );
    }
    float deltaMC = den->Integral();
    if(fabs(1.0 - deltaMC) > 0.02 ) {
      den->Scale(1.0/ deltaMC );
      MC_distr_->Scale(1.0/ deltaMC );
    }

    weights_->Divide( den );  // so now the average weight should be 1.0    

    std::cout << " Lumi/Pileup Reweighting: Computed Weights per In-Time Nint " << std::endl;

    for(int ibin = 1; ibin<NBins+1; ++ibin){
      std::cout << "   " << ibin-1 << " " << weights_->GetBinContent(ibin) << std::endl;
    }

    weightOOT_init();

    FirstWarning_ = true;

      }

      void weight3D_init( float ScaleFactor, std::string WeightOutputFile="") { 

    //create histogram to write output weights, save pain of generating them again...

    TH3D* WHist = new TH3D("WHist","3D weights",50,0.,50.,50,0.,50.,50,0.,50. );
    TH3D* DHist = new TH3D("DHist","3D weights",50,0.,50.,50,0.,50.,50,0.,50. );
    TH3D* MHist = new TH3D("MHist","3D weights",50,0.,50.,50,0.,50.,50,0.,50. );


    using std::min;

    if( MC_distr_->GetEntries() == 0 ) {
      std::cout << " MC and Data distributions are not initialized! You must call the LumiReWeighting constructor. " << std::endl;
    }

    // arrays for storing number of interactions

    double MC_ints[50][50][50];
    double Data_ints[50][50][50];

    for (int i=0; i<50; i++) {
      for(int j=0; j<50; j++) {
        for(int k=0; k<50; k++) {
          MC_ints[i][j][k] = 0.;
          Data_ints[i][j][k] = 0.;
        }
      }
    }

    double factorial[50];
    double PowerSer[50];
    double base = 1.;

    factorial[0] = 1.;
    PowerSer[0]=1.;

    for (int i = 1; i<50; ++i) {
      base = base*float(i);
      factorial[i] = base;
    }


    double x;
    double xweight;
    double probi, probj, probk;
    double Expval, mean;
    int xi;

    // Get entries for Data, MC, fill arrays:                                                                                                 
    int NMCbin = MC_distr_->GetNbinsX();

    for (int jbin=1;jbin<NMCbin+1;jbin++) {
      x =  MC_distr_->GetBinCenter(jbin);
      xweight = MC_distr_->GetBinContent(jbin); //use as weight for matrix         

      //for Summer 11, we have this int feature:                      
      xi = int(x);

      // Generate Poisson distribution for each value of the mean     
      mean = double(xi);

      if(mean<0.) {
        std::cout << "LumiReweighting:BadInputValue" << " Your histogram generates MC luminosity values less than zero!"
                          << " Please Check.  Terminating." << std::endl;
      }


      if(mean==0.){
        Expval = 1.;
      }
      else {
        Expval = exp(-1.*mean);
      }

      base = 1.;

      for (int i = 1; i<50; ++i) {
        base = base*mean;
        PowerSer[i] = base; // PowerSer is mean^i                        
      }

      // compute poisson probability for each Nvtx in weight matrix      
      for (int i=0; i<50; i++) {
        probi = PowerSer[i]/factorial[i]*Expval;
        for(int j=0; j<50; j++) {
          probj = PowerSer[j]/factorial[j]*Expval;
          for(int k=0; k<50; k++) {
        probk = PowerSer[k]/factorial[k]*Expval;
        // joint probability is product of event weights multiplied by weight of input distribution bin                                   
        MC_ints[i][j][k] = MC_ints[i][j][k]+probi*probj*probk*xweight;
          }
        }
      }

    }

    int NDatabin = Data_distr_->GetNbinsX();

    for (int jbin=1;jbin<NDatabin+1;jbin++) {
      mean =  (Data_distr_->GetBinCenter(jbin))*ScaleFactor;
      xweight = Data_distr_->GetBinContent(jbin);

      // Generate poisson distribution for each value of the mean
      if(mean<0.) {
        std::cout << "LumiReweighting:BadInputValue" << " Your histogram generates MC luminosity values less than zero!"
                          << " Please Check.  Terminating." << std::endl;
      }

      if(mean==0.){
        Expval = 1.;
      }
      else {
        Expval = exp(-1.*mean);
      }

      base = 1.;

      for (int i = 1; i<50; ++i) {
        base = base*mean;
        PowerSer[i] = base;
      }

      // compute poisson probability for each Nvtx in weight matrix                                                                           

      for (int i=0; i<50; i++) {
        probi = PowerSer[i]/factorial[i]*Expval;
        for(int j=0; j<50; j++) {
          probj = PowerSer[j]/factorial[j]*Expval;
          for(int k=0; k<50; k++) {
        probk = PowerSer[k]/factorial[k]*Expval;
        // joint probability is product of event weights multiplied by weight of input distribution bin                                   
        Data_ints[i][j][k] = Data_ints[i][j][k]+probi*probj*probk*xweight;
          }
        }
      }

    }


    for (int i=0; i<50; i++) {
      //if(i<5) std::cout << "i = " << i << std::endl;                       
      for(int j=0; j<50; j++) {
        for(int k=0; k<50; k++) {
          if( (MC_ints[i][j][k])>0.) {
        Weight3D_[i][j][k]  =  Data_ints[i][j][k]/MC_ints[i][j][k];
          }
          else {
        Weight3D_[i][j][k]  = 0.;
          }
          WHist->SetBinContent( i+1,j+1,k+1,Weight3D_[i][j][k] );
          DHist->SetBinContent( i+1,j+1,k+1,Data_ints[i][j][k] );
          MHist->SetBinContent( i+1,j+1,k+1,MC_ints[i][j][k] );
          //      if(i<5 && j<5 && k<5) std::cout << Weight3D_[i][j][k] << " " ;    
        }
        //      if(i<5 && j<5) std::cout << std::endl;        
      }
    }

    if(! WeightOutputFile.empty() ) {
      std::cout << " 3D Weight Matrix initialized! " << std::endl;
      std::cout << " Writing weights to file " << WeightOutputFile << " for re-use...  " << std::endl;


      TFile * outfile = new TFile(WeightOutputFile.c_str(),"RECREATE");
      WHist->Write();
      MHist->Write();
      DHist->Write();
      outfile->Write();
      outfile->Close();
      outfile->Delete();
    }
    
    return;
      }


      void weight3D_set( std::string WeightFileName ) { 

    TFile *infile = new TFile(WeightFileName.c_str());
    TH1F *WHist = (TH1F*)infile->Get("WHist");

    // Check if the histogram exists           
    if (!WHist) {
      std::cout << " Could not find the histogram WHist in the file "
                            << "in the file " << WeightFileName << "." << std::endl;
      return;
    }

    for (int i=0; i<50; i++) {  
      for(int j=0; j<50; j++) {
        for(int k=0; k<50; k++) {
          Weight3D_[i][j][k] = WHist->GetBinContent(i,j,k);
        }
      }
    }

    std::cout << " 3D Weight Matrix initialized! " << std::endl;

    return;


      }



      void weightOOT_init() {

    // The following are poisson distributions with different means, where the maximum
    // of the function has been normalized to weight 1.0
    // These are used to reweight the out-of-time pileup to match the in-time distribution.
    // The total event weight is the product of the in-time weight, the out-of-time weight,
    // and a residual correction to fix the distortions caused by the fact that the out-of-time
    // distribution is not flat.

    static double weight_24[25] = {
      0,
      0,
      0,
      0,
      2.46277e-06,
      2.95532e-05,
      0.000104668,
      0.000401431,
      0.00130034,
      0.00342202,
      0.00818132,
      0.0175534,
      0.035784,
      0.0650836,
      0.112232,
      0.178699,
      0.268934,
      0.380868,
      0.507505,
      0.640922,
      0.768551,
      0.877829,
      0.958624,
      0.99939,
      1
    };

    static double weight_23[25] = {
      0,
      1.20628e-06,
      1.20628e-06,
      2.41255e-06,
      1.20628e-05,
      6.39326e-05,
      0.000252112,
      0.000862487,
      0.00244995,
      0.00616527,
      0.0140821,
      0.0293342,
      0.0564501,
      0.100602,
      0.164479,
      0.252659,
      0.36268,
      0.491427,
      0.627979,
      0.75918,
      0.873185,
      0.957934,
      0.999381,
      1,
      0.957738
    };

    static double weight_22[25] = {
      0,
      0,
      0,
      5.88636e-06,
      3.0609e-05,
      0.000143627,
      0.000561558,
      0.00173059,
      0.00460078,
      0.0110616,
      0.0238974,
      0.0475406,
      0.0875077,
      0.148682,
      0.235752,
      0.343591,
      0.473146,
      0.611897,
      0.748345,
      0.865978,
      0.953199,
      0.997848,
      1,
      0.954245,
      0.873688
    };

    static double weight_21[25] = {
      0,
      0,
      1.15381e-06,
      8.07665e-06,
      7.1536e-05,
      0.000280375,
      0.00107189,
      0.00327104,
      0.00809396,
      0.0190978,
      0.0401894,
      0.0761028,
      0.13472,
      0.216315,
      0.324649,
      0.455125,
      0.598241,
      0.739215,
      0.861866,
      0.953911,
      0.998918,
      1,
      0.956683,
      0.872272,
      0.76399
    };
 
 
    static double weight_20[25] = {
      0,
      0,
      1.12532e-06,
      2.58822e-05,
      0.000145166,
      0.000633552,
      0.00215048,
      0.00592816,
      0.0145605,
      0.0328367,
      0.0652649,
      0.11893,
      0.19803,
      0.305525,
      0.436588,
      0.581566,
      0.727048,
      0.8534,
      0.949419,
      0.999785,
      1,
      0.953008,
      0.865689,
      0.753288,
      0.62765
    }; 
    static double weight_19[25] = {
      0,
      0,
      1.20714e-05,
      5.92596e-05,
      0.000364337,
      0.00124994,
      0.00403953,
      0.0108149,
      0.025824,
      0.0544969,
      0.103567,
      0.17936,
      0.283532,
      0.416091,
      0.562078,
      0.714714,
      0.846523,
      0.947875,
      1,
      0.999448,
      0.951404,
      0.859717,
      0.742319,
      0.613601,
      0.48552
    };

    static double weight_18[25] = {
      0,
      3.20101e-06,
      2.88091e-05,
      0.000164319,
      0.000719161,
      0.00250106,
      0.00773685,
      0.0197513,
      0.0443693,
      0.0885998,
      0.159891,
      0.262607,
      0.392327,
      0.543125,
      0.69924,
      0.837474,
      0.943486,
      0.998029,
      1,
      0.945937,
      0.851807,
      0.729309,
      0.596332,
      0.467818,
      0.350434
    };

 
    static double weight_17[25] = {
      1.03634e-06,
      7.25437e-06,
      4.97443e-05,
      0.000340956,
      0.00148715,
      0.00501485,
      0.0143067,
      0.034679,
      0.0742009,
      0.140287,
      0.238288,
      0.369416,
      0.521637,
      0.682368,
      0.828634,
      0.939655,
      1,
      0.996829,
      0.94062,
      0.841575,
      0.716664,
      0.582053,
      0.449595,
      0.331336,
      0.234332
    };

 
    static double weight_16[25] = {
      4.03159e-06,
      2.41895e-05,
      0.000141106,
      0.00081942,
      0.00314565,
      0.00990662,
      0.026293,
      0.0603881,
      0.120973,
      0.214532,
      0.343708,
      0.501141,
      0.665978,
      0.820107,
      0.938149,
      1,
      0.99941,
      0.940768,
      0.837813,
      0.703086,
      0.564023,
      0.42928,
      0.312515,
      0.216251,
      0.14561
    };
 
 
    static double weight_15[25] = {
      9.76084e-07,
      5.07564e-05,
      0.000303562,
      0.00174036,
      0.00617959,
      0.0188579,
      0.047465,
      0.101656,
      0.189492,
      0.315673,
      0.474383,
      0.646828,
      0.809462,
      0.934107,
      0.998874,
      1,
      0.936163,
      0.827473,
      0.689675,
      0.544384,
      0.40907,
      0.290648,
      0.198861,
      0.12951,
      0.0808051
    };
 
 
    static double weight_14[25] = {
      1.13288e-05,
      0.000124617,
      0.000753365,
      0.00345056,
      0.0123909,
      0.0352712,
      0.0825463,
      0.16413,
      0.287213,
      0.44615,
      0.625826,
      0.796365,
      0.930624,
      0.999958,
      1,
      0.934414,
      0.816456,
      0.672939,
      0.523033,
      0.386068,
      0.269824,
      0.180342,
      0.114669,
      0.0698288,
      0.0406496
    };

 
    static double weight_13[25] = {
      2.54296e-05,
      0.000261561,
      0.00167018,
      0.00748083,
      0.0241308,
      0.0636801,
      0.138222,
      0.255814,
      0.414275,
      0.600244,
      0.779958,
      0.92256,
      0.999155,
      1,
      0.927126,
      0.804504,
      0.651803,
      0.497534,
      0.35976,
      0.245834,
      0.160904,
      0.0991589,
      0.0585434,
      0.0332437,
      0.0180159
    };

    static double weight_12[25] = {
      5.85742e-05,
      0.000627706,
      0.00386677,
      0.0154068,
      0.0465892,
      0.111683,
      0.222487,
      0.381677,
      0.5719,
      0.765001,
      0.915916,
      1,
      0.999717,
      0.921443,
      0.791958,
      0.632344,
      0.475195,
      0.334982,
      0.223666,
      0.141781,
      0.0851538,
      0.048433,
      0.0263287,
      0.0133969,
      0.00696683
    };

 
    static double weight_11[25] = {
      0.00015238,
      0.00156064,
      0.00846044,
      0.0310939,
      0.0856225,
      0.187589,
      0.343579,
      0.541892,
      0.74224,
      0.909269,
      0.998711,
      1,
      0.916889,
      0.77485,
      0.608819,
      0.447016,
      0.307375,
      0.198444,
      0.121208,
      0.070222,
      0.0386492,
      0.0201108,
      0.0100922,
      0.00484937,
      0.00222458
    };

    static double weight_10[25] = {
      0.000393044,
      0.00367001,
      0.0179474,
      0.060389,
      0.151477,
      0.302077,
      0.503113,
      0.720373,
      0.899568,
      1,
      0.997739,
      0.909409,
      0.75728,
      0.582031,
      0.415322,
      0.277663,
      0.174147,
      0.102154,
      0.0566719,
      0.0298642,
      0.0147751,
      0.00710995,
      0.00319628,
      0.00140601,
      0.000568796
    };

 
    static double weight_9[25] = {
      0.00093396,
      0.00854448,
      0.0380306,
      0.113181,
      0.256614,
      0.460894,
      0.690242,
      0.888781,
      1,
      0.998756,
      0.899872,
      0.735642,
      0.552532,
      0.382726,
      0.246114,
      0.147497,
      0.0825541,
      0.0441199,
      0.0218157,
      0.0103578,
      0.00462959,
      0.0019142,
      0.000771598,
      0.000295893,
      0.000111529
    };

 
    static double weight_8[25] = {
      0.00240233,
      0.0192688,
      0.0768653,
      0.205008,
      0.410958,
      0.65758,
      0.875657,
      0.999886,
      1,
      0.889476,
      0.711446,
      0.517781,
      0.345774,
      0.212028,
      0.121208,
      0.0644629,
      0.0324928,
      0.0152492,
      0.00673527,
      0.0028547,
      0.00117213,
      0.000440177,
      0.000168471,
      5.80689e-05,
      1.93563e-05
    };

    static double weight_7[25] = {
      0.00617233,
      0.0428714,
      0.150018,
      0.350317,
      0.612535,
      0.856525,
      0.999923,
      1,
      0.87544,
      0.679383,
      0.478345,
      0.303378,
      0.176923,
      0.0950103,
      0.0476253,
      0.0222211,
      0.00972738,
      0.00392962,
      0.0015258,
      0.000559168,
      0.000183928,
      6.77983e-05,
      1.67818e-05,
      7.38398e-06,
      6.71271e-07
    };
 
    static double weight_6[25] = {
      0.0154465,
      0.0923472,
      0.277322,
      0.55552,
      0.833099,
      0.999035,
      1,
      0.855183,
      0.641976,
      0.428277,
      0.256804,
      0.139798,
      0.0700072,
      0.0321586,
      0.0137971,
      0.00544756,
      0.00202316,
      0.000766228,
      0.000259348,
      8.45836e-05,
      1.80362e-05,
      8.70713e-06,
      3.73163e-06,
      6.21938e-07,
      0
    };
 
 
    static double weight_5[25] = {
      0.0382845,
      0.191122,
      0.478782,
      0.797314,
      1,
      0.997148,
      0.831144,
      0.59461,
      0.371293,
      0.205903,
      0.103102,
      0.0471424,
      0.0194997,
      0.00749415,
      0.00273709,
      0.000879189,
      0.000286049,
      0.000102364,
      1.70606e-05,
      3.98081e-06,
      2.27475e-06,
      0,
      0,
      0,
      0
    };
 
 
    static double weight_4[25] = {
      0.0941305,
      0.373824,
      0.750094,
      1,
      0.997698,
      0.800956,
      0.532306,
      0.304597,
      0.152207,
      0.0676275,
      0.0270646,
      0.00975365,
      0.00326077,
      0.00101071,
      0.000301781,
      7.41664e-05,
      1.58563e-05,
      3.58045e-06,
      1.02299e-06,
      0,
      5.11493e-07,
      0,
      0,
      0,
      0
    };
 
 
    static double weight_3[25] = {
      0.222714,
      0.667015,
      1,
      0.999208,
      0.750609,
      0.449854,
      0.224968,
      0.0965185,
      0.0361225,
      0.012084,
      0.00359618,
      0.000977166,
      0.000239269,
      6.29422e-05,
      1.16064e-05,
      1.78559e-06,
      0,
      4.46398e-07,
      0,
      0,
      0,
      0,
      0,
      0,
      0
    };
 
    static double weight_2[25] = {
      0.499541,
      0.999607,
      1,
      0.666607,
      0.333301,
      0.13279,
      0.0441871,
      0.0127455,
      0.00318434,
      0.00071752,
      0.000132204,
      2.69578e-05,
      5.16999e-06,
      2.21571e-06,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0
    };
 
    static double weight_1[25] = {
      0.999165,
      1,
      0.499996,
      0.166868,
      0.0414266,
      0.00831053,
      0.00137472,
      0.000198911,
      2.66302e-05,
      2.44563e-06,
      2.71737e-07,
      2.71737e-07,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0
    };
 
    static double weight_0[25] = {
      1,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0,
      0
    };

    //WeightOOTPU_ = {0};

    double* WeightPtr = 0;

    for(int iint = 0; iint<25; ++iint){
      if(iint ==0) WeightPtr = weight_0;
      if(iint ==1) WeightPtr = weight_1;
      if(iint ==2) WeightPtr = weight_2;
      if(iint ==3) WeightPtr = weight_3;
      if(iint ==4) WeightPtr = weight_4;
      if(iint ==5) WeightPtr = weight_5;
      if(iint ==6) WeightPtr = weight_6;
      if(iint ==7) WeightPtr = weight_7;
      if(iint ==8) WeightPtr = weight_8;
      if(iint ==9) WeightPtr = weight_9;
      if(iint ==10) WeightPtr = weight_10;
      if(iint ==11) WeightPtr = weight_11;
      if(iint ==12) WeightPtr = weight_12;
      if(iint ==13) WeightPtr = weight_13;
      if(iint ==14) WeightPtr = weight_14;
      if(iint ==15) WeightPtr = weight_15;
      if(iint ==16) WeightPtr = weight_16;
      if(iint ==17) WeightPtr = weight_17;
      if(iint ==18) WeightPtr = weight_18;
      if(iint ==19) WeightPtr = weight_19;
      if(iint ==20) WeightPtr = weight_20;
      if(iint ==21) WeightPtr = weight_21;
      if(iint ==22) WeightPtr = weight_22;
      if(iint ==23) WeightPtr = weight_23;
      if(iint ==24) WeightPtr = weight_24;

      for(int ibin = 0; ibin<25; ++ibin){
        WeightOOTPU_[iint][ibin] = *(WeightPtr+ibin);
      }
    }

      }


      double ITweight( int npv ){
    int bin = weights_->GetXaxis()->FindBin( npv );
    return weights_->GetBinContent( bin );
      }

      double ITweight3BX( float ave_int ){
    int bin = weights_->GetXaxis()->FindBin( ave_int );
    return weights_->GetBinContent( bin );
      }

      double weight( float n_int ){
    int bin = weights_->GetXaxis()->FindBin( n_int );
    return weights_->GetBinContent( bin );
      }


      double weight3D( int pv1, int pv2, int pv3 ) {

    using std::min;

    int npm1 = min(pv1,34);
    int np0 = min(pv2,34);
    int npp1 = min(pv3,34);

    return Weight3D_[npm1][np0][npp1];

      }



      double weightOOT( int npv_in_time, int npv_m50nsBX ){

    static double Correct_Weights2011[25] = { // residual correction to match lumi spectrum
      5.30031,
      2.07903,
      1.40729,
      1.27687,
      1.0702,
      0.902094,
      0.902345,
      0.931449,
      0.78202,
      0.824686,
      0.837735,
      0.910261,
      1.01394,
      1.1599,
      1.12778,
      1.58423,
      1.78868,
      1.58296,
      2.3291,
      3.86641,
      0,
      0,
      0,
      0,
      0
    };                        


    if(FirstWarning_) {

      std::cout << " **** Warning: Out-of-time pileup reweighting appropriate only for PU_S3 **** " << std::endl;
      std::cout << " ****                          will be applied                           **** " << std::endl;

      FirstWarning_ = false;

    }


    // Note: for the "uncorrelated" out-of-time pileup, reweighting is only done on the 50ns
    // "late" bunch (BX=+1), since that is basically the only one that matters in terms of 
    // energy deposition.  

    if(npv_in_time < 0) {
      std::cerr << " no in-time beam crossing found\n! " ;
      std::cerr << " Returning event weight=0\n! ";
      return 0.;
    }
    if(npv_m50nsBX < 0) {
      std::cerr << " no out-of-time beam crossing found\n! " ;
      std::cerr << " Returning event weight=0\n! ";
      return 0.;
    }

    int bin = weights_->GetXaxis()->FindBin( npv_in_time );

    double inTimeWeight = weights_->GetBinContent( bin );

    double TotalWeight = 1.0;


    TotalWeight = inTimeWeight * WeightOOTPU_[bin-1][npv_m50nsBX] * Correct_Weights2011[bin-1];


    return TotalWeight;
 
      }

  protected:

      std::string generatedFileName_;
      std::string dataFileName_;
      std::string GenHistName_;
      std::string DataHistName_;
      TFile *generatedFile_;
      TFile *dataFile_;
      TH1  *weights_;

      //keep copies of normalized distributions:                                                                                  
      TH1*      MC_distr_;
      TH1*      Data_distr_;

      double WeightOOTPU_[25][25];
      double Weight3D_[50][50][50];

      bool FirstWarning_;


  };
}



#endif