Back to home page

Project CMSSW displayed by LXR

 
 

    


File indexing completed on 2021-02-14 13:33:32

0001 //+______________________________________________________________________________

0002 // Generate weights based on two input distributions, intended and generated

0003 
0004 
0005 #include <TF1.h>
0006 #include <TFile.h>
0007 #include <TH1F.h>
0008 #include <TCanvas.h>
0009 
0010 
0011 void Reweight_Gen() {
0012 
0013  TH1F* PU_intended = new TH1F("PU_intended","Intended pileup distribution (i.e. Data)",25,-0.5,24.5);
0014  TH1F* PU_generated = new TH1F("PU_generated","Generated pileup distribution (i.e., MC)",25,-0.5,24.5);
0015 
0016 
0017   double x;
0018 
0019   // "Flat10+Tail distribution taken directly from MixingModule input

0020 
0021   Double_t probdistFlat10[25] = {
0022     0.0698146584,
0023     0.0698146584,
0024     0.0698146584,
0025     0.0698146584,
0026     0.0698146584,
0027     0.0698146584,
0028     0.0698146584,
0029     0.0698146584,
0030     0.0698146584,
0031     0.0698146584,
0032     0.0698146584,
0033     0.0630151648,
0034     0.0526654164,
0035     0.0402754482,
0036     0.0292988928,
0037     0.0194384503,
0038     0.0122016783,
0039     0.007207042,
0040     0.004003637,
0041     0.0020278322,
0042     0.0010739954,
0043     0.0004595759,
0044     0.0002229748,
0045     0.0001028162,
0046     4.58337152809607E-05
0047   };
0048 
0049   // "Lumpy" distribution taken from PU_S3 Summer11 samples (also consistent with Spring11)

0050 
0051   Double_t probdist_Lumpy[25] = {
0052     0.073050961,
0053     0.073282135,
0054     0.06588457,
0055     0.07120157,
0056     0.064497526,
0057     0.073513309,
0058     0.078136788,
0059     0.073050961,
0060     0.066809265,
0061     0.073050961,
0062     0.06588457,
0063     0.060105221,
0064     0.049702395,
0065     0.03352022,
0066     0.029821437,
0067     0.018725088,
0068     0.012483392,
0069     0.008322261,
0070     0.002774087,
0071     0.002774087,
0072     0.001849391,
0073     0.000870009,
0074     0.000372861,
0075     0.000211288,
0076     0.000105644,
0077   }
0078 
0079   // alternate lumpy scenario, also from Summer11 SU_P3 samples

0080 
0081   Double_t probdist_Lumpy2[25] = {
0082     0.0662635239567,
0083     0.0749768160742,
0084     0.0644551777434,
0085     0.0768663060278,
0086     0.0675077279753,
0087     0.0712751159196,
0088     0.0687384080371,
0089     0.0680486862442,
0090     0.064364374034,
0091     0.0756530139104,
0092     0.0686843122102,
0093     0.0662480680062,
0094     0.0544165378671,
0095     0.0318933539413,
0096     0.0268682380216,
0097     0.0193836939722,
0098     0.0162635239567,
0099     0.0112364760433,
0100     0.00311244204019,
0101     0.00312017001546,
0102     0.000624034003091,
0103     0.0004,
0104     0.0002,
0105     0.0001,
0106     0.00004
0107   };
0108 
0109   // Summer11 PU_S4, distribution obtained by averaging the number of interactions

0110   // in each beam crossing to estimate the true mean

0111 
0112   Double_t PoissonIntDist[25] = {
0113     0.104109,
0114     0.0703573,
0115     0.0698445,
0116     0.0698254,
0117     0.0697054,
0118     0.0697907,
0119     0.0696751,
0120     0.0694486,
0121     0.0680332,
0122     0.0651044,
0123     0.0598036,
0124     0.0527395,
0125     0.0439513,
0126     0.0352202,
0127     0.0266714,
0128     0.019411,
0129     0.0133974,
0130     0.00898536,
0131     0.0057516,
0132     0.00351493,
0133     0.00212087,
0134     0.00122891,
0135     0.00070592,
0136     0.000384744,
0137     0.000219377
0138   };
0139 
0140   // Summer11 PU_S4, distribution obtained by only looking at the in-time crossing.

0141 
0142   Double_t PoissonOneXDist[25] = {
0143     0.14551,
0144     0.0644453,
0145     0.0696412,
0146     0.0700311,
0147     0.0694257,
0148     0.0685655,
0149     0.0670929,
0150     0.0646049,
0151     0.0609383,
0152     0.0564597,
0153     0.0508014,
0154     0.0445226,
0155     0.0378796,
0156     0.0314746,
0157     0.0254139,
0158     0.0200091,
0159     0.0154191,
0160     0.0116242,
0161     0.00846857,
0162     0.00614328,
0163     0.00426355,
0164     0.00300632,
0165     0.00203485,
0166     0.00133045,
0167     0.000893794
0168   };
0169 
0170   // luminosity distribution from estimatePileup.py for May 10 JSON Muon file

0171 
0172   Double_t TrueDist2011[25] = {
0173     0.019091,
0174     0.0293974,
0175     0.0667931,
0176     0.108859,
0177     0.139533,
0178     0.149342,
0179     0.138629,
0180     0.114582,
0181     0.0859364,
0182     0.059324,
0183     0.0381123,
0184     0.0229881,
0185     0.0131129,
0186     0.00711764,
0187     0.00369635,
0188     0.00184543,
0189     0.000889604,
0190     0.000415683,
0191     0.000188921,
0192     0.000146288,
0193     0.0,
0194     0.0,
0195     0.0,
0196     0.0,
0197     0.0
0198   };
0199 
0200   //Fill histograms with one generated, one desired distribution

0201   
0202   for (int i=1;i<26;i++) {
0203     PU_generated->SetBinContent(i,probdistFlat10[i-1]);
0204     PU_intended->SetBinContent(i,TrueDist2011[i-1]);
0205   }
0206 
0207   TCanvas *can1 = new TCanvas("can1,","can1",1200,800);
0208   can1->Divide(2,2);
0209 
0210   can1->cd(1);
0211   PU_generated->SetLineColor(kRed);
0212   PU_intended->SetLineColor(kBlue);
0213 
0214   PU_intended->Draw();
0215   PU_generated->Draw("Same");
0216 
0217 
0218   can1->cd(2);
0219   PU_generated->Draw();
0220 
0221 
0222   can1->cd(3);
0223   PU_intended->DrawNormalized();
0224 
0225   TCanvas *can2 = new TCanvas("can2,","can2",1200,800);
0226 
0227   TH1F* PUnorm = dynamic_cast<TH1F*>(PU_intended->DrawNormalized());
0228 
0229   TH1F* Quotient = PUnorm;
0230 
0231   Quotient->Divide(PUnorm,PU_generated,1.0,1.0);
0232 
0233   std::cout << "Bin Contents" << std::endl;
0234 
0235   for(int ibin=1; ibin<26; ibin++){
0236 
0237     x = Quotient->GetBinContent(ibin);
0238 
0239       std::cout << ibin-1 << " " << x << std::endl;
0240     //std::cout <<  " " << x << "," <<  std::endl;

0241 
0242   }
0243 
0244   Quotient->SetNameTitle("Computed Weights","Computed Weights");
0245   Quotient->Draw();
0246 
0247 }
0248