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// plot the variables
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#include "TROOT.h"
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#include "TMath.h"
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#include "TTree.h"
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#include "TArrayD.h"
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#include "TStyle.h"
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#include "TFile.h"
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#include "TRandom.h"
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#include "Riostream.h"
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#include "TCanvas.h"
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#include "TMatrixD.h"
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#include "TH2F.h"
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#include "TLegend.h"
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#include "TBranch.h"
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#include <vector>
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void plot( TString fname = "data.root", TString var0="var0", TString var1="var1" )
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{
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TFile* dataFile = TFile::Open( fname );
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if (!dataFile) {
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cout << "ERROR: cannot open file: " << fname << endl;
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return;
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}
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TTree *treeS = (TTree*)dataFile->Get("TreeS");
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TTree *treeB = (TTree*)dataFile->Get("TreeB");
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TCanvas* c = new TCanvas( "c", "", 0, 0, 550, 550 );
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TStyle *TMVAStyle = gROOT->GetStyle("Plain"); // our style is based on Plain
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TMVAStyle->SetOptStat(0);
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TMVAStyle->SetPadTopMargin(0.02);
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TMVAStyle->SetPadBottomMargin(0.16);
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TMVAStyle->SetPadRightMargin(0.03);
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TMVAStyle->SetPadLeftMargin(0.15);
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TMVAStyle->SetPadGridX(0);
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TMVAStyle->SetPadGridY(0);
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TMVAStyle->SetOptTitle(0);
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TMVAStyle->SetTitleW(.4);
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TMVAStyle->SetTitleH(.10);
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TMVAStyle->SetTitleX(.5);
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TMVAStyle->SetTitleY(.9);
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TMVAStyle->SetMarkerStyle(20);
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TMVAStyle->SetMarkerSize(1.6);
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TMVAStyle->cd();
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Float_t xmin = TMath::Min( treeS->GetMinimum( var0 ), treeB->GetMinimum( var0 ) );
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Float_t xmax = TMath::Max( treeS->GetMaximum( var0 ), treeB->GetMaximum( var0 ) );
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Float_t ymin = TMath::Min( treeS->GetMinimum( var1 ), treeB->GetMinimum( var1 ) );
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Float_t ymax = TMath::Max( treeS->GetMaximum( var1 ), treeB->GetMaximum( var1 ) );
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Int_t nbin = 500;
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TH2F* frameS = new TH2F( "DataS", "DataS", nbin, xmin, xmax, nbin, ymin, ymax );
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TH2F* frameB = new TH2F( "DataB", "DataB", nbin, xmin, xmax, nbin, ymin, ymax );
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// project trees
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treeS->Draw( Form("%s:%s>>DataS",var1.Data(),var0.Data()), "", "0" );
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treeB->Draw( Form("%s:%s>>DataB",var1.Data(),var0.Data()
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), "", "0" );
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// set style
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frameS->SetMarkerSize( 0.1 );
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frameS->SetMarkerColor( 4 );
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frameB->SetMarkerSize( 0.1 );
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frameB->SetMarkerColor( 2 );
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// legend
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frameS->SetTitle( var1+" versus "+var0+" for signal and background" );
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frameS->GetXaxis()->SetTitle( var0 );
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frameS->GetYaxis()->SetTitle( var1 );
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frameS->SetLabelSize( 0.04, "X" );
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frameS->SetLabelSize( 0.04, "Y" );
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frameS->SetTitleSize( 0.05, "X" );
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frameS->SetTitleSize( 0.05, "Y" );
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// and plot
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frameS->Draw();
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frameB->Draw( "same" );
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// Draw legend
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TLegend *legend = new TLegend( 1 - c->GetRightMargin() - 0.32, 1 - c->GetTopMargin() - 0.12,
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1 - c->GetRightMargin(), 1 - c->GetTopMargin() );
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legend->SetFillStyle( 1 );
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legend->AddEntry(frameS,"Signal","p");
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legend->AddEntry(frameB,"Background","p");
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legend->Draw("same");
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legend->SetBorderSize(1);
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legend->SetMargin( 0.3 );
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}
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TMatrixD* produceSqrtMat( const TMatrixD& covMat )
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{
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Double_t sum = 0;
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Int_t size = covMat.GetNrows();;
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TMatrixD* sqrtMat = new TMatrixD( size, size );
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for (Int_t i=0; i< size; i++) {
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sum = 0;
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for (Int_t j=0;j< i; j++) sum += (*sqrtMat)(i,j) * (*sqrtMat)(i,j);
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(*sqrtMat)(i,i) = TMath::Sqrt(TMath::Abs(covMat(i,i) - sum));
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for (Int_t k=i+1 ;k<size; k++) {
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sum = 0;
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for (Int_t l=0; l<i; l++) sum += (*sqrtMat)(k,l) * (*sqrtMat)(i,l);
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(*sqrtMat)(k,i) = (covMat(k,i) - sum) / (*sqrtMat)(i,i);
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}
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}
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return sqrtMat;
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}
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void getGaussRnd( TArrayD& v, const TMatrixD& sqrtMat, TRandom& R )
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{
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// generate "size" correlated Gaussian random numbers
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// sanity check
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const Int_t size = sqrtMat.GetNrows();
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if (size != v.GetSize())
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cout << "<getGaussRnd> too short input vector: " << size << " " << v.GetSize() << endl;
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Double_t* tmpVec = new Double_t[size];
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for (Int_t i=0; i<size; i++) {
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Double_t x, y, z;
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y = R.Rndm();
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z = R.Rndm();
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x = 2*TMath::Pi()*z;
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tmpVec[i] = TMath::Sin(x) * TMath::Sqrt(-2.0*TMath::Log(y));
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}
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for (Int_t i=0; i<size; i++) {
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v[i] = 0;
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for (Int_t j=0; j<=i; j++) v[i] += sqrtMat(i,j) * tmpVec[j];
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}
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delete tmpVec;
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}
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// create the data
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void create_lin_Nvar_withFriend(Int_t N = 2000)
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{
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const Int_t nvar = 4;
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const Int_t nvar2 = 1;
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Float_t xvar[nvar];
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// output flie
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TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
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// create signal and background trees
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TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
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TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
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for (Int_t ivar=0; ivar<nvar-nvar2; ivar++) {
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cout << "Creating branch var" << ivar+1 << " in signal tree" << endl;
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treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
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treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
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}
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TTree* treeSF = new TTree( "TreeSF", "TreeS", 1 );
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TTree* treeBF = new TTree( "TreeBF", "TreeB", 1 );
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for (Int_t ivar=nvar-nvar2; ivar<nvar; ivar++) {
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treeSF->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
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treeBF->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
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}
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TRandom R( 100 );
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Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
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Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
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Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
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TArrayD* v = new TArrayD( nvar );
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Float_t rho[20];
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rho[1*2] = 0.4;
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rho[1*3] = 0.6;
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rho[1*4] = 0.9;
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rho[2*3] = 0.7;
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rho[2*4] = 0.8;
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rho[3*4] = 0.93;
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// create covariance matrix
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TMatrixD* covMatS = new TMatrixD( nvar, nvar );
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TMatrixD* covMatB = new TMatrixD( nvar, nvar );
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for (Int_t ivar=0; ivar<nvar; ivar++) {
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(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
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(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
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for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
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(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
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(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
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(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
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(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
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}
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}
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cout << "signal covariance matrix: " << endl;
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covMatS->Print();
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cout << "background covariance matrix: " << endl;
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covMatB->Print();
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// produce the square-root matrix
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TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
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TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
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// loop over species
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for (Int_t itype=0; itype<2; itype++) {
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Float_t* x;
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TMatrixD* m;
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if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
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else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
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// event loop
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TTree* tree = (itype==0) ? treeS : treeB;
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TTree* treeF = (itype==0) ? treeSF : treeBF;
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for (Int_t i=0; i<N; i++) {
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if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
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getGaussRnd( *v, *m, R );
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for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
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tree->Fill();
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treeF->Fill();
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}
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}
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// treeS->AddFriend(treeSF);
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// treeB->AddFriend(treeBF);
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// write trees
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treeS->Write();
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treeB->Write();
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treeSF->Write();
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treeBF->Write();
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treeS->Show(0);
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treeB->Show(1);
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dataFile->Close();
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cout << "created data file: " << dataFile->GetName() << endl;
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}
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// create the tree
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TTree* makeTree_lin_Nvar( TString treeName, TString treeTitle, Float_t* x, Float_t* dx, const Int_t nvar, Int_t N )
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{
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Float_t xvar[nvar];
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// create tree
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TTree* tree = new TTree(treeName, treeTitle, 1);
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for (Int_t ivar=0; ivar<nvar; ivar++) {
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tree->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
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}
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TRandom R( 100 );
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TArrayD* v = new TArrayD( nvar );
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Float_t rho[20];
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rho[1*2] = 0.4;
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rho[1*3] = 0.6;
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rho[1*4] = 0.9;
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rho[2*3] = 0.7;
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rho[2*4] = 0.8;
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rho[3*4] = 0.93;
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// create covariance matrix
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TMatrixD* covMat = new TMatrixD( nvar, nvar );
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for (Int_t ivar=0; ivar<nvar; ivar++) {
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(*covMat)(ivar,ivar) = dx[ivar]*dx[ivar];
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for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
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(*covMat)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
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(*covMat)(jvar,ivar) = (*covMat)(ivar,jvar);
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}
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}
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//cout << "covariance matrix: " << endl;
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//covMat->Print();
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// produce the square-root matrix
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TMatrixD* sqrtMat = produceSqrtMat( *covMat );
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// event loop
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for (Int_t i=0; i<N; i++) {
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if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
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getGaussRnd( *v, *sqrtMat, R );
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for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
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tree->Fill();
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}
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// write trees
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// tree->Write();
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tree->Show(0);
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cout << "created tree: " << tree->GetName() << endl;
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return tree;
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}
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// create the data
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TTree* makeTree_circ(TString treeName, TString treeTitle, Int_t nvar = 2, Int_t N = 6000, Float_t radius = 1.0, Bool_t distort = false)
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{
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Int_t Nn = 0;
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Float_t xvar[nvar]; //variable array size does not work in interactive mode
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// create signal and background trees
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TTree* tree = new TTree( treeName, treeTitle, 1 );
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for (Int_t ivar=0; ivar<nvar; ivar++) {
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tree->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
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}
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TRandom R( 100 );
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//Float_t phimin = -30, phimax = 130;
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Float_t phimin = -70, phimax = 130;
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Float_t phisig = 5;
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Float_t rsig = 0.1;
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Float_t fnmin = -(radius+4.0*rsig);
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Float_t fnmax = +(radius+4.0*rsig);
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Float_t dfn = fnmax-fnmin;
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// event loop
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for (Int_t i=0; i<N; i++) {
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Double_t r1=R.Rndm(),r2=R.Rndm(), r3;
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r3= r1>r2? r1 :r2;
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Float_t phi;
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if (distort) phi = r3*(phimax - phimin) + phimin;
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else phi = R.Rndm()*(phimax - phimin) + phimin;
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phi += R.Gaus()*phisig;
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| 341 |
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| 342 |
Float_t r = radius;
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r += R.Gaus()*rsig;
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| 344 |
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xvar[0] = r*cos(TMath::DegToRad()*phi);
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xvar[1] = r*sin(TMath::DegToRad()*phi);
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| 347 |
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| 348 |
for( Int_t j = 2; j<nvar; ++j )
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xvar[j] = dfn*R.Rndm()+fnmin;
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| 350 |
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tree->Fill();
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}
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| 353 |
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| 354 |
for (Int_t i=0; i<Nn; i++) {
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xvar[0] = dfn*R.Rndm()+fnmin;
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xvar[1] = dfn*R.Rndm()+fnmin;
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| 358 |
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for( Int_t j = 2; j<nvar; ++j )
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| 360 |
xvar[j] = dfn*R.Rndm()+fnmin;
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| 362 |
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tree->Fill();
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}
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| 365 |
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tree->Show(0);
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| 367 |
// write trees
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cout << "created tree: " << tree->GetName() << endl;
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return tree;
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| 370 |
}
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| 371 |
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| 372 |
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| 373 |
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| 374 |
// create the data
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| 375 |
void create_lin_Nvar_2(Int_t N = 50000)
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| 376 |
{
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| 377 |
const int nvar = 4;
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| 378 |
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| 379 |
// output flie
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| 380 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
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| 381 |
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| 382 |
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| 383 |
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
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| 384 |
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
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| 385 |
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
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| 386 |
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| 387 |
// create signal and background trees
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| 388 |
TTree* treeS = makeTree_lin_Nvar( "TreeS", "Signal tree", xS, dx, nvar, N );
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| 389 |
TTree* treeB = makeTree_lin_Nvar( "TreeB", "Background tree", xB, dx, nvar, N );
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| 390 |
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| 391 |
treeS->Write();
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| 392 |
treeB->Write();
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| 393 |
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| 394 |
treeS->Show(0);
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| 395 |
treeB->Show(0);
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| 396 |
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| 397 |
dataFile->Close();
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| 398 |
cout << "created data file: " << dataFile->GetName() << endl;
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| 399 |
}
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| 400 |
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| 401 |
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| 402 |
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| 403 |
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| 404 |
// create the data
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| 405 |
void create_lin_Nvar(Int_t N = 50000)
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| 406 |
{
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| 407 |
const Int_t nvar = 4;
|
| 408 |
Float_t xvar[nvar];
|
| 409 |
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| 410 |
// output flie
|
| 411 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 412 |
|
| 413 |
// create signal and background trees
|
| 414 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 415 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 416 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 417 |
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 418 |
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 419 |
}
|
| 420 |
|
| 421 |
TRandom R( 100 );
|
| 422 |
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
|
| 423 |
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
|
| 424 |
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
|
| 425 |
TArrayD* v = new TArrayD( nvar );
|
| 426 |
Float_t rho[20];
|
| 427 |
rho[1*2] = 0.4;
|
| 428 |
rho[1*3] = 0.6;
|
| 429 |
rho[1*4] = 0.9;
|
| 430 |
rho[2*3] = 0.7;
|
| 431 |
rho[2*4] = 0.8;
|
| 432 |
rho[3*4] = 0.93;
|
| 433 |
|
| 434 |
// create covariance matrix
|
| 435 |
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
|
| 436 |
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
|
| 437 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 438 |
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 439 |
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 440 |
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
|
| 441 |
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 442 |
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
|
| 443 |
|
| 444 |
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 445 |
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
|
| 446 |
}
|
| 447 |
}
|
| 448 |
cout << "signal covariance matrix: " << endl;
|
| 449 |
covMatS->Print();
|
| 450 |
cout << "background covariance matrix: " << endl;
|
| 451 |
covMatB->Print();
|
| 452 |
|
| 453 |
// produce the square-root matrix
|
| 454 |
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
|
| 455 |
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
|
| 456 |
|
| 457 |
// loop over species
|
| 458 |
for (Int_t itype=0; itype<2; itype++) {
|
| 459 |
|
| 460 |
Float_t* x;
|
| 461 |
TMatrixD* m;
|
| 462 |
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
|
| 463 |
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
|
| 464 |
|
| 465 |
// event loop
|
| 466 |
TTree* tree = (itype==0) ? treeS : treeB;
|
| 467 |
for (Int_t i=0; i<N; i++) {
|
| 468 |
|
| 469 |
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
|
| 470 |
getGaussRnd( *v, *m, R );
|
| 471 |
|
| 472 |
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
|
| 473 |
|
| 474 |
tree->Fill();
|
| 475 |
}
|
| 476 |
}
|
| 477 |
|
| 478 |
// write trees
|
| 479 |
treeS->Write();
|
| 480 |
treeB->Write();
|
| 481 |
|
| 482 |
treeS->Show(0);
|
| 483 |
treeB->Show(1);
|
| 484 |
|
| 485 |
dataFile->Close();
|
| 486 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 487 |
}
|
| 488 |
|
| 489 |
// create the category data
|
| 490 |
// type = 1 (offset) or 2 (variable = -99)
|
| 491 |
void create_lin_Nvar_categories(Int_t N = 10000, Int_t type = 2)
|
| 492 |
{
|
| 493 |
const Int_t nvar = 4;
|
| 494 |
Float_t xvar[nvar];
|
| 495 |
Float_t eta;
|
| 496 |
|
| 497 |
// output flie
|
| 498 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 499 |
|
| 500 |
// create signal and background trees
|
| 501 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 502 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 503 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 504 |
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 505 |
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 506 |
}
|
| 507 |
|
| 508 |
// add category variable
|
| 509 |
treeS->Branch( "eta", &eta, "eta/F" );
|
| 510 |
treeB->Branch( "eta", &eta, "eta/F" );
|
| 511 |
|
| 512 |
TRandom R( 100 );
|
| 513 |
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
|
| 514 |
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
|
| 515 |
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
|
| 516 |
TArrayD* v = new TArrayD( nvar );
|
| 517 |
Float_t rho[20];
|
| 518 |
rho[1*2] = 0.0;
|
| 519 |
rho[1*3] = 0.0;
|
| 520 |
rho[1*4] = 0.0;
|
| 521 |
rho[2*3] = 0.0;
|
| 522 |
rho[2*4] = 0.0;
|
| 523 |
rho[3*4] = 0.0;
|
| 524 |
if (type != 1) {
|
| 525 |
rho[1*2] = 0.6;
|
| 526 |
rho[1*3] = 0.7;
|
| 527 |
rho[1*4] = 0.9;
|
| 528 |
rho[2*3] = 0.8;
|
| 529 |
rho[2*4] = 0.9;
|
| 530 |
rho[3*4] = 0.93;
|
| 531 |
}
|
| 532 |
|
| 533 |
// create covariance matrix
|
| 534 |
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
|
| 535 |
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
|
| 536 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 537 |
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 538 |
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 539 |
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
|
| 540 |
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 541 |
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
|
| 542 |
|
| 543 |
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 544 |
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
|
| 545 |
}
|
| 546 |
}
|
| 547 |
cout << "signal covariance matrix: " << endl;
|
| 548 |
covMatS->Print();
|
| 549 |
cout << "background covariance matrix: " << endl;
|
| 550 |
covMatB->Print();
|
| 551 |
|
| 552 |
// produce the square-root matrix
|
| 553 |
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
|
| 554 |
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
|
| 555 |
|
| 556 |
// loop over species
|
| 557 |
for (Int_t itype=0; itype<2; itype++) {
|
| 558 |
|
| 559 |
Float_t* x;
|
| 560 |
TMatrixD* m;
|
| 561 |
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
|
| 562 |
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
|
| 563 |
|
| 564 |
// event loop
|
| 565 |
TTree* tree = (itype==0) ? treeS : treeB;
|
| 566 |
for (Int_t i=0; i<N; i++) {
|
| 567 |
|
| 568 |
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
|
| 569 |
getGaussRnd( *v, *m, R );
|
| 570 |
|
| 571 |
eta = 2.5*2*(R.Rndm() - 0.5);
|
| 572 |
Float_t offset = 0;
|
| 573 |
if (type == 1) offset = TMath::Abs(eta) > 1.3 ? 0.8 : -0.8;
|
| 574 |
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar] + offset;
|
| 575 |
if (type != 1 && TMath::Abs(eta) > 1.3) xvar[nvar-1] = -5;
|
| 576 |
|
| 577 |
tree->Fill();
|
| 578 |
}
|
| 579 |
}
|
| 580 |
|
| 581 |
// write trees
|
| 582 |
treeS->Write();
|
| 583 |
treeB->Write();
|
| 584 |
|
| 585 |
treeS->Show(0);
|
| 586 |
treeB->Show(1);
|
| 587 |
|
| 588 |
dataFile->Close();
|
| 589 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 590 |
}
|
| 591 |
|
| 592 |
|
| 593 |
// create the data
|
| 594 |
void create_lin_Nvar_weighted(Int_t N = 10000, int WeightedSignal=0, int WeightedBkg=1)
|
| 595 |
{
|
| 596 |
const Int_t nvar = 4;
|
| 597 |
Float_t xvar[nvar];
|
| 598 |
Float_t weight;
|
| 599 |
|
| 600 |
|
| 601 |
cout << endl << endl << endl;
|
| 602 |
cout << "please use .L createData.C++ if you want to run this MC geneation" <<endl;
|
| 603 |
cout << "otherwise you will wait for ages!!! " << endl;
|
| 604 |
cout << endl << endl << endl;
|
| 605 |
|
| 606 |
|
| 607 |
// output flie
|
| 608 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 609 |
|
| 610 |
// create signal and background trees
|
| 611 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 612 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 613 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 614 |
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 615 |
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 616 |
}
|
| 617 |
if (WeightedSignal) treeS->Branch( "weight", &weight,"weight/F" );
|
| 618 |
if (WeightedBkg) treeB->Branch( "weight", &weight,"weight/F" );
|
| 619 |
|
| 620 |
TRandom R( 100 );
|
| 621 |
Float_t xS[nvar] = { 0.2, 0.3, 0.4, 0.8 };
|
| 622 |
Float_t xB[nvar] = { -0.2, -0.3, -0.4, -0.5 };
|
| 623 |
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
|
| 624 |
TArrayD* v = new TArrayD( nvar );
|
| 625 |
Float_t rho[20];
|
| 626 |
rho[1*2] = 0.4;
|
| 627 |
rho[1*3] = 0.6;
|
| 628 |
rho[1*4] = 0.9;
|
| 629 |
rho[2*3] = 0.7;
|
| 630 |
rho[2*4] = 0.8;
|
| 631 |
rho[3*4] = 0.93;
|
| 632 |
|
| 633 |
// create covariance matrix
|
| 634 |
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
|
| 635 |
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
|
| 636 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 637 |
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 638 |
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 639 |
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
|
| 640 |
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 641 |
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
|
| 642 |
|
| 643 |
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 644 |
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
|
| 645 |
}
|
| 646 |
}
|
| 647 |
cout << "signal covariance matrix: " << endl;
|
| 648 |
covMatS->Print();
|
| 649 |
cout << "background covariance matrix: " << endl;
|
| 650 |
covMatB->Print();
|
| 651 |
|
| 652 |
// produce the square-root matrix
|
| 653 |
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
|
| 654 |
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
|
| 655 |
|
| 656 |
// loop over species
|
| 657 |
for (Int_t itype=0; itype<2; itype++) {
|
| 658 |
|
| 659 |
Float_t* x;
|
| 660 |
TMatrixD* m;
|
| 661 |
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
|
| 662 |
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
|
| 663 |
|
| 664 |
// event loop
|
| 665 |
TTree* tree = (itype==0) ? treeS : treeB;
|
| 666 |
Int_t i=0;
|
| 667 |
do {
|
| 668 |
getGaussRnd( *v, *m, R );
|
| 669 |
|
| 670 |
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
|
| 671 |
// for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = R.Uniform()*10.-5.;
|
| 672 |
|
| 673 |
// weight = 0.5 / (TMath::Gaus( (xvar[nvar-1]-x[nvar-1]), 0, 1.1) );
|
| 674 |
// weight = TMath::Gaus(0.675,0,1) / (TMath::Gaus( (xvar[nvar-1]-x[nvar-1]), 0, 1.) );
|
| 675 |
weight = 0.8 / (TMath::Gaus( ((*v)[nvar-1]), 0, 1.09) );
|
| 676 |
Double_t tmp=R.Uniform()/0.00034;
|
| 677 |
if (itype==0 && !WeightedSignal) {
|
| 678 |
weight = 1;
|
| 679 |
tree->Fill();
|
| 680 |
i++;
|
| 681 |
} else if (itype==1 && !WeightedBkg) {
|
| 682 |
weight = 1;
|
| 683 |
tree->Fill();
|
| 684 |
i++;
|
| 685 |
}
|
| 686 |
else {
|
| 687 |
if (tmp < weight){
|
| 688 |
weight = 1./weight;
|
| 689 |
tree->Fill();
|
| 690 |
if (i%10 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
|
| 691 |
i++;
|
| 692 |
}
|
| 693 |
}
|
| 694 |
} while (i<N);
|
| 695 |
}
|
| 696 |
|
| 697 |
// write trees
|
| 698 |
treeS->Write();
|
| 699 |
treeB->Write();
|
| 700 |
|
| 701 |
treeS->Show(0);
|
| 702 |
treeB->Show(1);
|
| 703 |
|
| 704 |
TH1F *h[4];
|
| 705 |
TH1F *hw[4];
|
| 706 |
for (Int_t i=0;i<4;i++){
|
| 707 |
char buffer[5];
|
| 708 |
sprintf(buffer,"h%d",i);
|
| 709 |
h[i]= new TH1F(buffer,"",100,-5,5);
|
| 710 |
sprintf(buffer,"hw%d",i);
|
| 711 |
hw[i] = new TH1F(buffer,"",100,-5,5);
|
| 712 |
hw[i]->SetLineColor(3);
|
| 713 |
}
|
| 714 |
|
| 715 |
for (int ie=0;ie<treeS->GetEntries();ie++){
|
| 716 |
treeS->GetEntry(ie);
|
| 717 |
for (Int_t i=0;i<4;i++){
|
| 718 |
h[i]->Fill(xvar[i]);
|
| 719 |
hw[i]->Fill(xvar[i],weight);
|
| 720 |
}
|
| 721 |
}
|
| 722 |
|
| 723 |
TCanvas *c = new TCanvas("c","",800,800);
|
| 724 |
c->Divide(2,2);
|
| 725 |
|
| 726 |
for (Int_t i=0;i<4;i++){
|
| 727 |
c->cd(i+1);
|
| 728 |
h[i]->Draw();
|
| 729 |
hw[i]->Draw("same");
|
| 730 |
}
|
| 731 |
|
| 732 |
|
| 733 |
// dataFile->Close();
|
| 734 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 735 |
}
|
| 736 |
|
| 737 |
|
| 738 |
|
| 739 |
// create the data
|
| 740 |
void create_lin_Nvar_Arr(Int_t N = 1000)
|
| 741 |
{
|
| 742 |
const Int_t nvar = 4;
|
| 743 |
std::vector<float>* xvar[nvar];
|
| 744 |
|
| 745 |
// output flie
|
| 746 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 747 |
|
| 748 |
// create signal and background trees
|
| 749 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 750 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 751 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 752 |
xvar[ivar] = new std::vector<float>();
|
| 753 |
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), "vector<float>", &xvar[ivar], 64000, 1 );
|
| 754 |
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), "vector<float>", &xvar[ivar], 64000, 1 );
|
| 755 |
}
|
| 756 |
|
| 757 |
TRandom R( 100 );
|
| 758 |
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
|
| 759 |
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
|
| 760 |
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
|
| 761 |
TArrayD* v = new TArrayD( nvar );
|
| 762 |
Float_t rho[20];
|
| 763 |
rho[1*2] = 0.4;
|
| 764 |
rho[1*3] = 0.6;
|
| 765 |
rho[1*4] = 0.9;
|
| 766 |
rho[2*3] = 0.7;
|
| 767 |
rho[2*4] = 0.8;
|
| 768 |
rho[3*4] = 0.93;
|
| 769 |
|
| 770 |
// create covariance matrix
|
| 771 |
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
|
| 772 |
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
|
| 773 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 774 |
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 775 |
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 776 |
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
|
| 777 |
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 778 |
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
|
| 779 |
|
| 780 |
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 781 |
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
|
| 782 |
}
|
| 783 |
}
|
| 784 |
cout << "signal covariance matrix: " << endl;
|
| 785 |
covMatS->Print();
|
| 786 |
cout << "background covariance matrix: " << endl;
|
| 787 |
covMatB->Print();
|
| 788 |
|
| 789 |
// produce the square-root matrix
|
| 790 |
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
|
| 791 |
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
|
| 792 |
|
| 793 |
// loop over species
|
| 794 |
for (Int_t itype=0; itype<2; itype++) {
|
| 795 |
|
| 796 |
Float_t* x;
|
| 797 |
TMatrixD* m;
|
| 798 |
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
|
| 799 |
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
|
| 800 |
|
| 801 |
// event loop
|
| 802 |
TTree* tree = (itype==0) ? treeS : treeB;
|
| 803 |
for (Int_t i=0; i<N; i++) {
|
| 804 |
|
| 805 |
if (i%100 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
|
| 806 |
|
| 807 |
Int_t aSize = (Int_t)(gRandom->Rndm()*10); // size of array varies between events
|
| 808 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 809 |
xvar[ivar]->clear();
|
| 810 |
xvar[ivar]->reserve(aSize);
|
| 811 |
}
|
| 812 |
for(Int_t iA = 0; iA<aSize; iA++) {
|
| 813 |
//for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 814 |
getGaussRnd( *v, *m, R );
|
| 815 |
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar]->push_back((*v)[ivar] + x[ivar]);
|
| 816 |
//}
|
| 817 |
}
|
| 818 |
tree->Fill();
|
| 819 |
}
|
| 820 |
}
|
| 821 |
|
| 822 |
// write trees
|
| 823 |
treeS->Write();
|
| 824 |
treeB->Write();
|
| 825 |
|
| 826 |
treeS->Show(0);
|
| 827 |
treeB->Show(1);
|
| 828 |
|
| 829 |
dataFile->Close();
|
| 830 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 831 |
|
| 832 |
//plot();
|
| 833 |
}
|
| 834 |
|
| 835 |
|
| 836 |
|
| 837 |
// create the data
|
| 838 |
void create_lin_Nvar_double()
|
| 839 |
{
|
| 840 |
Int_t N = 10000;
|
| 841 |
const Int_t nvar = 4;
|
| 842 |
Double_t xvar[nvar];
|
| 843 |
Double_t xvarD[nvar];
|
| 844 |
Float_t xvarF[nvar];
|
| 845 |
|
| 846 |
// output flie
|
| 847 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 848 |
|
| 849 |
// create signal and background trees
|
| 850 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 851 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 852 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 853 |
if (ivar<2) {
|
| 854 |
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvarD[ivar], TString(Form( "var%i/D", ivar+1 )).Data() );
|
| 855 |
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvarD[ivar], TString(Form( "var%i/D", ivar+1 )).Data() );
|
| 856 |
}
|
| 857 |
else {
|
| 858 |
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvarF[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 859 |
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvarF[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 860 |
}
|
| 861 |
}
|
| 862 |
|
| 863 |
TRandom R( 100 );
|
| 864 |
Double_t xS[nvar] = { 0.2, 0.3, 0.5, 0.6 };
|
| 865 |
Double_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
|
| 866 |
Double_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
|
| 867 |
TArrayD* v = new TArrayD( nvar );
|
| 868 |
Double_t rho[20];
|
| 869 |
rho[1*2] = 0.4;
|
| 870 |
rho[1*3] = 0.6;
|
| 871 |
rho[1*4] = 0.9;
|
| 872 |
rho[2*3] = 0.7;
|
| 873 |
rho[2*4] = 0.8;
|
| 874 |
rho[3*4] = 0.93;
|
| 875 |
|
| 876 |
// create covariance matrix
|
| 877 |
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
|
| 878 |
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
|
| 879 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 880 |
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 881 |
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 882 |
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
|
| 883 |
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 884 |
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
|
| 885 |
|
| 886 |
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 887 |
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
|
| 888 |
}
|
| 889 |
}
|
| 890 |
cout << "signal covariance matrix: " << endl;
|
| 891 |
covMatS->Print();
|
| 892 |
cout << "background covariance matrix: " << endl;
|
| 893 |
covMatB->Print();
|
| 894 |
|
| 895 |
// produce the square-root matrix
|
| 896 |
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
|
| 897 |
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
|
| 898 |
|
| 899 |
// loop over species
|
| 900 |
for (Int_t itype=0; itype<2; itype++) {
|
| 901 |
|
| 902 |
Double_t* x;
|
| 903 |
TMatrixD* m;
|
| 904 |
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
|
| 905 |
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
|
| 906 |
|
| 907 |
// event loop
|
| 908 |
TTree* tree = (itype==0) ? treeS : treeB;
|
| 909 |
for (Int_t i=0; i<N; i++) {
|
| 910 |
|
| 911 |
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
|
| 912 |
getGaussRnd( *v, *m, R );
|
| 913 |
|
| 914 |
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
|
| 915 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 916 |
if (ivar<2) xvarD[ivar] = xvar[ivar];
|
| 917 |
else xvarF[ivar] = xvar[ivar];
|
| 918 |
}
|
| 919 |
|
| 920 |
tree->Fill();
|
| 921 |
}
|
| 922 |
}
|
| 923 |
|
| 924 |
// write trees
|
| 925 |
treeS->Write();
|
| 926 |
treeB->Write();
|
| 927 |
|
| 928 |
treeS->Show(0);
|
| 929 |
treeB->Show(1);
|
| 930 |
|
| 931 |
dataFile->Close();
|
| 932 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 933 |
|
| 934 |
plot();
|
| 935 |
}
|
| 936 |
|
| 937 |
// create the data
|
| 938 |
void create_lin_Nvar_discrete()
|
| 939 |
{
|
| 940 |
Int_t N = 10000;
|
| 941 |
const Int_t nvar = 4;
|
| 942 |
Float_t xvar[nvar];
|
| 943 |
Int_t xvarI[2];
|
| 944 |
|
| 945 |
// output flie
|
| 946 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 947 |
|
| 948 |
// create signal and background trees
|
| 949 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 950 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 951 |
for (Int_t ivar=0; ivar<nvar-2; ivar++) {
|
| 952 |
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 953 |
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 954 |
}
|
| 955 |
for (Int_t ivar=0; ivar<2; ivar++) {
|
| 956 |
treeS->Branch( TString(Form( "var%i", ivar+nvar-2+1 )).Data(), &xvarI[ivar], TString(Form( "var%i/I", ivar+nvar-2+1 )).Data() );
|
| 957 |
treeB->Branch( TString(Form( "var%i", ivar+nvar-2+1 )).Data(), &xvarI[ivar], TString(Form( "var%i/I", ivar+nvar-2+1 )).Data() );
|
| 958 |
}
|
| 959 |
|
| 960 |
TRandom R( 100 );
|
| 961 |
Float_t xS[nvar] = { 0.2, 0.3, 1, 2 };
|
| 962 |
Float_t xB[nvar] = { -0.2, -0.3, 0, 0 };
|
| 963 |
Float_t dx[nvar] = { 1.0, 1.0, 1, 2 };
|
| 964 |
TArrayD* v = new TArrayD( nvar );
|
| 965 |
Float_t rho[20];
|
| 966 |
rho[1*2] = 0.4;
|
| 967 |
rho[1*3] = 0.6;
|
| 968 |
rho[1*4] = 0.9;
|
| 969 |
rho[2*3] = 0.7;
|
| 970 |
rho[2*4] = 0.8;
|
| 971 |
rho[3*4] = 0.93;
|
| 972 |
// no correlations
|
| 973 |
for (int i=0; i<20; i++) rho[i] = 0;
|
| 974 |
|
| 975 |
// create covariance matrix
|
| 976 |
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
|
| 977 |
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
|
| 978 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 979 |
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 980 |
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 981 |
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
|
| 982 |
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 983 |
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
|
| 984 |
|
| 985 |
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 986 |
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
|
| 987 |
}
|
| 988 |
}
|
| 989 |
cout << "signal covariance matrix: " << endl;
|
| 990 |
covMatS->Print();
|
| 991 |
cout << "background covariance matrix: " << endl;
|
| 992 |
covMatB->Print();
|
| 993 |
|
| 994 |
// produce the square-root matrix
|
| 995 |
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
|
| 996 |
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
|
| 997 |
|
| 998 |
// loop over species
|
| 999 |
for (Int_t itype=0; itype<2; itype++) {
|
| 1000 |
|
| 1001 |
Float_t* x;
|
| 1002 |
TMatrixD* m;
|
| 1003 |
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
|
| 1004 |
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
|
| 1005 |
|
| 1006 |
// event loop
|
| 1007 |
TTree* tree = (itype==0) ? treeS : treeB;
|
| 1008 |
for (Int_t i=0; i<N; i++) {
|
| 1009 |
|
| 1010 |
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
|
| 1011 |
getGaussRnd( *v, *m, R );
|
| 1012 |
|
| 1013 |
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
|
| 1014 |
|
| 1015 |
xvarI[0] = TMath::Nint(xvar[nvar-2]);
|
| 1016 |
xvarI[1] = TMath::Nint(xvar[nvar-1]);
|
| 1017 |
|
| 1018 |
tree->Fill();
|
| 1019 |
}
|
| 1020 |
}
|
| 1021 |
|
| 1022 |
// write trees
|
| 1023 |
treeS->Write();
|
| 1024 |
treeB->Write();
|
| 1025 |
|
| 1026 |
treeS->Show(0);
|
| 1027 |
treeB->Show(1);
|
| 1028 |
|
| 1029 |
dataFile->Close();
|
| 1030 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1031 |
|
| 1032 |
plot();
|
| 1033 |
}
|
| 1034 |
|
| 1035 |
// create the data
|
| 1036 |
void create_ManyVars()
|
| 1037 |
{
|
| 1038 |
Int_t N = 20000;
|
| 1039 |
const Int_t nvar = 20;
|
| 1040 |
Float_t xvar[nvar];
|
| 1041 |
|
| 1042 |
// output flie
|
| 1043 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1044 |
|
| 1045 |
// create signal and background trees
|
| 1046 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1047 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1048 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1049 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1050 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1051 |
}
|
| 1052 |
|
| 1053 |
Float_t xS[nvar];
|
| 1054 |
Float_t xB[nvar];
|
| 1055 |
Float_t dx[nvar];
|
| 1056 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1057 |
xS[ivar] = 0 + ivar*0.05;
|
| 1058 |
xB[ivar] = 0 - ivar*0.05;
|
| 1059 |
dx[ivar] = 1;
|
| 1060 |
}
|
| 1061 |
|
| 1062 |
xS[0] = 0.2;
|
| 1063 |
xB[0] = -0.2;
|
| 1064 |
dx[0] = 1.0;
|
| 1065 |
xS[1] = 0.3;
|
| 1066 |
xB[1] = -0.3;
|
| 1067 |
dx[1] = 1.0;
|
| 1068 |
xS[2] = 0.4;
|
| 1069 |
xB[2] = -0.4;
|
| 1070 |
dx[2] = 1.0 ;
|
| 1071 |
xS[3] = 0.8 ;
|
| 1072 |
xB[3] = -0.5 ;
|
| 1073 |
dx[3] = 1.0 ;
|
| 1074 |
// TArrayD* v = new TArrayD( nvar );
|
| 1075 |
Float_t rho[20];
|
| 1076 |
rho[1*2] = 0.4;
|
| 1077 |
rho[1*3] = 0.6;
|
| 1078 |
rho[1*4] = 0.9;
|
| 1079 |
rho[2*3] = 0.7;
|
| 1080 |
rho[2*4] = 0.8;
|
| 1081 |
rho[3*4] = 0.93;
|
| 1082 |
|
| 1083 |
TRandom R( 100 );
|
| 1084 |
|
| 1085 |
// loop over species
|
| 1086 |
for (Int_t itype=0; itype<2; itype++) {
|
| 1087 |
|
| 1088 |
Float_t* x = (itype == 0) ? xS : xB;
|
| 1089 |
|
| 1090 |
// event loop
|
| 1091 |
TTree* tree = (itype == 0) ? treeS : treeB;
|
| 1092 |
for (Int_t i=0; i<N; i++) {
|
| 1093 |
|
| 1094 |
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
|
| 1095 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1096 |
if (ivar == 1500 && itype!=10) xvar[ivar] = 1;
|
| 1097 |
else xvar[ivar] = x[ivar] + R.Gaus()*dx[ivar];
|
| 1098 |
}
|
| 1099 |
|
| 1100 |
tree->Fill();
|
| 1101 |
}
|
| 1102 |
}
|
| 1103 |
|
| 1104 |
// write trees
|
| 1105 |
treeS->Write();
|
| 1106 |
treeB->Write();
|
| 1107 |
|
| 1108 |
treeS->Show(0);
|
| 1109 |
treeB->Show(1);
|
| 1110 |
|
| 1111 |
dataFile->Close();
|
| 1112 |
plot();
|
| 1113 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1114 |
}
|
| 1115 |
|
| 1116 |
// create the data
|
| 1117 |
void create_lin_NvarObsolete()
|
| 1118 |
{
|
| 1119 |
Int_t N = 20000;
|
| 1120 |
const Int_t nvar = 20;
|
| 1121 |
Float_t xvar[nvar];
|
| 1122 |
|
| 1123 |
// output flie
|
| 1124 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1125 |
|
| 1126 |
// create signal and background trees
|
| 1127 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1128 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1129 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1130 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1131 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1132 |
}
|
| 1133 |
|
| 1134 |
TRandom R( 100 );
|
| 1135 |
Float_t xS[nvar] = { 0.5, 0.5, 0.0, 0.0, 0.0, 0.0 };
|
| 1136 |
Float_t xB[nvar] = { -0.5, -0.5, -0.0, -0.0, -0.0, -0.0 };
|
| 1137 |
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 };
|
| 1138 |
TArrayD* v = new TArrayD( nvar );
|
| 1139 |
Float_t rho[50];
|
| 1140 |
for (Int_t i=0; i<50; i++) rho[i] = 0;
|
| 1141 |
rho[1*2] = 0.3;
|
| 1142 |
rho[1*3] = 0.0;
|
| 1143 |
rho[1*4] = 0.0;
|
| 1144 |
rho[2*3] = 0.0;
|
| 1145 |
rho[2*4] = 0.0;
|
| 1146 |
rho[3*4] = 0.0;
|
| 1147 |
|
| 1148 |
// create covariance matrix
|
| 1149 |
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
|
| 1150 |
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
|
| 1151 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1152 |
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 1153 |
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 1154 |
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
|
| 1155 |
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 1156 |
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
|
| 1157 |
|
| 1158 |
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 1159 |
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
|
| 1160 |
}
|
| 1161 |
}
|
| 1162 |
cout << "signal covariance matrix: " << endl;
|
| 1163 |
covMatS->Print();
|
| 1164 |
cout << "background covariance matrix: " << endl;
|
| 1165 |
covMatB->Print();
|
| 1166 |
|
| 1167 |
// produce the square-root matrix
|
| 1168 |
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
|
| 1169 |
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
|
| 1170 |
|
| 1171 |
// loop over species
|
| 1172 |
for (Int_t itype=0; itype<2; itype++) {
|
| 1173 |
|
| 1174 |
Float_t* x;
|
| 1175 |
TMatrixD* m;
|
| 1176 |
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
|
| 1177 |
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
|
| 1178 |
|
| 1179 |
// event loop
|
| 1180 |
TTree* tree = (itype==0) ? treeS : treeB;
|
| 1181 |
for (Int_t i=0; i<N; i++) {
|
| 1182 |
|
| 1183 |
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
|
| 1184 |
getGaussRnd( *v, *m, R );
|
| 1185 |
|
| 1186 |
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
|
| 1187 |
|
| 1188 |
tree->Fill();
|
| 1189 |
}
|
| 1190 |
}
|
| 1191 |
|
| 1192 |
// write trees
|
| 1193 |
treeS->Write();
|
| 1194 |
treeB->Write();
|
| 1195 |
|
| 1196 |
treeS->Show(0);
|
| 1197 |
treeB->Show(1);
|
| 1198 |
|
| 1199 |
dataFile->Close();
|
| 1200 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1201 |
|
| 1202 |
plot();
|
| 1203 |
}
|
| 1204 |
|
| 1205 |
// create the data
|
| 1206 |
void create_lin(Int_t N = 2000)
|
| 1207 |
{
|
| 1208 |
const Int_t nvar = 2;
|
| 1209 |
Double_t xvar[nvar];
|
| 1210 |
Float_t weight;
|
| 1211 |
|
| 1212 |
// output flie
|
| 1213 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1214 |
|
| 1215 |
// create signal and background trees
|
| 1216 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1217 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1218 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1219 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/D", ivar )).Data() );
|
| 1220 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/D", ivar )).Data() );
|
| 1221 |
}
|
| 1222 |
treeS->Branch( "weight", &weight, "weight/F" );
|
| 1223 |
treeB->Branch( "weight", &weight, "weight/F" );
|
| 1224 |
|
| 1225 |
TRandom R( 100 );
|
| 1226 |
Float_t xS[nvar] = { 0.0, 0.0 };
|
| 1227 |
Float_t xB[nvar] = { -0.0, -0.0 };
|
| 1228 |
Float_t dx[nvar] = { 1.0, 1.0 };
|
| 1229 |
TArrayD* v = new TArrayD( 2 );
|
| 1230 |
Float_t rhoS = 0.21;
|
| 1231 |
Float_t rhoB = 0.0;
|
| 1232 |
|
| 1233 |
// create covariance matrix
|
| 1234 |
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
|
| 1235 |
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
|
| 1236 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1237 |
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 1238 |
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 1239 |
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
|
| 1240 |
(*covMatS)(ivar,jvar) = rhoS*dx[ivar]*dx[jvar];
|
| 1241 |
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
|
| 1242 |
|
| 1243 |
(*covMatB)(ivar,jvar) = rhoB*dx[ivar]*dx[jvar];
|
| 1244 |
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
|
| 1245 |
}
|
| 1246 |
}
|
| 1247 |
cout << "signal covariance matrix: " << endl;
|
| 1248 |
covMatS->Print();
|
| 1249 |
cout << "background covariance matrix: " << endl;
|
| 1250 |
covMatB->Print();
|
| 1251 |
|
| 1252 |
// produce the square-root matrix
|
| 1253 |
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
|
| 1254 |
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
|
| 1255 |
|
| 1256 |
// loop over species
|
| 1257 |
for (Int_t itype=0; itype<2; itype++) {
|
| 1258 |
|
| 1259 |
Float_t* x;
|
| 1260 |
TMatrixD* m;
|
| 1261 |
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
|
| 1262 |
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
|
| 1263 |
|
| 1264 |
// event loop
|
| 1265 |
TTree* tree = (itype==0) ? treeS : treeB;
|
| 1266 |
for (Int_t i=0; i<N; i++) {
|
| 1267 |
|
| 1268 |
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
|
| 1269 |
getGaussRnd( *v, *m, R );
|
| 1270 |
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
|
| 1271 |
|
| 1272 |
// add weights
|
| 1273 |
if (itype == 0) weight = 1.0; // this is the signal weight
|
| 1274 |
else weight = 2.0; // this is the background weight
|
| 1275 |
|
| 1276 |
tree->Fill();
|
| 1277 |
}
|
| 1278 |
}
|
| 1279 |
|
| 1280 |
// write trees
|
| 1281 |
treeS->Write();
|
| 1282 |
treeB->Write();
|
| 1283 |
|
| 1284 |
treeS->Show(0);
|
| 1285 |
treeB->Show(1);
|
| 1286 |
|
| 1287 |
dataFile->Close();
|
| 1288 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1289 |
|
| 1290 |
plot();
|
| 1291 |
}
|
| 1292 |
|
| 1293 |
void create_fullcirc(Int_t nmax = 20000, Bool_t distort=false)
|
| 1294 |
{
|
| 1295 |
TFile* dataFile = TFile::Open( "circledata.root", "RECREATE" );
|
| 1296 |
int nvar = 2;
|
| 1297 |
int nsig = 0, nbgd=0;
|
| 1298 |
Float_t weight=1;
|
| 1299 |
Float_t xvar[100];
|
| 1300 |
// create signal and background trees
|
| 1301 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1302 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1303 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1304 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar)).Data() );
|
| 1305 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar)).Data() );
|
| 1306 |
}
|
| 1307 |
treeS->Branch("weight", &weight, "weight/F");
|
| 1308 |
treeB->Branch("weight", &weight, "weight/F");
|
| 1309 |
|
| 1310 |
TRandom R( 100 );
|
| 1311 |
do {
|
| 1312 |
for (Int_t ivar=0; ivar<nvar; ivar++) { xvar[ivar]=2.*R.Rndm()-1.;}
|
| 1313 |
Float_t xout = xvar[0]*xvar[0]+xvar[1]*xvar[1];
|
| 1314 |
if (nsig<10) cout << "xout = " << xout<<endl;
|
| 1315 |
if (xout < 0.3 || (xout >0.3 && xout<0.5 && R.Rndm() > xout)) {
|
| 1316 |
if (distort && xvar[0] < 0 && R.Rndm()>0.1) continue;
|
| 1317 |
treeS->Fill();
|
| 1318 |
nsig++;
|
| 1319 |
}
|
| 1320 |
else {
|
| 1321 |
if (distort && xvar[0] > 0 && R.Rndm()>0.1) continue;
|
| 1322 |
treeB->Fill();
|
| 1323 |
nbgd++;
|
| 1324 |
}
|
| 1325 |
} while ( nsig < nmax || nbgd < nmax);
|
| 1326 |
|
| 1327 |
dataFile->Write();
|
| 1328 |
dataFile->Close();
|
| 1329 |
|
| 1330 |
}
|
| 1331 |
|
| 1332 |
// create the data
|
| 1333 |
void create_circ(Int_t N = 6000, Bool_t distort = false)
|
| 1334 |
{
|
| 1335 |
Int_t Nn = 0;
|
| 1336 |
const Int_t nvar = 2;
|
| 1337 |
Float_t xvar[nvar];
|
| 1338 |
|
| 1339 |
// output flie
|
| 1340 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1341 |
|
| 1342 |
// create signal and background trees
|
| 1343 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1344 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1345 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1346 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1347 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1348 |
}
|
| 1349 |
// TTree *treeB = treeS->CloneTree();
|
| 1350 |
// for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1351 |
// treeS->SetBranchAddress( Form( "var%i", ivar ), &xvar[ivar] );
|
| 1352 |
// treeB->SetBranchAddress( Form( "var%i", ivar ), &xvar[ivar] );
|
| 1353 |
// }
|
| 1354 |
// treeB->SetName ( "TreeB" );
|
| 1355 |
// treeB->SetTitle( "TreeB" );
|
| 1356 |
|
| 1357 |
TRandom R( 100 );
|
| 1358 |
//Float_t phimin = -30, phimax = 130;
|
| 1359 |
Float_t phimin = -70, phimax = 130;
|
| 1360 |
Float_t phisig = 5;
|
| 1361 |
Float_t rS = 1.1;
|
| 1362 |
Float_t rB = 0.75;
|
| 1363 |
Float_t rsig = 0.1;
|
| 1364 |
Float_t fnmin = -(rS+4.0*rsig);
|
| 1365 |
Float_t fnmax = +(rS+4.0*rsig);
|
| 1366 |
Float_t dfn = fnmax-fnmin;
|
| 1367 |
// loop over species
|
| 1368 |
for (Int_t itype=0; itype<2; itype++) {
|
| 1369 |
|
| 1370 |
// event loop
|
| 1371 |
TTree* tree = (itype==0) ? treeS : treeB;
|
| 1372 |
for (Int_t i=0; i<N; i++) {
|
| 1373 |
Double_t r1=R.Rndm(),r2=R.Rndm(), r3;
|
| 1374 |
if (itype==0) r3= r1>r2? r1 :r2;
|
| 1375 |
else r3= r2;
|
| 1376 |
Float_t phi;
|
| 1377 |
if (distort) phi = r3*(phimax - phimin) + phimin;
|
| 1378 |
else phi = R.Rndm()*(phimax - phimin) + phimin;
|
| 1379 |
phi += R.Gaus()*phisig;
|
| 1380 |
|
| 1381 |
Float_t r = (itype==0) ? rS : rB;
|
| 1382 |
r += R.Gaus()*rsig;
|
| 1383 |
|
| 1384 |
xvar[0] = r*cos(TMath::DegToRad()*phi);
|
| 1385 |
xvar[1] = r*sin(TMath::DegToRad()*phi);
|
| 1386 |
|
| 1387 |
tree->Fill();
|
| 1388 |
}
|
| 1389 |
|
| 1390 |
for (Int_t i=0; i<Nn; i++) {
|
| 1391 |
|
| 1392 |
xvar[0] = dfn*R.Rndm()+fnmin;
|
| 1393 |
xvar[1] = dfn*R.Rndm()+fnmin;
|
| 1394 |
|
| 1395 |
tree->Fill();
|
| 1396 |
}
|
| 1397 |
}
|
| 1398 |
|
| 1399 |
// write trees
|
| 1400 |
treeS->Write();
|
| 1401 |
treeB->Write();
|
| 1402 |
|
| 1403 |
treeS->Show(0);
|
| 1404 |
treeB->Show(1);
|
| 1405 |
|
| 1406 |
dataFile->Close();
|
| 1407 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1408 |
|
| 1409 |
plot();
|
| 1410 |
}
|
| 1411 |
|
| 1412 |
|
| 1413 |
void create_schachbrett(Int_t nEvents = 20000) {
|
| 1414 |
|
| 1415 |
const Int_t nvar = 2;
|
| 1416 |
Float_t xvar[nvar];
|
| 1417 |
|
| 1418 |
// output flie
|
| 1419 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1420 |
|
| 1421 |
// create signal and background trees
|
| 1422 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1423 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1424 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1425 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1426 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1427 |
}
|
| 1428 |
|
| 1429 |
Int_t nSeed = 12345;
|
| 1430 |
TRandom *m_rand = new TRandom(nSeed);
|
| 1431 |
Double_t sigma=0.3;
|
| 1432 |
Double_t meanX;
|
| 1433 |
Double_t meanY;
|
| 1434 |
Int_t xtype=1, ytype=1;
|
| 1435 |
Int_t iev=0;
|
| 1436 |
Int_t m_nDim = 2; // actually the boundary, there is a "bump" for every interger value
|
| 1437 |
// between in the Inteval [-m_nDim,m_nDim]
|
| 1438 |
while (iev < nEvents){
|
| 1439 |
xtype=1;
|
| 1440 |
for (Int_t i=-m_nDim; i <= m_nDim; i++){
|
| 1441 |
ytype = 1;
|
| 1442 |
for (Int_t j=-m_nDim; j <= m_nDim; j++){
|
| 1443 |
meanX=Double_t(i);
|
| 1444 |
meanY=Double_t(j);
|
| 1445 |
xvar[0]=m_rand->Gaus(meanY,sigma);
|
| 1446 |
xvar[1]=m_rand->Gaus(meanX,sigma);
|
| 1447 |
Int_t type = xtype*ytype;
|
| 1448 |
TTree* tree = (type==1) ? treeS : treeB;
|
| 1449 |
tree->Fill();
|
| 1450 |
iev++;
|
| 1451 |
ytype *= -1;
|
| 1452 |
}
|
| 1453 |
xtype *= -1;
|
| 1454 |
}
|
| 1455 |
}
|
| 1456 |
|
| 1457 |
|
| 1458 |
// write trees
|
| 1459 |
treeS->Write();
|
| 1460 |
treeB->Write();
|
| 1461 |
|
| 1462 |
treeS->Show(0);
|
| 1463 |
treeB->Show(1);
|
| 1464 |
|
| 1465 |
dataFile->Close();
|
| 1466 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1467 |
|
| 1468 |
plot();
|
| 1469 |
|
| 1470 |
}
|
| 1471 |
|
| 1472 |
|
| 1473 |
void create_schachbrett_5D(Int_t nEvents = 200000) {
|
| 1474 |
const Int_t nvar = 5;
|
| 1475 |
Float_t xvar[nvar];
|
| 1476 |
|
| 1477 |
// output flie
|
| 1478 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1479 |
|
| 1480 |
// create signal and background trees
|
| 1481 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1482 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1483 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1484 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1485 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1486 |
}
|
| 1487 |
|
| 1488 |
Int_t nSeed = 12345;
|
| 1489 |
TRandom *m_rand = new TRandom(nSeed);
|
| 1490 |
Double_t sigma=0.3;
|
| 1491 |
Int_t itype[nvar];
|
| 1492 |
Int_t iev=0;
|
| 1493 |
Int_t m_nDim = 2; // actually the boundary, there is a "bump" for every interger value
|
| 1494 |
// between in the Inteval [-m_nDim,m_nDim]
|
| 1495 |
|
| 1496 |
int idx[nvar];
|
| 1497 |
while (iev < nEvents){
|
| 1498 |
itype[0]=1;
|
| 1499 |
for (idx[0]=-m_nDim; idx[0] <= m_nDim; idx[0]++){
|
| 1500 |
itype[1]=1;
|
| 1501 |
for (idx[1]=-m_nDim; idx[1] <= m_nDim; idx[1]++){
|
| 1502 |
itype[2]=1;
|
| 1503 |
for (idx[2]=-m_nDim; idx[2] <= m_nDim; idx[2]++){
|
| 1504 |
itype[3]=1;
|
| 1505 |
for (idx[3]=-m_nDim; idx[3] <= m_nDim; idx[3]++){
|
| 1506 |
itype[4]=1;
|
| 1507 |
for (idx[4]=-m_nDim; idx[4] <= m_nDim; idx[4]++){
|
| 1508 |
Int_t type = itype[0];
|
| 1509 |
for (Int_t i=0;i<nvar;i++){
|
| 1510 |
xvar[i]=m_rand->Gaus(Double_t(idx[i]),sigma);
|
| 1511 |
if (i>0) type *= itype[i];
|
| 1512 |
}
|
| 1513 |
TTree* tree = (type==1) ? treeS : treeB;
|
| 1514 |
tree->Fill();
|
| 1515 |
iev++;
|
| 1516 |
itype[4] *= -1;
|
| 1517 |
}
|
| 1518 |
itype[3] *= -1;
|
| 1519 |
}
|
| 1520 |
itype[2] *= -1;
|
| 1521 |
}
|
| 1522 |
itype[1] *= -1;
|
| 1523 |
}
|
| 1524 |
itype[0] *= -1;
|
| 1525 |
}
|
| 1526 |
}
|
| 1527 |
|
| 1528 |
// write trees
|
| 1529 |
treeS->Write();
|
| 1530 |
treeB->Write();
|
| 1531 |
|
| 1532 |
treeS->Show(0);
|
| 1533 |
treeB->Show(1);
|
| 1534 |
|
| 1535 |
dataFile->Close();
|
| 1536 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1537 |
|
| 1538 |
plot();
|
| 1539 |
|
| 1540 |
}
|
| 1541 |
|
| 1542 |
|
| 1543 |
void create_schachbrett_4D(Int_t nEvents = 200000) {
|
| 1544 |
|
| 1545 |
const Int_t nvar = 4;
|
| 1546 |
Float_t xvar[nvar];
|
| 1547 |
|
| 1548 |
// output flie
|
| 1549 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1550 |
|
| 1551 |
// create signal and background trees
|
| 1552 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1553 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1554 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1555 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1556 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1557 |
}
|
| 1558 |
|
| 1559 |
Int_t nSeed = 12345;
|
| 1560 |
TRandom *m_rand = new TRandom(nSeed);
|
| 1561 |
Double_t sigma=0.3;
|
| 1562 |
Int_t itype[nvar];
|
| 1563 |
Int_t iev=0;
|
| 1564 |
Int_t m_nDim = 2; // actually the boundary, there is a "bump" for every interger value
|
| 1565 |
// between in the Inteval [-m_nDim,m_nDim]
|
| 1566 |
|
| 1567 |
int idx[nvar];
|
| 1568 |
while (iev < nEvents){
|
| 1569 |
itype[0]=1;
|
| 1570 |
for (idx[0]=-m_nDim; idx[0] <= m_nDim; idx[0]++){
|
| 1571 |
itype[1]=1;
|
| 1572 |
for (idx[1]=-m_nDim; idx[1] <= m_nDim; idx[1]++){
|
| 1573 |
itype[2]=1;
|
| 1574 |
for (idx[2]=-m_nDim; idx[2] <= m_nDim; idx[2]++){
|
| 1575 |
itype[3]=1;
|
| 1576 |
for (idx[3]=-m_nDim; idx[3] <= m_nDim; idx[3]++){
|
| 1577 |
Int_t type = itype[0];
|
| 1578 |
for (Int_t i=0;i<nvar;i++){
|
| 1579 |
xvar[i]=m_rand->Gaus(Double_t(idx[i]),sigma);
|
| 1580 |
if (i>0) type *= itype[i];
|
| 1581 |
}
|
| 1582 |
TTree* tree = (type==1) ? treeS : treeB;
|
| 1583 |
tree->Fill();
|
| 1584 |
iev++;
|
| 1585 |
itype[3] *= -1;
|
| 1586 |
}
|
| 1587 |
itype[2] *= -1;
|
| 1588 |
}
|
| 1589 |
itype[1] *= -1;
|
| 1590 |
}
|
| 1591 |
itype[0] *= -1;
|
| 1592 |
}
|
| 1593 |
}
|
| 1594 |
|
| 1595 |
// write trees
|
| 1596 |
treeS->Write();
|
| 1597 |
treeB->Write();
|
| 1598 |
|
| 1599 |
treeS->Show(0);
|
| 1600 |
treeB->Show(1);
|
| 1601 |
|
| 1602 |
dataFile->Close();
|
| 1603 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1604 |
|
| 1605 |
plot();
|
| 1606 |
|
| 1607 |
}
|
| 1608 |
|
| 1609 |
|
| 1610 |
void create_schachbrett_3D(Int_t nEvents = 20000) {
|
| 1611 |
|
| 1612 |
const Int_t nvar = 3;
|
| 1613 |
Float_t xvar[nvar];
|
| 1614 |
|
| 1615 |
// output flie
|
| 1616 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1617 |
|
| 1618 |
// create signal and background trees
|
| 1619 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1620 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1621 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1622 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1623 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1624 |
}
|
| 1625 |
|
| 1626 |
Int_t nSeed = 12345;
|
| 1627 |
TRandom *m_rand = new TRandom(nSeed);
|
| 1628 |
Double_t sigma=0.3;
|
| 1629 |
Int_t itype[nvar];
|
| 1630 |
Int_t iev=0;
|
| 1631 |
Int_t m_nDim = 2; // actually the boundary, there is a "bump" for every interger value
|
| 1632 |
// between in the Inteval [-m_nDim,m_nDim]
|
| 1633 |
|
| 1634 |
int idx[nvar];
|
| 1635 |
while (iev < nEvents){
|
| 1636 |
itype[0]=1;
|
| 1637 |
for (idx[0]=-m_nDim; idx[0] <= m_nDim; idx[0]++){
|
| 1638 |
itype[1]=1;
|
| 1639 |
for (idx[1]=-m_nDim; idx[1] <= m_nDim; idx[1]++){
|
| 1640 |
itype[2]=1;
|
| 1641 |
for (idx[2]=-m_nDim; idx[2] <= m_nDim; idx[2]++){
|
| 1642 |
Int_t type = itype[0];
|
| 1643 |
for (Int_t i=0;i<nvar;i++){
|
| 1644 |
xvar[i]=m_rand->Gaus(Double_t(idx[i]),sigma);
|
| 1645 |
if (i>0) type *= itype[i];
|
| 1646 |
}
|
| 1647 |
TTree* tree = (type==1) ? treeS : treeB;
|
| 1648 |
tree->Fill();
|
| 1649 |
iev++;
|
| 1650 |
itype[2] *= -1;
|
| 1651 |
}
|
| 1652 |
itype[1] *= -1;
|
| 1653 |
}
|
| 1654 |
itype[0] *= -1;
|
| 1655 |
}
|
| 1656 |
}
|
| 1657 |
|
| 1658 |
// write trees
|
| 1659 |
treeS->Write();
|
| 1660 |
treeB->Write();
|
| 1661 |
|
| 1662 |
treeS->Show(0);
|
| 1663 |
treeB->Show(1);
|
| 1664 |
|
| 1665 |
dataFile->Close();
|
| 1666 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1667 |
|
| 1668 |
plot();
|
| 1669 |
|
| 1670 |
}
|
| 1671 |
|
| 1672 |
|
| 1673 |
void create_schachbrett_2D(Int_t nEvents = 100000, Int_t nbumps=2) {
|
| 1674 |
|
| 1675 |
const Int_t nvar = 2;
|
| 1676 |
Float_t xvar[nvar];
|
| 1677 |
|
| 1678 |
// output flie
|
| 1679 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1680 |
|
| 1681 |
// create signal and background trees
|
| 1682 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1683 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1684 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1685 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1686 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1687 |
}
|
| 1688 |
|
| 1689 |
Int_t nSeed = 345;
|
| 1690 |
TRandom *m_rand = new TRandom(nSeed);
|
| 1691 |
Double_t sigma=0.35;
|
| 1692 |
Int_t itype[nvar];
|
| 1693 |
Int_t iev=0;
|
| 1694 |
Int_t m_nDim = nbumps; // actually the boundary, there is a "bump" for every interger value
|
| 1695 |
// between in the Inteval [-m_nDim,m_nDim]
|
| 1696 |
|
| 1697 |
int idx[nvar];
|
| 1698 |
while (iev < nEvents){
|
| 1699 |
itype[0]=1;
|
| 1700 |
for (idx[0]=-m_nDim; idx[0] <= m_nDim; idx[0]++){
|
| 1701 |
itype[1]=1;
|
| 1702 |
for (idx[1]=-m_nDim; idx[1] <= m_nDim; idx[1]++){
|
| 1703 |
Int_t type = itype[0];
|
| 1704 |
for (Int_t i=0;i<nvar;i++){
|
| 1705 |
xvar[i]=m_rand->Gaus(Double_t(idx[i]),sigma);
|
| 1706 |
if (i>0) type *= itype[i];
|
| 1707 |
}
|
| 1708 |
TTree* tree = (type==1) ? treeS : treeB;
|
| 1709 |
tree->Fill();
|
| 1710 |
iev++;
|
| 1711 |
itype[1] *= -1;
|
| 1712 |
}
|
| 1713 |
itype[0] *= -1;
|
| 1714 |
}
|
| 1715 |
}
|
| 1716 |
|
| 1717 |
// write trees
|
| 1718 |
treeS->Write();
|
| 1719 |
treeB->Write();
|
| 1720 |
|
| 1721 |
treeS->Show(0);
|
| 1722 |
treeB->Show(1);
|
| 1723 |
|
| 1724 |
dataFile->Close();
|
| 1725 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1726 |
|
| 1727 |
plot();
|
| 1728 |
|
| 1729 |
}
|
| 1730 |
|
| 1731 |
|
| 1732 |
|
| 1733 |
void create_3Bumps(Int_t nEvents = 5000) {
|
| 1734 |
// signal is clustered around (1,0) and (-1,0) where one is two times(1,0)
|
| 1735 |
// bkg (0,0)
|
| 1736 |
|
| 1737 |
|
| 1738 |
|
| 1739 |
const Int_t nvar = 2;
|
| 1740 |
Float_t xvar[nvar];
|
| 1741 |
|
| 1742 |
// output flie
|
| 1743 |
TString filename = "data_3Bumps.root";
|
| 1744 |
TFile* dataFile = TFile::Open( filename, "RECREATE" );
|
| 1745 |
|
| 1746 |
// create signal and background trees
|
| 1747 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1748 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1749 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1750 |
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1751 |
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
|
| 1752 |
}
|
| 1753 |
|
| 1754 |
Int_t nSeed = 12345;
|
| 1755 |
TRandom *m_rand = new TRandom(nSeed);
|
| 1756 |
Double_t sigma=0.2;
|
| 1757 |
Int_t type;
|
| 1758 |
Int_t iev=0;
|
| 1759 |
Double_t Centers[nvar][6] = {{-1,0,0,0,1,1},{0,0,0,0,0,0}}; //
|
| 1760 |
|
| 1761 |
|
| 1762 |
while (iev < nEvents){
|
| 1763 |
for (int idx=0; idx<6; idx++){
|
| 1764 |
if (idx==1 || idx==2 || idx==3) type = 0;
|
| 1765 |
else type=1;
|
| 1766 |
for (Int_t ivar=0;ivar<nvar;ivar++){
|
| 1767 |
xvar[ivar]=m_rand->Gaus(Centers[ivar][idx],sigma);
|
| 1768 |
}
|
| 1769 |
TTree* tree = (type==1) ? treeS : treeB;
|
| 1770 |
tree->Fill();
|
| 1771 |
iev++;
|
| 1772 |
}
|
| 1773 |
}
|
| 1774 |
|
| 1775 |
// write trees
|
| 1776 |
treeS->Write();
|
| 1777 |
treeB->Write();
|
| 1778 |
|
| 1779 |
treeS->Show(0);
|
| 1780 |
treeB->Show(1);
|
| 1781 |
|
| 1782 |
dataFile->Close();
|
| 1783 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1784 |
|
| 1785 |
plot(filename);
|
| 1786 |
|
| 1787 |
}
|
| 1788 |
|
| 1789 |
void createOnionData(Int_t nmax = 50000){
|
| 1790 |
// output file
|
| 1791 |
TFile* dataFile = TFile::Open( "oniondata.root", "RECREATE" );
|
| 1792 |
int nvar = 4;
|
| 1793 |
int nsig = 0, nbgd=0;
|
| 1794 |
Float_t xvar[100];
|
| 1795 |
// create signal and background trees
|
| 1796 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1797 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1798 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1799 |
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 1800 |
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
|
| 1801 |
}
|
| 1802 |
|
| 1803 |
TRandom R( 100 );
|
| 1804 |
do {
|
| 1805 |
for (Int_t ivar=0; ivar<nvar; ivar++) { xvar[ivar]=R.Rndm();}
|
| 1806 |
Float_t xout = sin(2.*acos(-1.)*(xvar[0]*xvar[1]*xvar[2]*xvar[3]+xvar[0]*xvar[1]));
|
| 1807 |
if (nsig<100) cout << "xout = " << xout<<endl;
|
| 1808 |
Int_t i = (Int_t) ((1.+xout)*4.99);
|
| 1809 |
if (i%2 == 0 && nsig < nmax) {
|
| 1810 |
treeS->Fill();
|
| 1811 |
nsig++;
|
| 1812 |
}
|
| 1813 |
if (i%2 != 0 && nbgd < nmax){
|
| 1814 |
treeB->Fill();
|
| 1815 |
nbgd++;
|
| 1816 |
}
|
| 1817 |
} while ( nsig < nmax || nbgd < nmax);
|
| 1818 |
|
| 1819 |
dataFile->Write();
|
| 1820 |
dataFile->Close();
|
| 1821 |
}
|
| 1822 |
|
| 1823 |
void create_multiclassdata(Int_t nmax = 20000)
|
| 1824 |
{
|
| 1825 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1826 |
int ncls = 3;
|
| 1827 |
int nvar = 4;
|
| 1828 |
int ndat = 0;
|
| 1829 |
Int_t cls;
|
| 1830 |
Float_t thecls;
|
| 1831 |
Float_t weight=1;
|
| 1832 |
Float_t xcls[100];
|
| 1833 |
Float_t xmean[3][4] = {
|
| 1834 |
{ 0. , 0.3, 0.5, 0.9 },
|
| 1835 |
{ -0.2 , -0.3, 0.5, 0.4 },
|
| 1836 |
{ 0.2 , 0.1, -0.1, 0.7 }} ;
|
| 1837 |
|
| 1838 |
Float_t xvar[100];
|
| 1839 |
// create tree using class flag stored in int variable cls
|
| 1840 |
TTree* treeR = new TTree( "TreeR", "TreeR", 1 );
|
| 1841 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1842 |
treeR->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar)).Data() );
|
| 1843 |
}
|
| 1844 |
for (Int_t icls=0; icls<ncls; icls++) {
|
| 1845 |
treeR->Branch(TString(Form( "cls%i", icls )).Data(), &xcls[icls], TString(Form( "cls%i/F", icls)).Data() );
|
| 1846 |
}
|
| 1847 |
|
| 1848 |
treeR->Branch("cls", &thecls, "cls/F");
|
| 1849 |
treeR->Branch("weight", &weight, "weight/F");
|
| 1850 |
|
| 1851 |
TRandom R( 100 );
|
| 1852 |
do {
|
| 1853 |
for (Int_t icls=0; icls<ncls; icls++) xcls[icls]=0.;
|
| 1854 |
cls = R.Integer(ncls);
|
| 1855 |
thecls = cls;
|
| 1856 |
xcls[cls]=1.;
|
| 1857 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1858 |
xvar[ivar]=R.Gaus(xmean[cls][ivar],1.);
|
| 1859 |
}
|
| 1860 |
|
| 1861 |
if (ndat<30) cout << "cls=" << cls <<" xvar = " << xvar[0]<<" " <<xvar[1]<<" " << xvar[2]<<" " <<xvar[3]<<endl;
|
| 1862 |
|
| 1863 |
treeR->Fill();
|
| 1864 |
ndat++;
|
| 1865 |
} while ( ndat < nmax );
|
| 1866 |
|
| 1867 |
dataFile->Write();
|
| 1868 |
dataFile->Close();
|
| 1869 |
|
| 1870 |
}
|
| 1871 |
|
| 1872 |
|
| 1873 |
|
| 1874 |
|
| 1875 |
|
| 1876 |
|
| 1877 |
// create the data
|
| 1878 |
void create_array_with_different_lengths(Int_t N = 100)
|
| 1879 |
{
|
| 1880 |
const Int_t nvar = 4;
|
| 1881 |
Int_t nvarCurrent = 4;
|
| 1882 |
Float_t xvar[nvar];
|
| 1883 |
|
| 1884 |
// output flie
|
| 1885 |
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
|
| 1886 |
|
| 1887 |
// create signal and background trees
|
| 1888 |
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
|
| 1889 |
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
|
| 1890 |
treeS->Branch( "arrSize", &nvarCurrent, "arrSize/I" );
|
| 1891 |
treeS->Branch( "arr", xvar, "arr[arrSize]/F" );
|
| 1892 |
treeB->Branch( "arrSize", &nvarCurrent, "arrSize/I" );
|
| 1893 |
treeB->Branch( "arr", xvar, "arr[arrSize]/F" );
|
| 1894 |
|
| 1895 |
TRandom R( 100 );
|
| 1896 |
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
|
| 1897 |
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
|
| 1898 |
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
|
| 1899 |
TArrayD* v = new TArrayD( nvar );
|
| 1900 |
Float_t rho[20];
|
| 1901 |
rho[1*2] = 0.4;
|
| 1902 |
rho[1*3] = 0.6;
|
| 1903 |
rho[1*4] = 0.9;
|
| 1904 |
rho[2*3] = 0.7;
|
| 1905 |
rho[2*4] = 0.8;
|
| 1906 |
rho[3*4] = 0.93;
|
| 1907 |
|
| 1908 |
// create covariance matrix
|
| 1909 |
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
|
| 1910 |
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
|
| 1911 |
for (Int_t ivar=0; ivar<nvar; ivar++) {
|
| 1912 |
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 1913 |
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
|
| 1914 |
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
|
| 1915 |
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 1916 |
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
|
| 1917 |
|
| 1918 |
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
|
| 1919 |
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
|
| 1920 |
}
|
| 1921 |
}
|
| 1922 |
cout << "signal covariance matrix: " << endl;
|
| 1923 |
covMatS->Print();
|
| 1924 |
cout << "background covariance matrix: " << endl;
|
| 1925 |
covMatB->Print();
|
| 1926 |
|
| 1927 |
// produce the square-root matrix
|
| 1928 |
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
|
| 1929 |
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
|
| 1930 |
|
| 1931 |
// loop over species
|
| 1932 |
for (Int_t itype=0; itype<2; itype++) {
|
| 1933 |
|
| 1934 |
Float_t* x;
|
| 1935 |
TMatrixD* m;
|
| 1936 |
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
|
| 1937 |
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
|
| 1938 |
|
| 1939 |
// event loop
|
| 1940 |
TTree* tree = (itype==0) ? treeS : treeB;
|
| 1941 |
for (Int_t i=0; i<N; i++) {
|
| 1942 |
|
| 1943 |
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
|
| 1944 |
getGaussRnd( *v, *m, R );
|
| 1945 |
|
| 1946 |
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
|
| 1947 |
|
| 1948 |
|
| 1949 |
nvarCurrent = (i%4)+1;
|
| 1950 |
|
| 1951 |
tree->Fill();
|
| 1952 |
}
|
| 1953 |
}
|
| 1954 |
|
| 1955 |
// write trees
|
| 1956 |
treeS->Write();
|
| 1957 |
treeB->Write();
|
| 1958 |
|
| 1959 |
treeS->Show(0);
|
| 1960 |
treeB->Show(1);
|
| 1961 |
|
| 1962 |
dataFile->Close();
|
| 1963 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 1964 |
}
|
| 1965 |
|
| 1966 |
|
| 1967 |
|
| 1968 |
// create the data
|
| 1969 |
void create_MultipleBackground(Int_t N = 50000)
|
| 1970 |
{
|
| 1971 |
const int nvar = 4;
|
| 1972 |
|
| 1973 |
// output flie
|
| 1974 |
TFile* dataFile = TFile::Open( "tmva_example_multiple_background.root", "RECREATE" );
|
| 1975 |
|
| 1976 |
|
| 1977 |
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
|
| 1978 |
Float_t xB0[nvar] = { -0.2, -0.3, -0.5, -0.6 };
|
| 1979 |
Float_t xB1[nvar] = { -0.2, 0.3, 0.5, -0.6 };
|
| 1980 |
Float_t dx0[nvar] = { 1.0, 1.0, 1.0, 1.0 };
|
| 1981 |
Float_t dx1[nvar] = { -1.0, -1.0, -1.0, -1.0 };
|
| 1982 |
|
| 1983 |
// create signal and background trees
|
| 1984 |
TTree* treeS = makeTree_lin_Nvar( "TreeS", "Signal tree", xS, dx0, nvar, N );
|
| 1985 |
TTree* treeB0 = makeTree_lin_Nvar( "TreeB0", "Background 0", xB0, dx0, nvar, N );
|
| 1986 |
TTree* treeB1 = makeTree_lin_Nvar( "TreeB1", "Background 1", xB1, dx1, nvar, N );
|
| 1987 |
TTree* treeB2 = makeTree_circ( "TreeB2", "Background 2", nvar, N, 1.5, true);
|
| 1988 |
|
| 1989 |
treeS->Write();
|
| 1990 |
treeB0->Write();
|
| 1991 |
treeB1->Write();
|
| 1992 |
treeB2->Write();
|
| 1993 |
|
| 1994 |
//treeS->Show(0);
|
| 1995 |
//treeB0->Show(0);
|
| 1996 |
//treeB1->Show(0);
|
| 1997 |
//treeB2->Show(0);
|
| 1998 |
|
| 1999 |
dataFile->Close();
|
| 2000 |
cout << "created data file: " << dataFile->GetName() << endl;
|
| 2001 |
}
|
