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createData.C File Reference
Tutorials » Machine Learning tutorials

Detailed Description

Plot the variables.

#include "TROOT.h"
#include "TMath.h"
#include "TTree.h"
#include "TArrayD.h"
#include "TStyle.h"
#include "TFile.h"
#include "TRandom.h"
#include "Riostream.h"
#include "TCanvas.h"
#include "TMatrixD.h"
#include "TH2F.h"
#include "TLegend.h"
#include "TBranch.h"
#include <vector>
void plot( TString fname = "data.root", TString var0="var0", TString var1="var1" )
{
TFile* dataFile = TFile::Open( fname );
if (!dataFile) {
cout << "ERROR: cannot open file: " << fname << endl;
return;
}
TTree *treeS = (TTree*)dataFile->Get("TreeS");
TTree *treeB = (TTree*)dataFile->Get("TreeB");
TCanvas* c = new TCanvas( "c", "", 0, 0, 550, 550 );
TStyle *TMVAStyle = gROOT->GetStyle("Plain"); // our style is based on Plain
TMVAStyle->SetOptStat(0);
TMVAStyle->SetPadTopMargin(0.02);
TMVAStyle->SetPadBottomMargin(0.16);
TMVAStyle->SetPadRightMargin(0.03);
TMVAStyle->SetPadLeftMargin(0.15);
TMVAStyle->SetPadGridX(0);
TMVAStyle->SetPadGridY(0);
TMVAStyle->SetOptTitle(0);
TMVAStyle->SetTitleW(.4);
TMVAStyle->SetTitleH(.10);
TMVAStyle->SetTitleX(.5);
TMVAStyle->SetTitleY(.9);
TMVAStyle->SetMarkerStyle(20);
TMVAStyle->SetMarkerSize(1.6);
TMVAStyle->cd();
Float_t xmin = TMath::Min( treeS->GetMinimum( var0 ), treeB->GetMinimum( var0 ) );
Float_t xmax = TMath::Max( treeS->GetMaximum( var0 ), treeB->GetMaximum( var0 ) );
Float_t ymin = TMath::Min( treeS->GetMinimum( var1 ), treeB->GetMinimum( var1 ) );
Float_t ymax = TMath::Max( treeS->GetMaximum( var1 ), treeB->GetMaximum( var1 ) );
Int_t nbin = 500;
TH2F* frameS = new TH2F( "DataS", "DataS", nbin, xmin, xmax, nbin, ymin, ymax );
TH2F* frameB = new TH2F( "DataB", "DataB", nbin, xmin, xmax, nbin, ymin, ymax );
// project trees
treeS->Draw( Form("%s:%s>>DataS",var1.Data(),var0.Data()), "", "0" );
treeB->Draw( Form("%s:%s>>DataB",var1.Data(),var0.Data()
), "", "0" );
// set style
frameS->SetMarkerSize( 0.1 );
frameS->SetMarkerColor( 4 );
frameB->SetMarkerSize( 0.1 );
frameB->SetMarkerColor( 2 );
// legend
frameS->SetTitle( var1+" versus "+var0+" for signal and background" );
frameS->GetXaxis()->SetTitle( var0 );
frameS->GetYaxis()->SetTitle( var1 );
frameS->SetLabelSize( 0.04, "X" );
frameS->SetLabelSize( 0.04, "Y" );
frameS->SetTitleSize( 0.05, "X" );
frameS->SetTitleSize( 0.05, "Y" );
// and plot
frameS->Draw();
frameB->Draw( "same" );
// Draw legend
TLegend *legend = new TLegend( 1 - c->GetRightMargin() - 0.32, 1 - c->GetTopMargin() - 0.12,
1 - c->GetRightMargin(), 1 - c->GetTopMargin() );
legend->SetFillStyle( 1 );
legend->AddEntry(frameS,"Signal","p");
legend->AddEntry(frameB,"Background","p");
legend->Draw("same");
legend->SetBorderSize(1);
legend->SetMargin( 0.3 );
}
TMatrixD* produceSqrtMat( const TMatrixD& covMat )
{
Double_t sum = 0;
Int_t size = covMat.GetNrows();;
TMatrixD* sqrtMat = new TMatrixD( size, size );
for (Int_t i=0; i< size; i++) {
sum = 0;
for (Int_t j=0;j< i; j++) sum += (*sqrtMat)(i,j) * (*sqrtMat)(i,j);
(*sqrtMat)(i,i) = TMath::Sqrt(TMath::Abs(covMat(i,i) - sum));
for (Int_t k=i+1 ;k<size; k++) {
sum = 0;
for (Int_t l=0; l<i; l++) sum += (*sqrtMat)(k,l) * (*sqrtMat)(i,l);
(*sqrtMat)(k,i) = (covMat(k,i) - sum) / (*sqrtMat)(i,i);
}
}
return sqrtMat;
}
void getGaussRnd( TArrayD& v, const TMatrixD& sqrtMat, TRandom& R )
{
// generate "size" correlated Gaussian random numbers
// sanity check
const Int_t size = sqrtMat.GetNrows();
if (size != v.GetSize())
cout << "<getGaussRnd> too short input vector: " << size << " " << v.GetSize() << endl;
Double_t* tmpVec = new Double_t[size];
for (Int_t i=0; i<size; i++) {
Double_t x, y, z;
y = R.Rndm();
z = R.Rndm();
x = 2*TMath::Pi()*z;
tmpVec[i] = TMath::Sin(x) * TMath::Sqrt(-2.0*TMath::Log(y));
}
for (Int_t i=0; i<size; i++) {
v[i] = 0;
for (Int_t j=0; j<=i; j++) v[i] += sqrtMat(i,j) * tmpVec[j];
}
delete[] tmpVec;
}
// create the data
void create_lin_Nvar_withFriend(Int_t N = 2000)
{
const Int_t nvar = 4;
const Int_t nvar2 = 1;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar-nvar2; ivar++) {
cout << "Creating branch var" << ivar+1 << " in signal tree" << endl;
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
}
TTree* treeSF = new TTree( "TreeSF", "TreeS", 1 );
TTree* treeBF = new TTree( "TreeBF", "TreeB", 1 );
for (Int_t ivar=nvar-nvar2; ivar<nvar; ivar++) {
treeSF->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
treeBF->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
}
TRandom R( 100 );
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
TArrayD* v = new TArrayD( nvar );
Float_t rho[20];
rho[1*2] = 0.4;
rho[1*3] = 0.6;
rho[1*4] = 0.9;
rho[2*3] = 0.7;
rho[2*4] = 0.8;
rho[3*4] = 0.93;
// create covariance matrix
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
}
}
cout << "signal covariance matrix: " << endl;
covMatS->Print();
cout << "background covariance matrix: " << endl;
covMatB->Print();
// produce the square-root matrix
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Float_t* x;
TMatrixD* m;
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
TTree* treeF = (itype==0) ? treeSF : treeBF;
for (Int_t i=0; i<N; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
getGaussRnd( *v, *m, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
tree->Fill();
treeF->Fill();
}
}
// treeS->AddFriend(treeSF);
// treeB->AddFriend(treeBF);
// write trees
treeS->Write();
treeB->Write();
treeSF->Write();
treeBF->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
}
// create the tree
TTree* makeTree_lin_Nvar( TString treeName, TString treeTitle, Float_t* x, Float_t* dx, const Int_t nvar, Int_t N )
{
Float_t xvar[nvar];
// create tree
TTree* tree = new TTree(treeName, treeTitle, 1);
for (Int_t ivar=0; ivar<nvar; ivar++) {
tree->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
}
TRandom R( 100 );
TArrayD* v = new TArrayD( nvar );
Float_t rho[20];
rho[1*2] = 0.4;
rho[1*3] = 0.6;
rho[1*4] = 0.9;
rho[2*3] = 0.7;
rho[2*4] = 0.8;
rho[3*4] = 0.93;
// create covariance matrix
TMatrixD* covMat = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMat)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMat)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMat)(jvar,ivar) = (*covMat)(ivar,jvar);
}
}
//cout << "covariance matrix: " << endl;
//covMat->Print();
// produce the square-root matrix
TMatrixD* sqrtMat = produceSqrtMat( *covMat );
// event loop
for (Int_t i=0; i<N; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
getGaussRnd( *v, *sqrtMat, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
tree->Fill();
}
// write trees
// tree->Write();
tree->Show(0);
cout << "created tree: " << tree->GetName() << endl;
return tree;
}
// create the data
TTree* makeTree_circ(TString treeName, TString treeTitle, Int_t nvar = 2, Int_t N = 6000, Float_t radius = 1.0, Bool_t distort = false)
{
Int_t Nn = 0;
Float_t xvar[nvar]; //variable array size does not work in interactive mode
// create signal and background trees
TTree* tree = new TTree( treeName, treeTitle, 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
tree->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
}
TRandom R( 100 );
//Float_t phimin = -30, phimax = 130;
Float_t phimin = -70, phimax = 130;
Float_t phisig = 5;
Float_t rsig = 0.1;
Float_t fnmin = -(radius+4.0*rsig);
Float_t fnmax = +(radius+4.0*rsig);
Float_t dfn = fnmax-fnmin;
// event loop
for (Int_t i=0; i<N; i++) {
Double_t r1=R.Rndm(),r2=R.Rndm(), r3;
r3= r1>r2? r1 :r2;
Float_t phi;
if (distort) phi = r3*(phimax - phimin) + phimin;
else phi = R.Rndm()*(phimax - phimin) + phimin;
phi += R.Gaus()*phisig;
Float_t r = radius;
r += R.Gaus()*rsig;
xvar[0] = r*cos(TMath::DegToRad()*phi);
xvar[1] = r*sin(TMath::DegToRad()*phi);
for( Int_t j = 2; j<nvar; ++j )
xvar[j] = dfn*R.Rndm()+fnmin;
tree->Fill();
}
for (Int_t i=0; i<Nn; i++) {
xvar[0] = dfn*R.Rndm()+fnmin;
xvar[1] = dfn*R.Rndm()+fnmin;
for( Int_t j = 2; j<nvar; ++j )
xvar[j] = dfn*R.Rndm()+fnmin;
tree->Fill();
}
tree->Show(0);
// write trees
cout << "created tree: " << tree->GetName() << endl;
return tree;
}
// create the data
void create_lin_Nvar_2(Int_t N = 50000)
{
const int nvar = 4;
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
// create signal and background trees
TTree* treeS = makeTree_lin_Nvar( "TreeS", "Signal tree", xS, dx, nvar, N );
TTree* treeB = makeTree_lin_Nvar( "TreeB", "Background tree", xB, dx, nvar, N );
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(0);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
}
// create the data
void create_lin_Nvar(Int_t N = 50000)
{
const Int_t nvar = 4;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
}
TRandom R( 100 );
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
TArrayD* v = new TArrayD( nvar );
Float_t rho[20];
rho[1*2] = 0.4;
rho[1*3] = 0.6;
rho[1*4] = 0.9;
rho[2*3] = 0.7;
rho[2*4] = 0.8;
rho[3*4] = 0.93;
// create covariance matrix
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
}
}
cout << "signal covariance matrix: " << endl;
covMatS->Print();
cout << "background covariance matrix: " << endl;
covMatB->Print();
// produce the square-root matrix
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Float_t* x;
TMatrixD* m;
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
for (Int_t i=0; i<N; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
getGaussRnd( *v, *m, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
}
// create the category data
// type = 1 (offset) or 2 (variable = -99)
void create_lin_Nvar_categories(Int_t N = 10000, Int_t type = 2)
{
const Int_t nvar = 4;
Float_t xvar[nvar];
Float_t eta;
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
}
// add category variable
treeS->Branch( "eta", &eta, "eta/F" );
treeB->Branch( "eta", &eta, "eta/F" );
TRandom R( 100 );
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
TArrayD* v = new TArrayD( nvar );
Float_t rho[20];
rho[1*2] = 0.0;
rho[1*3] = 0.0;
rho[1*4] = 0.0;
rho[2*3] = 0.0;
rho[2*4] = 0.0;
rho[3*4] = 0.0;
if (type != 1) {
rho[1*2] = 0.6;
rho[1*3] = 0.7;
rho[1*4] = 0.9;
rho[2*3] = 0.8;
rho[2*4] = 0.9;
rho[3*4] = 0.93;
}
// create covariance matrix
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
}
}
cout << "signal covariance matrix: " << endl;
covMatS->Print();
cout << "background covariance matrix: " << endl;
covMatB->Print();
// produce the square-root matrix
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Float_t* x;
TMatrixD* m;
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
for (Int_t i=0; i<N; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
getGaussRnd( *v, *m, R );
eta = 2.5*2*(R.Rndm() - 0.5);
Float_t offset = 0;
if (type == 1) offset = TMath::Abs(eta) > 1.3 ? 0.8 : -0.8;
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar] + offset;
if (type != 1 && TMath::Abs(eta) > 1.3) xvar[nvar-1] = -5;
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
}
// create the data
void create_lin_Nvar_weighted(Int_t N = 10000, int WeightedSignal=0, int WeightedBkg=1, Float_t BackgroundContamination=0, Int_t seed=100)
{
const Int_t nvar = 4;
Float_t xvar[nvar];
Float_t weight;
cout << endl << endl << endl;
cout << "please use .L createData.C++ if you want to run this MC generation" <<endl;
cout << "otherwise you will wait for ages!!! " << endl;
cout << endl << endl << endl;
// output file
TString fileName;
if (BackgroundContamination) fileName = Form("linCorGauss%d_weighted+background.root",seed);
else fileName = Form("linCorGauss%d_weighted.root",seed);
TFile* dataFile = TFile::Open( fileName.Data(), "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
}
if (WeightedSignal||BackgroundContamination>0||1) treeS->Branch( "weight", &weight,"weight/F" );
if (WeightedBkg) treeB->Branch( "weight", &weight,"weight/F" );
TRandom R( seed );
Float_t xS[nvar] = { 0.2, 0.3, 0.4, 0.8 };
Float_t xB[nvar] = { -0.2, -0.3, -0.4, -0.5 };
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
TArrayD* v = new TArrayD( nvar );
Float_t rho[20];
rho[1*2] = 0.4;
rho[1*3] = 0.6;
rho[1*4] = 0.9;
rho[2*3] = 0.7;
rho[2*4] = 0.8;
rho[3*4] = 0.93;
// create covariance matrix
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
}
}
cout << "signal covariance matrix: " << endl;
covMatS->Print();
cout << "background covariance matrix: " << endl;
covMatB->Print();
// produce the square-root matrix
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Float_t* x;
TMatrixD* m;
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
Int_t i=0;
do {
getGaussRnd( *v, *m, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
// for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = R.Uniform()*10.-5.;
// weight = 0.5 / (TMath::Gaus( (xvar[nvar-1]-x[nvar-1]), 0, 1.1) );
// weight = TMath::Gaus(0.675,0,1) / (TMath::Gaus( (xvar[nvar-1]-x[nvar-1]), 0, 1.) );
weight = 0.8 / (TMath::Gaus( ((*v)[nvar-1]), 0, 1.09) );
Double_t tmp=R.Uniform()/0.00034;
if (itype==0 && !WeightedSignal) {
weight = 1;
tree->Fill();
i++;
} else if (itype==1 && !WeightedBkg) {
weight = 1;
tree->Fill();
i++;
}
else {
if (tmp < weight){
weight = 1./weight;
tree->Fill();
if (i%10 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
i++;
}
}
} while (i<N);
}
if (BackgroundContamination > 0){ // add "background contamination" in the Signal (which later is again "subtracted" with
// using (statistically independent) background events with negative weight)
Float_t* x=xB;
TMatrixD* m = sqrtMatB;
TTree* tree = treeS;
for (Int_t i=0; i<N*BackgroundContamination*2; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
getGaussRnd( *v, *m, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
// add weights
if (i%2) weight = 1;
else weight = -1;
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
TH1F *h[4];
TH1F *hw[4];
for (Int_t i=0;i<4;i++){
char buffer[5];
sprintf(buffer,"h%d",i);
h[i]= new TH1F(buffer,"",100,-5,5);
sprintf(buffer,"hw%d",i);
hw[i] = new TH1F(buffer,"",100,-5,5);
hw[i]->SetLineColor(3);
}
for (int ie=0;ie<treeS->GetEntries();ie++){
treeS->GetEntry(ie);
for (Int_t i=0;i<4;i++){
h[i]->Fill(xvar[i]);
hw[i]->Fill(xvar[i],weight);
}
}
TCanvas *c = new TCanvas("c","",800,800);
c->Divide(2,2);
for (Int_t i=0;i<4;i++){
c->cd(i+1);
h[i]->Draw();
hw[i]->Draw("same");
}
// dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
}
// create the data
void create_lin_Nvar_Arr(Int_t N = 1000)
{
const Int_t nvar = 4;
std::vector<float>* xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
xvar[ivar] = new std::vector<float>();
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), "vector<float>", &xvar[ivar], 64000, 1 );
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), "vector<float>", &xvar[ivar], 64000, 1 );
}
TRandom R( 100 );
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
TArrayD* v = new TArrayD( nvar );
Float_t rho[20];
rho[1*2] = 0.4;
rho[1*3] = 0.6;
rho[1*4] = 0.9;
rho[2*3] = 0.7;
rho[2*4] = 0.8;
rho[3*4] = 0.93;
// create covariance matrix
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
}
}
cout << "signal covariance matrix: " << endl;
covMatS->Print();
cout << "background covariance matrix: " << endl;
covMatB->Print();
// produce the square-root matrix
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Float_t* x;
TMatrixD* m;
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
for (Int_t i=0; i<N; i++) {
if (i%100 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
Int_t aSize = (Int_t)(gRandom->Rndm()*10); // size of array varies between events
for (Int_t ivar=0; ivar<nvar; ivar++) {
xvar[ivar]->clear();
xvar[ivar]->reserve(aSize);
}
for(Int_t iA = 0; iA<aSize; iA++) {
//for (Int_t ivar=0; ivar<nvar; ivar++) {
getGaussRnd( *v, *m, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar]->push_back((*v)[ivar] + x[ivar]);
//}
}
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
//plot();
}
// create the data
void create_lin_Nvar_double()
{
Int_t N = 10000;
const Int_t nvar = 4;
Double_t xvar[nvar];
Double_t xvarD[nvar];
Float_t xvarF[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
if (ivar<2) {
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvarD[ivar], TString(Form( "var%i/D", ivar+1 )).Data() );
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvarD[ivar], TString(Form( "var%i/D", ivar+1 )).Data() );
}
else {
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvarF[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvarF[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
}
}
TRandom R( 100 );
Double_t xS[nvar] = { 0.2, 0.3, 0.5, 0.6 };
Double_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
Double_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
TArrayD* v = new TArrayD( nvar );
Double_t rho[20];
rho[1*2] = 0.4;
rho[1*3] = 0.6;
rho[1*4] = 0.9;
rho[2*3] = 0.7;
rho[2*4] = 0.8;
rho[3*4] = 0.93;
// create covariance matrix
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
}
}
cout << "signal covariance matrix: " << endl;
covMatS->Print();
cout << "background covariance matrix: " << endl;
covMatB->Print();
// produce the square-root matrix
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Double_t* x;
TMatrixD* m;
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
for (Int_t i=0; i<N; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
getGaussRnd( *v, *m, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
for (Int_t ivar=0; ivar<nvar; ivar++) {
if (ivar<2) xvarD[ivar] = xvar[ivar];
else xvarF[ivar] = xvar[ivar];
}
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot();
}
// create the data
void create_lin_Nvar_discrete()
{
Int_t N = 10000;
const Int_t nvar = 4;
Float_t xvar[nvar];
Int_t xvarI[2];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar-2; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
}
for (Int_t ivar=0; ivar<2; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar+nvar-2+1 )).Data(), &xvarI[ivar], TString(Form( "var%i/I", ivar+nvar-2+1 )).Data() );
treeB->Branch( TString(Form( "var%i", ivar+nvar-2+1 )).Data(), &xvarI[ivar], TString(Form( "var%i/I", ivar+nvar-2+1 )).Data() );
}
TRandom R( 100 );
Float_t xS[nvar] = { 0.2, 0.3, 1, 2 };
Float_t xB[nvar] = { -0.2, -0.3, 0, 0 };
Float_t dx[nvar] = { 1.0, 1.0, 1, 2 };
TArrayD* v = new TArrayD( nvar );
Float_t rho[20];
rho[1*2] = 0.4;
rho[1*3] = 0.6;
rho[1*4] = 0.9;
rho[2*3] = 0.7;
rho[2*4] = 0.8;
rho[3*4] = 0.93;
// no correlations
for (int i=0; i<20; i++) rho[i] = 0;
// create covariance matrix
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
}
}
cout << "signal covariance matrix: " << endl;
covMatS->Print();
cout << "background covariance matrix: " << endl;
covMatB->Print();
// produce the square-root matrix
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Float_t* x;
TMatrixD* m;
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
for (Int_t i=0; i<N; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
getGaussRnd( *v, *m, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
xvarI[0] = TMath::Nint(xvar[nvar-2]);
xvarI[1] = TMath::Nint(xvar[nvar-1]);
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot();
}
// create the data
void create_ManyVars()
{
Int_t N = 20000;
const Int_t nvar = 20;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
}
Float_t xS[nvar];
Float_t xB[nvar];
Float_t dx[nvar];
for (Int_t ivar=0; ivar<nvar; ivar++) {
xS[ivar] = 0 + ivar*0.05;
xB[ivar] = 0 - ivar*0.05;
dx[ivar] = 1;
}
xS[0] = 0.2;
xB[0] = -0.2;
dx[0] = 1.0;
xS[1] = 0.3;
xB[1] = -0.3;
dx[1] = 1.0;
xS[2] = 0.4;
xB[2] = -0.4;
dx[2] = 1.0 ;
xS[3] = 0.8 ;
xB[3] = -0.5 ;
dx[3] = 1.0 ;
// TArrayD* v = new TArrayD( nvar );
Float_t rho[20];
rho[1*2] = 0.4;
rho[1*3] = 0.6;
rho[1*4] = 0.9;
rho[2*3] = 0.7;
rho[2*4] = 0.8;
rho[3*4] = 0.93;
TRandom R( 100 );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Float_t* x = (itype == 0) ? xS : xB;
// event loop
TTree* tree = (itype == 0) ? treeS : treeB;
for (Int_t i=0; i<N; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
for (Int_t ivar=0; ivar<nvar; ivar++) {
if (ivar == 1500 && itype!=10) xvar[ivar] = 1;
else xvar[ivar] = x[ivar] + R.Gaus()*dx[ivar];
}
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
plot();
cout << "created data file: " << dataFile->GetName() << endl;
}
// create the data
void create_lin_NvarObsolete()
{
Int_t N = 20000;
const Int_t nvar = 20;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
}
TRandom R( 100 );
Float_t xS[nvar] = { 0.5, 0.5, 0.0, 0.0, 0.0, 0.0 };
Float_t xB[nvar] = { -0.5, -0.5, -0.0, -0.0, -0.0, -0.0 };
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 };
TArrayD* v = new TArrayD( nvar );
Float_t rho[50];
for (Int_t i=0; i<50; i++) rho[i] = 0;
rho[1*2] = 0.3;
rho[1*3] = 0.0;
rho[1*4] = 0.0;
rho[2*3] = 0.0;
rho[2*4] = 0.0;
rho[3*4] = 0.0;
// create covariance matrix
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
}
}
cout << "signal covariance matrix: " << endl;
covMatS->Print();
cout << "background covariance matrix: " << endl;
covMatB->Print();
// produce the square-root matrix
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Float_t* x;
TMatrixD* m;
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
for (Int_t i=0; i<N; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
getGaussRnd( *v, *m, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot();
}
// create the data
void create_lin(Int_t N = 2000)
{
const Int_t nvar = 2;
Double_t xvar[nvar];
Float_t weight;
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/D", ivar )).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/D", ivar )).Data() );
}
treeS->Branch( "weight", &weight, "weight/F" );
treeB->Branch( "weight", &weight, "weight/F" );
TRandom R( 100 );
Float_t xS[nvar] = { 0.0, 0.0 };
Float_t xB[nvar] = { -0.0, -0.0 };
Float_t dx[nvar] = { 1.0, 1.0 };
TArrayD* v = new TArrayD( 2 );
Float_t rhoS = 0.21;
Float_t rhoB = 0.0;
// create covariance matrix
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMatS)(ivar,jvar) = rhoS*dx[ivar]*dx[jvar];
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
(*covMatB)(ivar,jvar) = rhoB*dx[ivar]*dx[jvar];
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
}
}
cout << "signal covariance matrix: " << endl;
covMatS->Print();
cout << "background covariance matrix: " << endl;
covMatB->Print();
// produce the square-root matrix
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Float_t* x;
TMatrixD* m;
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
for (Int_t i=0; i<N; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
getGaussRnd( *v, *m, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
// add weights
if (itype == 0) weight = 1.0; // this is the signal weight
else weight = 2.0; // this is the background weight
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot();
}
// create the data
void create_fullcirc(Int_t nmax = 20000, Bool_t distort=false)
{
TFile* dataFile = TFile::Open( "circledata.root", "RECREATE" );
int nvar = 2;
int nsig = 0, nbgd=0;
Float_t weight=1;
Float_t xvar[100];
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar)).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar)).Data() );
}
treeS->Branch("weight", &weight, "weight/F");
treeB->Branch("weight", &weight, "weight/F");
TRandom R( 100 );
do {
for (Int_t ivar=0; ivar<nvar; ivar++) { xvar[ivar]=2.*R.Rndm()-1.;}
Float_t xout = xvar[0]*xvar[0]+xvar[1]*xvar[1];
if (nsig<10) cout << "xout = " << xout<<endl;
if (xout < 0.3 || (xout >0.3 && xout<0.5 && R.Rndm() > xout)) {
if (distort && xvar[0] < 0 && R.Rndm()>0.1) continue;
treeS->Fill();
nsig++;
}
else {
if (distort && xvar[0] > 0 && R.Rndm()>0.1) continue;
treeB->Fill();
nbgd++;
}
} while ( nsig < nmax || nbgd < nmax);
dataFile->Write();
dataFile->Close();
}
// create the data
void create_circ(Int_t N = 6000, Bool_t distort = false)
{
Int_t Nn = 0;
const Int_t nvar = 2;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
}
// TTree *treeB = treeS->CloneTree();
// for (Int_t ivar=0; ivar<nvar; ivar++) {
// treeS->SetBranchAddress( Form( "var%i", ivar ), &xvar[ivar] );
// treeB->SetBranchAddress( Form( "var%i", ivar ), &xvar[ivar] );
// }
// treeB->SetName ( "TreeB" );
// treeB->SetTitle( "TreeB" );
TRandom R( 100 );
//Float_t phimin = -30, phimax = 130;
Float_t phimin = -70, phimax = 130;
Float_t phisig = 5;
Float_t rS = 1.1;
Float_t rB = 0.75;
Float_t rsig = 0.1;
Float_t fnmin = -(rS+4.0*rsig);
Float_t fnmax = +(rS+4.0*rsig);
Float_t dfn = fnmax-fnmin;
// loop over species
for (Int_t itype=0; itype<2; itype++) {
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
for (Int_t i=0; i<N; i++) {
Double_t r1=R.Rndm(),r2=R.Rndm(), r3;
if (itype==0) r3= r1>r2? r1 :r2;
else r3= r2;
Float_t phi;
if (distort) phi = r3*(phimax - phimin) + phimin;
else phi = R.Rndm()*(phimax - phimin) + phimin;
phi += R.Gaus()*phisig;
Float_t r = (itype==0) ? rS : rB;
r += R.Gaus()*rsig;
xvar[0] = r*cos(TMath::DegToRad()*phi);
xvar[1] = r*sin(TMath::DegToRad()*phi);
tree->Fill();
}
for (Int_t i=0; i<Nn; i++) {
xvar[0] = dfn*R.Rndm()+fnmin;
xvar[1] = dfn*R.Rndm()+fnmin;
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot();
}
void create_schachbrett(Int_t nEvents = 20000) {
const Int_t nvar = 2;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
}
Int_t nSeed = 12345;
TRandom *m_rand = new TRandom(nSeed);
Double_t sigma=0.3;
Double_t meanX;
Double_t meanY;
Int_t xtype=1, ytype=1;
Int_t iev=0;
Int_t m_nDim = 2; // actually the boundary, there is a "bump" for every integer value
// between in the Interval [-m_nDim,m_nDim]
while (iev < nEvents){
xtype=1;
for (Int_t i=-m_nDim; i <= m_nDim; i++){
ytype = 1;
for (Int_t j=-m_nDim; j <= m_nDim; j++){
meanX=Double_t(i);
meanY=Double_t(j);
xvar[0]=m_rand->Gaus(meanY,sigma);
xvar[1]=m_rand->Gaus(meanX,sigma);
Int_t type = xtype*ytype;
TTree* tree = (type==1) ? treeS : treeB;
tree->Fill();
iev++;
ytype *= -1;
}
xtype *= -1;
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot();
}
void create_schachbrett_5D(Int_t nEvents = 200000) {
const Int_t nvar = 5;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
}
Int_t nSeed = 12345;
TRandom *m_rand = new TRandom(nSeed);
Double_t sigma=0.3;
Int_t itype[nvar];
Int_t iev=0;
Int_t m_nDim = 2; // actually the boundary, there is a "bump" for every integer value
// between in the Interval [-m_nDim,m_nDim]
int idx[nvar];
while (iev < nEvents){
itype[0]=1;
for (idx[0]=-m_nDim; idx[0] <= m_nDim; idx[0]++){
itype[1]=1;
for (idx[1]=-m_nDim; idx[1] <= m_nDim; idx[1]++){
itype[2]=1;
for (idx[2]=-m_nDim; idx[2] <= m_nDim; idx[2]++){
itype[3]=1;
for (idx[3]=-m_nDim; idx[3] <= m_nDim; idx[3]++){
itype[4]=1;
for (idx[4]=-m_nDim; idx[4] <= m_nDim; idx[4]++){
Int_t type = itype[0];
for (Int_t i=0;i<nvar;i++){
xvar[i]=m_rand->Gaus(Double_t(idx[i]),sigma);
if (i>0) type *= itype[i];
}
TTree* tree = (type==1) ? treeS : treeB;
tree->Fill();
iev++;
itype[4] *= -1;
}
itype[3] *= -1;
}
itype[2] *= -1;
}
itype[1] *= -1;
}
itype[0] *= -1;
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot();
}
void create_schachbrett_4D(Int_t nEvents = 200000) {
const Int_t nvar = 4;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
}
Int_t nSeed = 12345;
TRandom *m_rand = new TRandom(nSeed);
Double_t sigma=0.3;
Int_t itype[nvar];
Int_t iev=0;
Int_t m_nDim = 2; // actually the boundary, there is a "bump" for every integer value
// between in the Interval [-m_nDim,m_nDim]
int idx[nvar];
while (iev < nEvents){
itype[0]=1;
for (idx[0]=-m_nDim; idx[0] <= m_nDim; idx[0]++){
itype[1]=1;
for (idx[1]=-m_nDim; idx[1] <= m_nDim; idx[1]++){
itype[2]=1;
for (idx[2]=-m_nDim; idx[2] <= m_nDim; idx[2]++){
itype[3]=1;
for (idx[3]=-m_nDim; idx[3] <= m_nDim; idx[3]++){
Int_t type = itype[0];
for (Int_t i=0;i<nvar;i++){
xvar[i]=m_rand->Gaus(Double_t(idx[i]),sigma);
if (i>0) type *= itype[i];
}
TTree* tree = (type==1) ? treeS : treeB;
tree->Fill();
iev++;
itype[3] *= -1;
}
itype[2] *= -1;
}
itype[1] *= -1;
}
itype[0] *= -1;
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot();
}
void create_schachbrett_3D(Int_t nEvents = 20000) {
const Int_t nvar = 3;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
}
Int_t nSeed = 12345;
TRandom *m_rand = new TRandom(nSeed);
Double_t sigma=0.3;
Int_t itype[nvar];
Int_t iev=0;
Int_t m_nDim = 2; // actually the boundary, there is a "bump" for every integer value
// between in the Interval [-m_nDim,m_nDim]
int idx[nvar];
while (iev < nEvents){
itype[0]=1;
for (idx[0]=-m_nDim; idx[0] <= m_nDim; idx[0]++){
itype[1]=1;
for (idx[1]=-m_nDim; idx[1] <= m_nDim; idx[1]++){
itype[2]=1;
for (idx[2]=-m_nDim; idx[2] <= m_nDim; idx[2]++){
Int_t type = itype[0];
for (Int_t i=0;i<nvar;i++){
xvar[i]=m_rand->Gaus(Double_t(idx[i]),sigma);
if (i>0) type *= itype[i];
}
TTree* tree = (type==1) ? treeS : treeB;
tree->Fill();
iev++;
itype[2] *= -1;
}
itype[1] *= -1;
}
itype[0] *= -1;
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot();
}
void create_schachbrett_2D(Int_t nEvents = 100000, Int_t nbumps=2) {
const Int_t nvar = 2;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
}
Int_t nSeed = 345;
TRandom *m_rand = new TRandom(nSeed);
Double_t sigma=0.35;
Int_t itype[nvar];
Int_t iev=0;
Int_t m_nDim = nbumps; // actually the boundary, there is a "bump" for every integer value
// between in the Interval [-m_nDim,m_nDim]
int idx[nvar];
while (iev < nEvents){
itype[0]=1;
for (idx[0]=-m_nDim; idx[0] <= m_nDim; idx[0]++){
itype[1]=1;
for (idx[1]=-m_nDim; idx[1] <= m_nDim; idx[1]++){
Int_t type = itype[0];
for (Int_t i=0;i<nvar;i++){
xvar[i]=m_rand->Gaus(Double_t(idx[i]),sigma);
if (i>0) type *= itype[i];
}
TTree* tree = (type==1) ? treeS : treeB;
tree->Fill();
iev++;
itype[1] *= -1;
}
itype[0] *= -1;
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot();
}
void create_3Bumps(Int_t nEvents = 5000) {
// signal is clustered around (1,0) and (-1,0) where one is two times(1,0)
// bkg (0,0)
const Int_t nvar = 2;
Float_t xvar[nvar];
// output file
TString filename = "data_3Bumps.root";
TFile* dataFile = TFile::Open( filename, "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
treeB->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar )).Data() );
}
Int_t nSeed = 12345;
TRandom *m_rand = new TRandom(nSeed);
Double_t sigma=0.2;
Int_t type;
Int_t iev=0;
Double_t Centers[nvar][6] = {{-1,0,0,0,1,1},{0,0,0,0,0,0}}; //
while (iev < nEvents){
for (int idx=0; idx<6; idx++){
if (idx==1 || idx==2 || idx==3) type = 0;
else type=1;
for (Int_t ivar=0;ivar<nvar;ivar++){
xvar[ivar]=m_rand->Gaus(Centers[ivar][idx],sigma);
}
TTree* tree = (type==1) ? treeS : treeB;
tree->Fill();
iev++;
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
plot(filename);
}
void createOnionData(Int_t nmax = 50000){
// output file
TFile* dataFile = TFile::Open( "oniondata.root", "RECREATE" );
int nvar = 4;
int nsig = 0, nbgd=0;
Float_t xvar[100];
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeS->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
treeB->Branch( TString(Form( "var%i", ivar+1 )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar+1 )).Data() );
}
TRandom R( 100 );
do {
for (Int_t ivar=0; ivar<nvar; ivar++) { xvar[ivar]=R.Rndm();}
Float_t xout = sin(2.*acos(-1.)*(xvar[0]*xvar[1]*xvar[2]*xvar[3]+xvar[0]*xvar[1]));
if (nsig<100) cout << "xout = " << xout<<endl;
Int_t i = (Int_t) ((1.+xout)*4.99);
if (i%2 == 0 && nsig < nmax) {
treeS->Fill();
nsig++;
}
if (i%2 != 0 && nbgd < nmax){
treeB->Fill();
nbgd++;
}
} while ( nsig < nmax || nbgd < nmax);
dataFile->Write();
dataFile->Close();
}
void create_multiclassdata(Int_t nmax = 20000)
{
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
int ncls = 3;
int nvar = 4;
int ndat = 0;
Int_t cls;
Float_t thecls;
Float_t weight=1;
Float_t xcls[100];
Float_t xmean[3][4] = {
{ 0. , 0.3, 0.5, 0.9 },
{ -0.2 , -0.3, 0.5, 0.4 },
{ 0.2 , 0.1, -0.1, 0.7 }} ;
Float_t xvar[100];
// create tree using class flag stored in int variable cls
TTree* treeR = new TTree( "TreeR", "TreeR", 1 );
for (Int_t ivar=0; ivar<nvar; ivar++) {
treeR->Branch( TString(Form( "var%i", ivar )).Data(), &xvar[ivar], TString(Form( "var%i/F", ivar)).Data() );
}
for (Int_t icls=0; icls<ncls; icls++) {
treeR->Branch(TString(Form( "cls%i", icls )).Data(), &xcls[icls], TString(Form( "cls%i/F", icls)).Data() );
}
treeR->Branch("cls", &thecls, "cls/F");
treeR->Branch("weight", &weight, "weight/F");
TRandom R( 100 );
do {
for (Int_t icls=0; icls<ncls; icls++) xcls[icls]=0.;
cls = R.Integer(ncls);
thecls = cls;
xcls[cls]=1.;
for (Int_t ivar=0; ivar<nvar; ivar++) {
xvar[ivar]=R.Gaus(xmean[cls][ivar],1.);
}
if (ndat<30) cout << "cls=" << cls <<" xvar = " << xvar[0]<<" " <<xvar[1]<<" " << xvar[2]<<" " <<xvar[3]<<endl;
treeR->Fill();
ndat++;
} while ( ndat < nmax );
dataFile->Write();
dataFile->Close();
}
// create the data
void create_array_with_different_lengths(Int_t N = 100)
{
const Int_t nvar = 4;
Int_t nvarCurrent = 4;
Float_t xvar[nvar];
// output file
TFile* dataFile = TFile::Open( "data.root", "RECREATE" );
// create signal and background trees
TTree* treeS = new TTree( "TreeS", "TreeS", 1 );
TTree* treeB = new TTree( "TreeB", "TreeB", 1 );
treeS->Branch( "arrSize", &nvarCurrent, "arrSize/I" );
treeS->Branch( "arr", xvar, "arr[arrSize]/F" );
treeB->Branch( "arrSize", &nvarCurrent, "arrSize/I" );
treeB->Branch( "arr", xvar, "arr[arrSize]/F" );
TRandom R( 100 );
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
Float_t xB[nvar] = { -0.2, -0.3, -0.5, -0.6 };
Float_t dx[nvar] = { 1.0, 1.0, 1.0, 1.0 };
TArrayD* v = new TArrayD( nvar );
Float_t rho[20];
rho[1*2] = 0.4;
rho[1*3] = 0.6;
rho[1*4] = 0.9;
rho[2*3] = 0.7;
rho[2*4] = 0.8;
rho[3*4] = 0.93;
// create covariance matrix
TMatrixD* covMatS = new TMatrixD( nvar, nvar );
TMatrixD* covMatB = new TMatrixD( nvar, nvar );
for (Int_t ivar=0; ivar<nvar; ivar++) {
(*covMatS)(ivar,ivar) = dx[ivar]*dx[ivar];
(*covMatB)(ivar,ivar) = dx[ivar]*dx[ivar];
for (Int_t jvar=ivar+1; jvar<nvar; jvar++) {
(*covMatS)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatS)(jvar,ivar) = (*covMatS)(ivar,jvar);
(*covMatB)(ivar,jvar) = rho[(ivar+1)*(jvar+1)]*dx[ivar]*dx[jvar];
(*covMatB)(jvar,ivar) = (*covMatB)(ivar,jvar);
}
}
cout << "signal covariance matrix: " << endl;
covMatS->Print();
cout << "background covariance matrix: " << endl;
covMatB->Print();
// produce the square-root matrix
TMatrixD* sqrtMatS = produceSqrtMat( *covMatS );
TMatrixD* sqrtMatB = produceSqrtMat( *covMatB );
// loop over species
for (Int_t itype=0; itype<2; itype++) {
Float_t* x;
TMatrixD* m;
if (itype == 0) { x = xS; m = sqrtMatS; cout << "- produce signal" << endl; }
else { x = xB; m = sqrtMatB; cout << "- produce background" << endl; }
// event loop
TTree* tree = (itype==0) ? treeS : treeB;
for (Int_t i=0; i<N; i++) {
if (i%1000 == 0) cout << "... event: " << i << " (" << N << ")" << endl;
getGaussRnd( *v, *m, R );
for (Int_t ivar=0; ivar<nvar; ivar++) xvar[ivar] = (*v)[ivar] + x[ivar];
nvarCurrent = (i%4)+1;
tree->Fill();
}
}
// write trees
treeS->Write();
treeB->Write();
treeS->Show(0);
treeB->Show(1);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
}
// create the data
void create_MultipleBackground(Int_t N = 50000)
{
const int nvar = 4;
// output file
TFile* dataFile = TFile::Open( "tmva_example_multiple_background.root", "RECREATE" );
Float_t xS[nvar] = { 0.2, 0.3, 0.5, 0.9 };
Float_t xB0[nvar] = { -0.2, -0.3, -0.5, -0.6 };
Float_t xB1[nvar] = { -0.2, 0.3, 0.5, -0.6 };
Float_t dx0[nvar] = { 1.0, 1.0, 1.0, 1.0 };
Float_t dx1[nvar] = { -1.0, -1.0, -1.0, -1.0 };
// create signal and background trees
TTree* treeS = makeTree_lin_Nvar( "TreeS", "Signal tree", xS, dx0, nvar, N );
TTree* treeB0 = makeTree_lin_Nvar( "TreeB0", "Background 0", xB0, dx0, nvar, N );
TTree* treeB1 = makeTree_lin_Nvar( "TreeB1", "Background 1", xB1, dx1, nvar, N );
TTree* treeB2 = makeTree_circ( "TreeB2", "Background 2", nvar, N, 1.5, true);
treeS->Write();
treeB0->Write();
treeB1->Write();
treeB2->Write();
//treeS->Show(0);
//treeB0->Show(0);
//treeB1->Show(0);
//treeB2->Show(0);
dataFile->Close();
cout << "created data file: " << dataFile->GetName() << endl;
}
c
#define c(i)
Definition RSha256.hxx:101
h
#define h(i)
Definition RSha256.hxx:106
R
#define R(a, b, c, d, e, f, g, h, i)
Definition RSha256.hxx:110
size
size_t size(const MatrixT &matrix)
retrieve the size of a square matrix
Bool_t
bool Bool_t
Definition RtypesCore.h:63
Int_t
int Int_t
Definition RtypesCore.h:45
Float_t
float Float_t
Definition RtypesCore.h:57
Double_t
double Double_t
Definition RtypesCore.h:59
TRangeDynCast
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
Definition TCollection.h:358
N
#define N
plot
winID h TVirtualViewer3D TVirtualGLPainter char TVirtualGLPainter plot
Definition TGWin32VirtualGLProxy.cxx:53
filename
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t GCValues_t GetPrimarySelectionOwner GetDisplay GetScreen GetColormap GetNativeEvent const char const char dpyName wid window const char font_name cursor keysym reg const char only_if_exist regb h Point_t winding char text const char depth char const char Int_t count const char ColorStruct_t color const char filename
Definition TGWin32VirtualXProxy.cxx:232
offset
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t GCValues_t GetPrimarySelectionOwner GetDisplay GetScreen GetColormap GetNativeEvent const char const char dpyName wid window const char font_name cursor keysym reg const char only_if_exist regb h Point_t winding char text const char depth char const char Int_t count const char ColorStruct_t color const char Pixmap_t Pixmap_t PictureAttributes_t attr const char char ret_data h unsigned char height h offset
Definition TGWin32VirtualXProxy.cxx:245
r
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t r
Definition TGWin32VirtualXProxy.cxx:168
type
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t Int_t Int_t Window_t TString Int_t GCValues_t GetPrimarySelectionOwner GetDisplay GetScreen GetColormap GetNativeEvent const char const char dpyName wid window const char font_name cursor keysym reg const char only_if_exist regb h Point_t winding char text const char depth char const char Int_t count const char ColorStruct_t color const char Pixmap_t Pixmap_t PictureAttributes_t attr const char char ret_data h unsigned char height h Atom_t Int_t ULong_t ULong_t unsigned char prop_list Atom_t Atom_t Atom_t Time_t type
Definition TGWin32VirtualXProxy.cxx:249
xmin
float xmin
Definition THbookFile.cxx:95
ymin
float ymin
Definition THbookFile.cxx:95
xmax
float xmax
Definition THbookFile.cxx:95
ymax
float ymax
Definition THbookFile.cxx:95
TMatrixD
TMatrixT< Double_t > TMatrixD
Definition TMatrixDfwd.h:23
gROOT
#define gROOT
Definition TROOT.h:406
gRandom
R__EXTERN TRandom * gRandom
Definition TRandom.h:62
Form
char * Form(const char *fmt,...)
Formats a string in a circular formatting buffer.
Definition TString.cxx:2489
TArrayD
Array of doubles (64 bits per element).
Definition TArrayD.h:27
TCanvas
The Canvas class.
Definition TCanvas.h:23
TFile
A ROOT file is an on-disk file, usually with extension .root, that stores objects in a file-system-li...
Definition TFile.h:53
TFile::Open
static TFile * Open(const char *name, Option_t *option="", const char *ftitle="", Int_t compress=ROOT::RCompressionSetting::EDefaults::kUseCompiledDefault, Int_t netopt=0)
Create / open a file.
Definition TFile.cxx:4088
TH1F
1-D histogram with a float per channel (see TH1 documentation)
Definition TH1.h:645
TH2F
2-D histogram with a float per channel (see TH1 documentation)
Definition TH2.h:303
TLegend
This class displays a legend box (TPaveText) containing several legend entries.
Definition TLegend.h:23
TRandom
This is the base class for the ROOT Random number generators.
Definition TRandom.h:27
TRandom::Rndm
Double_t Rndm() override
Machine independent random number generator.
Definition TRandom.cxx:559
TString
Basic string class.
Definition TString.h:139
TString::Data
const char * Data() const
Definition TString.h:376
TStyle
TStyle objects may be created to define special styles.
Definition TStyle.h:29
TTree
A TTree represents a columnar dataset.
Definition TTree.h:79
ROOT::VecOps::acos
RVec< PromoteType< T > > acos(const RVec< T > &v)
Definition RVec.hxx:1855
sigma
const Double_t sigma
Definition h1analysisProxy.h:11
y
Double_t y[n]
Definition legend1.C:17
x
Double_t x[n]
Definition legend1.C:17
TMVA_SOFIE_GNN_Parser.tmp
tmp
Definition TMVA_SOFIE_GNN_Parser.py:196
TMVA_SOFIE_GNN_Parser.tree
tree
Definition TMVA_SOFIE_GNN_Parser.py:169
TMath::Gaus
Double_t Gaus(Double_t x, Double_t mean=0, Double_t sigma=1, Bool_t norm=kFALSE)
Calculates a gaussian function with mean and sigma.
Definition TMath.cxx:471
TMath::Nint
Int_t Nint(T x)
Round to nearest integer. Rounds half integers to the nearest even integer.
Definition TMath.h:697
TMath::Max
Short_t Max(Short_t a, Short_t b)
Returns the largest of a and b.
Definition TMathBase.h:250
TMath::Log
Double_t Log(Double_t x)
Returns the natural logarithm of x.
Definition TMath.h:760
TMath::DegToRad
constexpr Double_t DegToRad()
Conversion from degree to radian: .
Definition TMath.h:79
TMath::Sqrt
Double_t Sqrt(Double_t x)
Returns the square root of x.
Definition TMath.h:666
TMath::Min
Short_t Min(Short_t a, Short_t b)
Returns the smallest of a and b.
Definition TMathBase.h:198
TMath::Pi
constexpr Double_t Pi()
Definition TMath.h:37
TMath::Sin
Double_t Sin(Double_t)
Returns the sine of an angle of x radians.
Definition TMath.h:592
TMath::Abs
Short_t Abs(Short_t d)
Returns the absolute value of parameter Short_t d.
Definition TMathBase.h:123
v
@ v
Definition rootcling_impl.cxx:3699
m
TMarker m
Definition textangle.C:8
l
TLine l
Definition textangle.C:4
sum
static uint64_t sum(uint64_t i)
Definition Factory.cxx:2345
Author
Andreas Hoecker

Definition in file createData.C.