TGraphErrors* plotTG(int i,bool isSum, int ntheta, TString dirname, int marker, int color){
if(ntheta==5){
if(!isSum)
TFile *f = TFile::Open(Form("%s/M%d%d/mergedv_Prod2.root",dirname.Data(),trkpointmax[i],trkpointmin[i]));
else
TFile *f = TFile::Open(Form("%s/M%d%d/mergedv_Prod.root",dirname.Data(),trkpointmax[i],trkpointmin[i]));
}
else{
if(!isSum)
TFile *f = TFile::Open(Form("theta%d/%s/M%d%d/mergedv_Prod2.root",ntheta,dirname.Data(),trkpointmax[i],trkpointmin[i]));
else
TFile *f = TFile::Open(Form("theta%d/%s/M%d%d/mergedv_Prod.root",ntheta,dirname.Data(),trkpointmax[i],trkpointmin[i]));
}
TVectorD *vecDv2 = (TVectorD*)f->Get(Form("D_%d/vmean",ibin));
TVectorD *vecDv2err = (TVectorD*)f->Get(Form("D_%d/deltavmean",ibin));
TVectorD *vecDavgpt = (TVectorD*)f->Get(Form("D_%d/avgpt",ibin));
double *avgpt = vecDavgpt->GetMatrixArray();
double *v2 = vecDv2->GetMatrixArray();
double *v2err = vecDv2err->GetMatrixArray();
int npt = vecDavgpt->GetNrows();
TGraphErrors *gr=new TGraphErrors(npt,avgpt,v2,0,v2err);
gr->SetMarkerSize(1.3);
gr->SetMarkerStyle(marker);
gr->SetMarkerColor(color);
gr->SetLineColor(color);
f->Close();
return gr;
}
void DrawCell( TMVA::PDEFoamCell *cell, TMVA::PDEFoam *foam,
Double_t x, Double_t y,
Double_t xscale, Double_t yscale )
{
// recursively draw cell and it's daughters
Float_t xsize = xscale*1.5;
Float_t ysize = yscale/3;
if (xsize > 0.15) xsize=0.1; //xscale/2;
if (cell->GetDau0() != NULL) {
TLine *a1 = new TLine(x-xscale/4, y-ysize, x-xscale, y-ysize*2);
a1->SetLineWidth(2);
a1->Draw();
DrawCell(cell->GetDau0(), foam, x-xscale, y-yscale, xscale/2, yscale);
}
if (cell->GetDau1() != NULL){
TLine *a1 = new TLine(x+xscale/4, y-ysize, x+xscale, y-ysize*2);
a1->SetLineWidth(2);
a1->Draw();
DrawCell(cell->GetDau1(), foam, x+xscale, y-yscale, xscale/2, yscale);
}
TPaveText *t = new TPaveText(x-xsize, y-ysize, x+xsize, y+ysize, "NDC");
t->SetBorderSize(1);
t->SetFillStyle(1);
// draw all cell elements
t->AddText( Form("Intg=%.5f", cell->GetIntg()) );
t->AddText( Form("Var=%.5f", cell->GetDriv()) );
TVectorD *vec = (TVectorD*) cell->GetElement();
if (vec != NULL){
for (Int_t i = 0; i < vec->GetNrows(); ++i) {
t->AddText( Form("E[%i]=%.5f", i, vec(i)) );
}
}
if (cell->GetStat() != 1) {
// cell is inactive --> draw split point
t->SetFillColor( TColor::GetColor("#BBBBBB") );
t->SetTextColor( TColor::GetColor("#000000") );
// cell position and size
TMVA::PDEFoamVect cellPosi(foam->GetTotDim()), cellSize(foam->GetTotDim());
cell->GetHcub(cellPosi, cellSize);
Int_t kBest = cell->GetBest(); // best division variable
Double_t xBest = cell->GetXdiv(); // best division point
t->AddText( Form("dim=%i", kBest) );
t->AddText( Form("cut=%.5g", foam->VarTransformInvers(kBest,cellPosi[kBest] + xBest*cellSize[kBest])) );
} else {
t->SetFillColor( TColor::GetColor("#DD0033") );
t->SetTextColor( TColor::GetColor("#FFFFFF") );
}
t->Draw();
return;
}
TMatrixD Chol (TVectorD& covV, TVectorD& newSig)
{
int nCov = covV.GetNrows();
int n = newSig.GetNrows();
std::cout << nCov << " " << n << std::endl;
if ( nCov != n*(n+1)/2. ) {
std::cout << "vecTest: mismatch in inputs" << std::endl;
return TMatrixD();
}
//
// create modified vector (replacing std.dev.s)
//
TVectorD newCovV(covV);
int ind(0);
for ( int i=0; i<n; ++i ) {
for ( int j=0; j<=i; ++j ) {
if ( j==i ) newCovV[ind] = newSig(i);
++ind;
}
}
return Chol(newCovV,newSig);
}
void MultiGaus(const TVectorD& parMeans, const TMatrixDSym& covMatrix, TVectorD& genPars)
{
TRandom3 rnd(0);
int nPars = parMeans.GetNrows();
if(nPars <= 0) {
Error("MultiGaus", "Must have >0 pars");
return;
}
if(covMatrix.GetNrows() != nPars) {
Error("MultiGaus", "parMeans.GetNrows() != covMatrix.GetNrows()");
return;
}
// Check that covMatrix is symmetric
for(int iRow = 0; iRow < nPars; iRow++) {
for(int iCol = iRow; iCol < nPars; iCol++) {
if(covMatrix(iRow, iCol) != covMatrix(iCol, iRow)) {
Error("MultiGaus", "malformed cov matrix at row %d, col %d", iRow, iCol);
return;
}
}
}
genPars.ResizeTo(nPars);
TMatrixDSymEigen eigenvariances(covMatrix);
TMatrixD V = eigenvariances.GetEigenVectors();
TVectorD rotParMeans = V * parMeans;
for(int iPar = 0; iPar < nPars; iPar++) {
double variance = eigenvariances.GetEigenValues()[iPar];
// check for positive-definiteness of covMatrix
if(variance < 0) {
Error("MultiGaus", "Got a negative eigenvariance (%f) on iPar = %d", variance, iPar);
}
genPars[iPar] = rnd.Gaus(rotParMeans[iPar], sqrt(variance));
}
V.Invert();
genPars = V * genPars;
}
double operator() (double *x, double *p) {
// 4 parameters
int dim = X.GetNrows();
int k = 0;
for (int i = 0; i<dim; ++i) { X[i] = x[i] - p[k]; k++; }
for (int i = 0; i<dim; ++i) {
CovMat(i,i) = p[k]*p[k];
k++;
}
for (int i = 0; i<dim; ++i) {
for (int j = i+1; j<dim; ++j) {
// p now are the correlations N(N-1)/2
CovMat(i,j) = p[k]*sqrt(CovMat(i,i)*CovMat(j,j));
CovMat(j,i) = CovMat(i,j);
k++;
}
}
if (debug) {
X.Print();
CovMat.Print();
}
double det = CovMat.Determinant();
if (det <= 0) {
Fatal("GausND","Determinant is <= 0 det = %f",det);
CovMat.Print();
return 0;
}
double norm = std::pow( 2. * TMath::Pi(), dim/2) * sqrt(det);
// compute the gaussians
CovMat.Invert();
double fval = std::exp( - 0.5 * CovMat.Similarity(X) )/ norm;
if (debug) {
std::cout << "det " << det << std::endl;
std::cout << "norm " << norm << std::endl;
std::cout << "fval " << fval << std::endl;
}
return fval;
}
TMatrixD Chol (TVectorD& covV)
{
int nCov = covV.GetNrows();
int n = int((sqrt(8*nCov+1.)-1.)/2.+0.5);
if ( nCov != n*(n+1)/2. ) {
std::cout << "Chol: length of vector " << nCov << " is not n*(n+1)/2" << std::endl;
return TMatrixD();
}
// get diagonal elements
int ind(0);
TVectorD sigmas(n);
for ( int i=0; i<n; ++i ) {
for ( int j=0; j<=i; ++j ) {
if ( j == i ) sigmas[i] = covV(ind);
++ind;
}
}
// fill cov matrix (could be more elegant ...)
ind = 0;
TMatrixDSym covMatrix(n);
for ( int i=0; i<n; ++i ) {
for ( int j=0; j<=i; ++j ) {
if ( j == i )
covMatrix(i,i) = sigmas(i)*sigmas(i);
else
covMatrix(i,j) = covMatrix(j,i) = covV(ind)*sigmas(i)*sigmas(j);
++ind;
}
}
covMatrix.Print();
TDecompChol tdc(covMatrix);
bool worked = tdc.Decompose();
if ( !worked ) {
std::cout << "Decomposition failed" << std::endl;
return TMatrixD();
}
TMatrixD matU = tdc.GetU();
return matU;
// //
// // cross check with random generation
// //
// double sum0(0.);
// TVectorD sum1(n);
// TMatrixDSym sum2(n);
// TRandom2 rgen;
// TVectorD xrnd(n);
// TVectorD xrndRot(n);
// for ( unsigned int i=0; i<1000000; ++i ) {
// for ( unsigned int j=0; j<n; ++j ) xrnd(j) = 0.;
// for ( unsigned int j=0; j<n; ++j ) {
// TVectorD aux(n);
// for ( int k=0; k<n; ++k ) aux(k) = matU(j,k);
// xrnd += rgen.Gaus(0.,1.)*aux;
// }
// // xrnd *= matUT;
// sum0 += 1.;
// for ( unsigned int j0=0; j0<n; ++j0 ) {
// sum1(j0) += xrnd(j0);
// for ( unsigned int j1=0; j1<n; ++j1 ) {
// sum2(j0,j1) += xrnd(j0)*xrnd(j1);
// }
// }
// }
// for ( unsigned int j0=0; j0<n; ++j0 ) {
// printf("%10.3g",sum1(j0)/sum0);
// }
// printf(" sum1 \n");
// printf("\n");
// for ( unsigned int j0=0; j0<n; ++j0 ) {
// for ( unsigned int j1=0; j1<n; ++j1 ) {
// printf("%10.3g",sum2(j0,j1)/sum0);
// }
// printf(" sum2 \n");
// }
// return matU;
}
