#include "TF1.h"
#include "TLinearFitter.h"
+#include "AliExternalTrackParam.h"
+
//
// includes neccessary for test functions
//
}
}
-Double_t AliMathBase::FitGaus(TH1F* his, TVectorD *param, TMatrixD *matrix, Float_t xmin, Float_t xmax, Bool_t verbose){
+Double_t AliMathBase::FitGaus(TH1F* his, TVectorD *param, TMatrixD */*matrix*/, Float_t xmin, Float_t xmax, Bool_t verbose){
//
// Fit histogram with gaussian function
//
Double_t chi2 = fitter.GetChisquare()/Float_t(npoints);
//fitter.GetParameters();
if (!param) param = new TVectorD(3);
- if (!matrix) matrix = new TMatrixD(3,3);
+ //if (!matrix) matrix = new TMatrixD(3,3);
(*param)[1] = par[1]/(-2.*par[2]);
(*param)[2] = 1./TMath::Sqrt(TMath::Abs(-2.*par[2]));
(*param)[0] = TMath::Exp(par[0]+ par[1]* (*param)[1] + par[2]*(*param)[1]*(*param)[1]);
return chi2;
}
-Double_t AliMathBase::FitGaus(Float_t *arr, Int_t nBins, Float_t xMin, Float_t xMax, TVectorD *param, TMatrixD *matrix, Bool_t verbose){
+Double_t AliMathBase::FitGaus(Float_t *arr, Int_t nBins, Float_t xMin, Float_t xMax, TVectorD *param, TMatrixD */*matrix*/, Bool_t verbose){
//
// Fit histogram with gaussian function
//
Float_t entries = 0;
Int_t nfilled=0;
+ if (!param) param = new TVectorD(4);
+
for (Int_t i=0; i<nBins; i++){
entries+=arr[i];
if (arr[i]>0) nfilled++;
if (TMath::Abs(par[1])<kTol) return -4;
if (TMath::Abs(par[2])<kTol) return -4;
- if (!param) param = new TVectorD(4);
+ //if (!param) param = new TVectorD(4);
if ( param->GetNrows()<4 ) param->ResizeTo(4);
- if (!matrix) matrix = new TMatrixD(3,3); // !!!!might be a memory leek. use dummy matrix pointer to call this function!
+ //if (!matrix) matrix = new TMatrixD(3,3); // !!!!might be a memory leek. use dummy matrix pointer to call this function!
(*param)[1] = par[1]/(-2.*par[2]);
(*param)[2] = 1./TMath::Sqrt(TMath::Abs(-2.*par[2]));
}
+Double_t AliMathBase::ErfcFast(Double_t x){
+ // Fast implementation of the complementary error function
+ // The error of the approximation is |eps(x)| < 5E-4
+ // See Abramowitz and Stegun, p.299, 7.1.27
+
+ Double_t z = TMath::Abs(x);
+ Double_t ans = 1+z*(0.278393+z*(0.230389+z*(0.000972+z*0.078108)));
+ ans = 1.0/ans;
+ ans *= ans;
+ ans *= ans;
+
+ return (x>=0.0 ? ans : 2.0 - ans);
+}
///////////////////////////////////////////////////////////////
////////////// TEST functions /////////////////////////
// TAxis * zaxis = his->GetZaxis();
Int_t nbinx = xaxis->GetNbins();
Int_t nbiny = yaxis->GetNbins();
- char name[1000];
+ const Int_t nc=1000;
+ char name[nc];
Int_t icount=0;
TGraph2D *graph = new TGraph2D(nbinx*nbiny);
TF1 f1("f1","gaus");
for (Int_t iy=0; iy<nbiny;iy++){
Float_t xcenter = xaxis->GetBinCenter(ix);
Float_t ycenter = yaxis->GetBinCenter(iy);
- sprintf(name,"%s_%d_%d",his->GetName(), ix,iy);
+ snprintf(name,nc,"%s_%d_%d",his->GetName(), ix,iy);
TH1 *projection = his->ProjectionZ(name,ix-delta0,ix+delta0,iy-delta1,iy+delta1);
Float_t stat= 0;
if (type==0) stat = projection->GetMean();
// TAxis * zaxis = his->GetZaxis();
Int_t nbinx = xaxis->GetNbins();
Int_t nbiny = yaxis->GetNbins();
- char name[1000];
+ const Int_t nc=1000;
+ char name[nc];
Int_t icount=0;
TGraph *graph = new TGraph(nbinx);
TF1 f1("f1","gaus");
for (Int_t ix=0; ix<nbinx;ix++){
Float_t xcenter = xaxis->GetBinCenter(ix);
// Float_t ycenter = yaxis->GetBinCenter(iy);
- sprintf(name,"%s_%d",his->GetName(), ix);
+ snprintf(name,nc,"%s_%d",his->GetName(), ix);
TH1 *projection = his->ProjectionZ(name,ix-delta1,ix+delta1,0,nbiny);
Float_t stat= 0;
if (type==0) stat = projection->GetMean();
}while(TMath::Abs(value-mean)>cutat);
return value;
}
+
+Double_t AliMathBase::TruncatedGaus(Double_t mean, Double_t sigma, Double_t leftCut, Double_t rightCut)
+{
+ // return number generated according to a gaussian distribution N(mean,sigma)
+ // truncated at leftCut and rightCut
+ //
+ Double_t value;
+ do{
+ value=gRandom->Gaus(mean,sigma);
+ }while((value-mean)<-leftCut || (value-mean)>rightCut);
+ return value;
+}
+
+Double_t AliMathBase::BetheBlochAleph(Double_t bg,
+ Double_t kp1,
+ Double_t kp2,
+ Double_t kp3,
+ Double_t kp4,
+ Double_t kp5) {
+ //
+ // This is the empirical ALEPH parameterization of the Bethe-Bloch formula.
+ // It is normalized to 1 at the minimum.
+ //
+ // bg - beta*gamma
+ //
+ // The default values for the kp* parameters are for ALICE TPC.
+ // The returned value is in MIP units
+ //
+
+ return AliExternalTrackParam::BetheBlochAleph(bg,kp1,kp2,kp3,kp4,kp5);
+}