本文整理汇总了C++中TF1::GetParErrors方法的典型用法代码示例。如果您正苦于以下问题：C++ TF1::GetParErrors方法的具体用法？C++ TF1::GetParErrors怎么用？C++ TF1::GetParErrors使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类TF1的用法示例。
在下文中一共展示了TF1::GetParErrors方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: drawPrunedJM_noDiboson
void drawPrunedJM_noDiboson(){
gStyle->SetOptStat(0);
gStyle->SetOptFit(11111111);
TFile *f = TFile::Open("prunedJetMMu_noDiboson.root");
TH1D* h_MCWW = (TH1D*)(f->Get("prunedJetMMu_WW_pythia_filtered"));
TH1D* h_MCWZ = (TH1D*)(f->Get("prunedJetMMu_WZ_pythia_filtered"));
TH1D* h_MCZZ = (TH1D*)(f->Get("prunedJetMMu_ZZ_pythia_filtered"));
TH1D* h_dataMu = (TH1D*)(f->Get("prunedJetMMu_data_DoubleMu"));
Double_t lumi_MCWW = 9959752/56.0;
Double_t lumi_MCWZ = 9910267/22.4;
Double_t lumi_MCZZ = 9769891/7.6;
Double_t lumi_dataMu = 19671.225;
h_MCWW->Scale(lumi_dataMu/lumi_MCWW);
h_MCWZ->Scale(lumi_dataMu/lumi_MCWZ);
h_MCZZ->Scale(lumi_dataMu/lumi_MCZZ);
TH1D* h_allDibosonMC = new TH1D("h_allDibosonMC", "", 100, 40, 240);
h_allDibosonMC->Add(h_MCWW);
h_allDibosonMC->Add(h_MCWZ);
h_allDibosonMC->Add(h_MCZZ);
TH1D* h_dataMu_noDiboson = new TH1D("h_dataMu_noDiboson", "", 100, 40, 240);
h_dataMu_noDiboson->SetTitle("Pruned jet mass distribution (data)");
h_dataMu_noDiboson->GetXaxis()->SetTitle("Mass");
h_dataMu_noDiboson->GetYaxis()->SetTitle("Event numbers");
Int_t NBIN = h_allDibosonMC->GetNbinsX();
for(Int_t i = 1; i < NBIN; i++){
Int_t binCenter = h_dataMu_noDiboson->GetBinCenter(i);
Int_t binContent = h_dataMu->GetBinContent(i) - h_allDibosonMC->GetBinContent(i);
if( binCenter > 110 && binCenter < 140 ) continue;
h_dataMu_noDiboson->SetBinContent(i, binContent);
}
TF1* fitCurve = new TF1("fitCurve", fitFunc, 40, 240, 4);
h_dataMu_noDiboson->Fit(fitCurve, "", "", 40, 240);
Double_t nBkgSig = fitCurve->Integral(110,140)/h_dataMu->GetBinWidth(1);
vector<Double_t> par;
vector<Double_t> posPar;
vector<Double_t> negPar;
for(Int_t i = 0; i < 4; i++){
par.push_back(fitCurve->GetParameters()[i]);
posPar.push_back(par[i] + fitCurve->GetParErrors()[i]);
negPar.push_back(par[i] - fitCurve->GetParErrors()[i]);
}
Double_t x;
TF1* posFit[4];
posFit[0] = new TF1("posFit1",
Form("%f*TMath::Exp(%f*x)*0.5*(1+TMath::Erf((x-(%f))/%f))",posPar[0],par[1],par[2],par[3]),
40, 240);
posFit[1] = new TF1("posFit2",
Form("%f*TMath::Exp(%f*x)*0.5*(1+TMath::Erf((x-(%f))/%f))",par[0],posPar[1],par[2],par[3]),
40, 240);
posFit[2] = new TF1("posFit3",
Form("%f*TMath::Exp(%f*x)*0.5*(1+TMath::Erf((x-(%f))/%f))",par[0],par[1],posPar[2],par[3]),
40, 240);
posFit[3] = new TF1("posFit4",
Form("%f*TMath::Exp(%f*x)*0.5*(1+TMath::Erf((x-(%f))/%f))",par[0],par[1],par[2],posPar[3]),
40, 240);
TF1* negFit[4];
negFit[0] = new TF1("negFit1",
Form("%f*TMath::Exp(%f*x)*0.5*(1+TMath::Erf((x-(%f))/%f))",negPar[0],par[1],par[2],par[3]),
40, 240);
negFit[1] = new TF1("negFit2",
Form("%f*TMath::Exp(%f*x)*0.5*(1+TMath::Erf((x-(%f))/%f))",par[0],negPar[1],par[2],par[3]),
40, 240);
negFit[2] = new TF1("negFit3",
Form("%f*TMath::Exp(%f*x)*0.5*(1+TMath::Erf((x-(%f))/%f))",par[0],par[1],negPar[2],par[3]),
40, 240);
negFit[3] = new TF1("negFit4",
Form("%f*TMath::Exp(%f*x)*0.5*(1+TMath::Erf((x-(%f))/%f))",par[0],par[1],par[2],negPar[3]),
40, 240);
TMatrixD posColM(4,1);
TMatrixD negColM(4,1);
TMatrixD posRowM(1,4);
TMatrixD negRowM(1,4);
for(Int_t i = 0; i < 4; i++){
posColM(i,0) = fabs(nBkgSig - posFit[i]->Integral(110,140)/h_dataMu->GetBinWidth(1));
negColM(i,0) = fabs(nBkgSig - negFit[i]->Integral(110,140)/h_dataMu->GetBinWidth(1));
//.........这里部分代码省略.........
示例2: doFit
Stat_t AnalysisClass::doFit(Int_t RunNumber,Char_t *Variable, Char_t *SubDetName, Char_t *Layer,Char_t *label){
TH1 *htoFit=0;
pLanGausS[0]=0; pLanGausS[1]=0; pLanGausS[2]=0; pLanGausS[3]=0;
epLanGausS[0]=0; epLanGausS[1]=0; epLanGausS[2]=0; epLanGausS[3]=0;
if (debug) cout << d1->GetTitle() << " " << Variable << " " << SubDetName << endl;
pPar[0]=0; pPar[1]=0;
TIter it(d1->GetListOfKeys());
TObject * o;
while ( (o = it()))
{
TObject * d = d1->Get(o->GetName());
if(d->IsA()->InheritsFrom("TDirectory") && strstr(d->GetName(),SubDetName)){
if (debug) cout << "Found " << SubDetName << endl;
TIter it2(((TDirectoryFile * )d)->GetListOfKeys());
TObject *o2;
while( ( o2 = it2()) ){
TObject *d2 = ((TDirectoryFile * )d)->Get(o2->GetName());
if(d2->IsA()->InheritsFrom("TDirectory") && strstr(d2->GetName(),Layer) ){
if (debug) cout << "Found Layer" << Layer << endl;
TIter it3(((TDirectoryFile * )d2)->GetListOfKeys());
TObject *o3;
while( ( o3 = it3()) ){
TObject *d3 = ((TDirectoryFile * )d2)->Get(o3->GetName());
if(strstr(d3->GetName(),Variable) && strstr(d3->GetName(),label)){
htoFit = (TH1*) d3;
if (debug) cout << "Found " << Variable << endl;
if (htoFit->GetEntries()!=0) {
cout<<"Fitting "<< htoFit->GetTitle() <<endl;
// Setting fit range and start values
Double_t fr[2];
Double_t sv[4], pllo[4], plhi[4];
fr[0]=0.5*htoFit->GetMean();
fr[1]=3.0*htoFit->GetMean();
// (EM) parameters setting good for signal only
Int_t imax=htoFit->GetMaximumBin();
Double_t xmax=htoFit->GetBinCenter(imax);
Double_t ymax=htoFit->GetBinContent(imax);
Int_t i[2];
Int_t iArea[2];
i[0]=htoFit->GetXaxis()->FindBin(fr[0]);
i[1]=htoFit->GetXaxis()->FindBin(fr[1]);
iArea[0]=htoFit->GetXaxis()->FindBin(fr[0]);
iArea[1]=htoFit->GetXaxis()->FindBin(fr[1]);
Double_t AreaFWHM=htoFit->Integral(iArea[0],iArea[1],"width");
sv[1]=xmax;
sv[2]=htoFit->Integral(i[0],i[1],"width");
sv[3]=AreaFWHM/(4*ymax);
sv[0]=sv[3];
plhi[0]=25.0; plhi[1]=200.0; plhi[2]=1000000.0; plhi[3]=50.0;
pllo[0]=1.5 ; pllo[1]=10.0 ; pllo[2]=1.0 ; pllo[3]= 1.0;
// create different landau+gaussians for different runs
Char_t FunName[100];
sprintf(FunName,"FitfcnLG_%s%d",htoFit->GetName(),fRun);
TF1 *ffitold = (TF1*)gROOT->GetListOfFunctions()->FindObject(FunName);
if (ffitold) delete ffitold;
langausFit = new TF1(FunName,langaufun,fr[0],fr[1],4);
langausFit->SetParameters(sv);
langausFit->SetParNames("Width","MP","Area","GSigma");
for (Int_t i=0; i<4; i++) {
langausFit->SetParLimits(i,pllo[i],plhi[i]);
}
htoFit->Fit(langausFit,"R0"); // "R" fit in a range,"0" quiet fit
langausFit->SetRange(fr[0],fr[1]);
pLanGausS=langausFit->GetParameters();
epLanGausS=langausFit->GetParErrors();
chi2GausS =langausFit->GetChisquare(); // obtain chi^2
nDofGausS = langausFit->GetNDF(); // obtain ndf
Double_t sPeak, sFWHM;
langaupro(pLanGausS,sPeak,sFWHM);
pLanConv[0]=sPeak;
pLanConv[1]=sFWHM;
cout << "langaupro: max " << sPeak << endl;
cout << "langaupro: FWHM " << sFWHM << endl;
TCanvas *cAll = new TCanvas("Fit",htoFit->GetTitle(),1);
Char_t fitFileName[60];
sprintf(fitFileName,"Fits/Run_%d/%s/Fit_%s.png",RunNumber,SubDetName,htoFit->GetTitle());
htoFit->Draw("pe");
htoFit->SetStats(100);
langausFit->Draw("lsame");
gStyle->SetOptFit(1111111);
cAll->Print(fitFileName,"png");
}
else {
pLanGausS[0]=-10; pLanGausS[1]=-10; pLanGausS[2]=-10; pLanGausS[3]=-10;
//.........这里部分代码省略.........
示例3: doNoiseFit
//Noise section
Stat_t AnalysisClass::doNoiseFit(Int_t RunNumber, Char_t *Variable, Char_t *SubDetName, Char_t *Layer, Char_t *label){
TH1 *hNtoFit=0;
if (debug) cout << d1->GetTitle() << " " << Variable << " " << SubDetName << endl;
pPar[0]=0; pPar[1]=0;
TIter it(d1->GetListOfKeys());
TObject * o;
while ( (o = it()))
{
TObject * d = d1->Get(o->GetName());
if(d->IsA()->InheritsFrom("TDirectory") && strstr(d->GetName(),SubDetName)){
if (debug) cout << "Found " << SubDetName << endl;
TIter it2(((TDirectoryFile * )d)->GetListOfKeys());
TObject *o2;
while( ( o2 = it2()) ){
TObject *d2 = ((TDirectoryFile * )d)->Get(o2->GetName());
if(d2->IsA()->InheritsFrom("TDirectory") && strstr(d2->GetName(),Layer) ){
if (debug) cout << "Found Layer" << Layer << endl;
TIter it3(((TDirectoryFile * )d2)->GetListOfKeys());
TObject *o3;
while( ( o3 = it3()) ){
TObject *d3 = ((TDirectoryFile * )d2)->Get(o3->GetName());
if(strstr(d3->GetName(),Variable) && strstr(d3->GetName(),label)){
hNtoFit = (TH1*) d3;
if (debug) cout << "Found " << Variable << endl;
if (hNtoFit->GetEntries()!=0) {
cout<<"Fitting "<< hNtoFit->GetTitle() <<endl;
// Setting fit range and start values
Double_t fr[2];
Double_t sv[3], pllo[3], plhi[3];
fr[0]=hNtoFit->GetMean()-5*hNtoFit->GetRMS();
fr[1]=hNtoFit->GetMean()+5*hNtoFit->GetRMS();
Int_t imax=hNtoFit->GetMaximumBin();
Double_t xmax=hNtoFit->GetBinCenter(imax);
Double_t ymax=hNtoFit->GetBinContent(imax);
Int_t i[2];
Int_t iArea[2];
i[0]=hNtoFit->GetXaxis()->FindBin(fr[0]);
i[1]=hNtoFit->GetXaxis()->FindBin(fr[1]);
iArea[0]=hNtoFit->GetXaxis()->FindBin(fr[0]);
iArea[1]=hNtoFit->GetXaxis()->FindBin(fr[1]);
Double_t AreaFWHM=hNtoFit->Integral(iArea[0],iArea[1],"width");
sv[2]=AreaFWHM/(4*ymax);
sv[1]=xmax;
sv[0]=hNtoFit->Integral(i[0],i[1],"width");
plhi[0]=1000000.0; plhi[1]=10.0; plhi[2]=10.;
pllo[0]=1.5 ; pllo[1]=0.1; pllo[2]=0.3;
Char_t FunName[100];
sprintf(FunName,"FitfcnLG_%s%d",hNtoFit->GetName(),fRun);
TF1 *ffitold = (TF1*)gROOT->GetListOfFunctions()->FindObject(FunName);
if (ffitold) delete ffitold;
gausFit = new TF1(FunName,Gauss,fr[0],fr[1],3);
gausFit->SetParameters(sv);
gausFit->SetParNames("Constant","GaussPeak","Sigma");
for (Int_t i=0; i<3; i++) {
gausFit->SetParLimits(i,pllo[i],plhi[i]);
}
hNtoFit->Fit(gausFit,"R0");
gausFit->SetRange(fr[0],fr[1]);
pGausS=gausFit->GetParameters();
epGausS=gausFit->GetParErrors();
chi2GausS =langausFit->GetChisquare(); // obtain chi^2
nDofGausS = langausFit->GetNDF();// obtain ndf
TCanvas *cAllN = new TCanvas("NoiseFit",hNtoFit->GetTitle(),1);
Char_t fitFileName[60];
sprintf(fitFileName,"Fits/Run_%d/%s/Fit_%s.png",RunNumber,SubDetName,hNtoFit->GetTitle());
hNtoFit->Draw("pe");
gStyle->SetOptFit(1111111);
gausFit->Draw("lsame");
cAllN->Print(fitFileName,"png");
}else {
pGausS[0]=-10; pGausS[1]=-10; pGausS[2]=-10;
epGausS[0]=-10; epGausS[1]=-10; epGausS[2]=-10;
}
}
}
}
}
}
}
return hNtoFit->GetEntries();
}示例4: fileOutName
/**
* This function fits TH2F slices with a selected fitType function (gaussian, lorentz, ...).
*/
TGraphErrors* fit2DProj(TString name, TString path, int minEntries, int rebinX, int rebinY, int fitType,
TFile * outputFile, const TString & resonanceType, const double & xDisplace, const TString & append) {
//Read the TH2 from file
TFile *inputFile = new TFile(path);
TH2 * histo = (TH2*) inputFile->Get(name);
if( rebinX > 0 ) histo->RebinX(rebinX);
if( rebinY > 0 ) histo->RebinY(rebinY);
//Declare some variables
TH1 * histoY;
TString nameY;
std::vector<double> Ftop;
std::vector<double> Fwidth;
std::vector<double> Fmass;
std::vector<double> Etop;
std::vector<double> Ewidth;
std::vector<double> Emass;
std::vector<double> Fchi2;
std::vector<double> Xcenter;
std::vector<double> Ex;
TString fileOutName("fitCompare2"+name);
fileOutName += append;
fileOutName += ".root";
TFile *fileOut=new TFile(fileOutName,"RECREATE");
for (int i=1; i<=(histo->GetXaxis()->GetNbins());i++) {
//Project on Y (set name and title)
std::stringstream number;
number << i;
TString numberString(number.str());
nameY = name + "_" + numberString;
// std::cout << "nameY " << nameY << std::endl;
histoY = histo->ProjectionY(nameY, i, i);
double xBin = histo->GetXaxis()->GetBinCenter(i);
std::stringstream xBinString;
xBinString << xBin;
TString title("Projection of x = ");
title += xBinString.str();
histoY->SetName(title);
if (histoY->GetEntries() > minEntries) {
//Make the dirty work!
TF1 *fit;
std::cout << "fitType = " << fitType << std::endl;
if(fitType == 1) fit = gaussianFit(histoY, resonanceType);
else if(fitType == 2) fit = lorentzianFit(histoY, resonanceType);
else if(fitType == 3) fit = linLorentzianFit(histoY);
else {
std::cout<<"Wrong fit type: 1=gaussian, 2=lorentzian, 3=lorentzian+linear."<<std::endl;
abort();
}
double *par = fit->GetParameters();
double *err = fit->GetParErrors();
// Check the histogram alone
TCanvas *canvas = new TCanvas(nameY+"alone", nameY+" alone");
histoY->Draw();
canvas->Write();
// Only for check
TCanvas *c = new TCanvas(nameY, nameY);
histoY->Draw();
fit->Draw("same");
fileOut->cd();
c->Write();
if( par[0] == par[0] ) {
//Store the fit results
Ftop.push_back(par[0]);
Fwidth.push_back(fabs(par[1]));//sometimes the gaussian has negative width (checked with Rene Brun)
Fmass.push_back(par[2]);
Etop.push_back(err[0]);
Ewidth.push_back(err[1]);
Emass.push_back(err[2]);
Fchi2.push_back(fit->GetChisquare()/fit->GetNDF());
double xx= histo->GetXaxis()->GetBinCenter(i);
Xcenter.push_back(xx);
double ex = 0;
Ex.push_back(ex);
}
else {
// Skip nan
std::cout << "Skipping nan" << std::endl;
Ftop.push_back(0);
Fwidth.push_back(0);
Fmass.push_back(0);
//.........这里部分代码省略.........