本文整理汇总了C++中TF1::SetRange方法的典型用法代码示例。如果您正苦于以下问题：C++ TF1::SetRange方法的具体用法？C++ TF1::SetRange怎么用？C++ TF1::SetRange使用的例子？那么恭喜您, 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::SetRange方法的15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: fullPedestalAnalysis
//.........这里部分代码省略.........
kSProbab_ = 0.; jBProbab_ = 0.;
kSValue_ = 0.; jBValue_ = 0.;
aDValue_= 0.; aDProbab_ = 0.;
nBin_ = 0.; xMin_ = 0.; xMax_ = 0.;
// basic info
detid_ = *detid;
fedKey_ = fedKey;
fecCrate_ = *fecCrate;
fecSlot_ = *fecSlot;
fecRing_ = *fecRing;
ccuAdd_ = *ccuAdd;
ccuChan_ = *ccuChan;
lldChannel_ = *lldChannel;
fedId_ = *fedId;
fedCh_ = *fedCh;
apvId_ = apvID;
stripId_ = stripID;
// basic info of nioise distribution
noiseMean_ = histoNoiseStrip->GetMean();
noiseRMS_ = histoNoiseStrip->GetRMS();
noiseSkewness_ = histoNoiseStrip->GetSkewness();
noiseKurtosis_ = histoNoiseStrip->GetKurtosis();
float integral = histoNoiseStrip->Integral();
noiseIntegral3Sigma_ = (histoNoiseStrip->Integral(histoNoiseStrip->FindBin(noiseMean_+noiseRMS_*3),histoNoiseStrip->GetNbinsX()+1) + histoNoiseStrip->Integral(0,histoNoiseStrip->FindBin(noiseMean_-noiseRMS_*3)))/integral;
noiseIntegral4Sigma_ = (histoNoiseStrip->Integral(histoNoiseStrip->FindBin(noiseMean_+noiseRMS_*4),histoNoiseStrip->GetNbinsX()+1) + histoNoiseStrip->Integral(0,histoNoiseStrip->FindBin(noiseMean_-noiseRMS_*4)))/integral;
noiseIntegral5Sigma_ = (histoNoiseStrip->Integral(histoNoiseStrip->FindBin(noiseMean_+noiseRMS_*5),histoNoiseStrip->GetNbinsX()+1) + histoNoiseStrip->Integral(0,histoNoiseStrip->FindBin(noiseMean_-noiseRMS_*5)))/integral;
// make a gaussian fit
if(fitFunc == NULL or fitFunc == 0){
fitFunc = new TF1 ("fitFunc","gaus(0)",histoNoise->GetXaxis()->GetXmin(),histoNoise->GetXaxis()->GetXmax());
}
fitFunc->SetRange(histoNoise->GetXaxis()->GetXmin(),histoNoise->GetXaxis()->GetXmax());
fitFunc->SetParameters(histoNoiseStrip->Integral(),noiseMean_,noiseRMS_);
result = histoNoiseStrip->Fit(fitFunc,"QSR");
if(result.Get()){
fitStatus_ = result->Status();
fitGausNormalization_ = fitFunc->GetParameter(0);
fitGausMean_ = fitFunc->GetParameter(1);
fitGausSigma_ = fitFunc->GetParameter(2);
fitGausNormalizationError_ = fitFunc->GetParError(0);
fitGausMeanError_ = fitFunc->GetParError(1);
fitGausSigmaError_ = fitFunc->GetParError(2);
fitChi2_ = result->Chi2();
fitChi2Probab_ = result->Prob();
noiseIntegral3SigmaFromFit_ = (histoNoiseStrip->Integral(histoNoiseStrip->FindBin(noiseMean_+fitGausSigma_*3),histoNoiseStrip->GetNbinsX()+1) + histoNoiseStrip->Integral(0,histoNoiseStrip->FindBin(noiseMean_-fitGausSigma_*3)))/histoNoiseStrip->Integral();
noiseIntegral4SigmaFromFit_ = (histoNoiseStrip->Integral(histoNoiseStrip->FindBin(noiseMean_+fitGausSigma_*4),histoNoiseStrip->GetNbinsX()+1) + histoNoiseStrip->Integral(0,histoNoiseStrip->FindBin(noiseMean_-fitGausSigma_*4)))/histoNoiseStrip->Integral();
noiseIntegral5SigmaFromFit_ = (histoNoiseStrip->Integral(histoNoiseStrip->FindBin(noiseMean_+fitGausSigma_*5),histoNoiseStrip->GetNbinsX()+1) + histoNoiseStrip->Integral(0,histoNoiseStrip->FindBin(noiseMean_-fitGausSigma_*5)))/histoNoiseStrip->Integral();
jBValue_ = (histoNoiseStrip->Integral()/6)*(noiseSkewness_*noiseSkewness_+(noiseKurtosis_*noiseKurtosis_)/4);
jBProbab_ = ROOT::Math::chisquared_cdf_c(jBValue_,2);
if(randomHisto == 0 or randomHisto == NULL)
randomHisto = (TH1F*) histoNoiseStrip->Clone("randomHisto");
randomHisto->Reset();
randomHisto->SetDirectory(0);
if(integral != 0){
if(generateRandomDistribution){
randomHisto->FillRandom("fitFunc",histoNoiseStrip->Integral());
kSValue_ = histoNoiseStrip->KolmogorovTest(randomHisto,"MN");
kSProbab_ = histoNoiseStrip->KolmogorovTest(randomHisto,"N"); 示例2: Alignment_1
//-------------------------------------------------------------------
void Alignment_1(int cluster_length_leftCut = 2,int cluster_length_rightCut = 7,float TotSignal_Cut = 5){
gStyle->SetOptStat(11111111);
gStyle->SetOptFit(111111111);
//gAnaCombine->LinkBranches();
ofstream outputlog("./AMS/AMSAlignment_1.txt",ios::out | ios::app);
outputlog<<"\nfile: "<<gRootIOSvc->GetInputFileName()<<".\tCluster length: "<<cluster_length_leftCut<<"~"<<cluster_length_rightCut<<".\tTotal signale cut "<<TotSignal_Cut<<endl;
TH1D *h_ladder_stripID[5][2];
TH1D *h_Refer[5][2];
char name[80];
for(short lid =0;lid<5;++lid){
for(short sid=0;sid<2;++sid){
snprintf(name,80,"ladder_%d-side_%d",lid,sid);
h_ladder_stripID[lid][sid] = new TH1D(name,name,500,0,1100);
snprintf(name,80,"ladder_%d-side_%d VS ladder 0",lid,sid);
h_Refer[lid][sid] = new TH1D(name,name,200,-200,200);
}
snprintf(name,80,"ladder_%d",lid);
h_ladder_stripID[lid][0]->SetTitle(name);
snprintf(name,80,"Seed Address ladder_%d",lid);
h_Refer[lid][0]->SetTitle(name);
}
TChain *tree = gAnaCombine->GetTree();
long nEvt = tree->GetEntries();
std::vector<Cluster*> clusterIndex[5][2];
for(long ievt=0;ievt<nEvt;++ievt){
tree->GetEntry(ievt);
short nCluster = gAnaCombine->fEvtAMS->GetEntriesFast();
for(int iclu=0;iclu<nCluster;++iclu){
Cluster *acluster = (Cluster*)gAnaCombine->fEvtAMS->At(iclu);
if(acluster->GetTotSig()>TotSignal_Cut && cluster_length_leftCut<=acluster->length && acluster->length <= cluster_length_rightCut){
int ladder = acluster->ladder;
if(ladder==5){
ladder = 2;
}else if(ladder == 4){
ladder = 3;
}else if(ladder == 3){
ladder = 4;
}
clusterIndex[ladder][acluster->side].push_back(acluster);
}
}
if(clusterIndex[0][0].size() == 1 && clusterIndex[0][1].size() == 1){
for(short il=0;il<5;++il){
for(short is=0;is<2;++is){
if(clusterIndex[il][is].size() == 1){
h_ladder_stripID[il][is]->Fill(clusterIndex[il][is][0]->GetSeedAdd());
h_Refer[il][is]->Fill(clusterIndex[il][is][0]->GetSeedAdd() - clusterIndex[0][is][0]->GetSeedAdd());
}
clusterIndex[il][is].clear();
}
}
}
}
snprintf(name,80,"AMS Alignment_1_a: cluster length %d~%d, total signal cut %f",cluster_length_leftCut,cluster_length_rightCut,TotSignal_Cut);
TCanvas *c1 = new TCanvas(name,name);
c1->Divide(2,3);
snprintf(name,80,"AMS Alignment_1_b: cluster length %d~%d, totalt signal cut %f",cluster_length_leftCut,cluster_length_rightCut,TotSignal_Cut);
TF1 *gausFit = new TF1("GausFit","gaus",0,150);
TCanvas *c2 = new TCanvas(name,name);
c2->Divide(2,3);
double mean=0.,sigma =0.;
for(short lid=0;lid<5;++lid){
c1->cd(lid+1);
h_ladder_stripID[lid][0]->Draw();
h_ladder_stripID[lid][1]->SetLineColor(6);
h_ladder_stripID[lid][1]->Draw("same");
c2->cd(lid+1);
h_Refer[lid][0]->Draw();
mean = h_Refer[lid][0]->GetMean(); sigma = h_Refer[lid][0]->GetRMS();
gausFit->SetRange(mean-2.5*sigma,mean+2.5*sigma);
h_Refer[lid][0]->Fit(gausFit,"R0Q");
gausFit->DrawCopy("lsame");
outputlog<<lid<<" "<<gausFit->GetParameter(1)<<" "<<gausFit->GetParameter(2)<<" ";
h_Refer[lid][1]->SetLineColor(6);
h_Refer[lid][1]->Draw("same");
mean = h_Refer[lid][1]->GetMean(); sigma = h_Refer[lid][1]->GetRMS();
gausFit->SetRange(mean-2.5*sigma,mean+2.5*sigma);
h_Refer[lid][1]->Fit(gausFit,"R0Q");
gausFit->DrawCopy("lsame");
outputlog<<gausFit->GetParameter(1)<<" "<<gausFit->GetParameter(2)<<endl;
}
}示例3: TCanvas
TF1 *fit(TTree *nt,TTree *ntMC,double ptmin,double ptmax, bool ispPb, int count){
//cout<<cut.Data()<<endl;
//static int count=0;
//count++;
TCanvas *c= new TCanvas(Form("c%d",count),"",600,600);
TH1D *h = new TH1D(Form("h%d",count),"",50,5,6);
TH1D *hMC = new TH1D(Form("hMC%d",count),"",50,5,6);
TString iNP="7.26667e+00*Gaus(x,5.10472e+00,2.63158e-02)/(sqrt(2*3.14159)*2.63158e-02)+4.99089e+01*Gaus(x,4.96473e+00,9.56645e-02)/(sqrt(2*3.14159)*9.56645e-02)+3.94417e-01*(3.74282e+01*Gaus(x,5.34796e+00,3.11510e-02)+1.14713e+01*Gaus(x,5.42190e+00,1.00544e-01))";
TF1 *f = new TF1(Form("f%d",count),"[0]*([7]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2])+(1-[7])*Gaus(x,[1],[8])/(sqrt(2*3.14159)*[8]))+[3]+[4]*x+[5]*("+iNP+")");
nt->Project(Form("h%d",count),"mass",Form("%s&&pt>%f&&pt<%f",seldata_2y.Data(),ptmin,ptmax));
ntMC->Project(Form("hMC%d",count),"mass",Form("%s&&pt>%f&&pt<%f",seldata_2y.Data(),ptmin,ptmax));
clean0(h);
TH1D *hraw = new TH1D(Form("hraw%d",count),"",50,5,6);
clean0(hraw);
hraw = (TH1D*)h->Clone(Form("hraw%d",count));
h->Draw();
f->SetParLimits(4,-1000,0);
f->SetParLimits(2,0.01,0.05);
f->SetParLimits(8,0.01,0.05);
f->SetParLimits(7,0,1);
f->SetParLimits(5,0,1000);
f->SetParameter(0,setparam0);
f->SetParameter(1,setparam1);
f->SetParameter(2,setparam2);
f->SetParameter(8,setparam3);
f->FixParameter(1,fixparam1);
h->GetEntries();
hMC->Fit(Form("f%d",count),"q","",5,6);
hMC->Fit(Form("f%d",count),"q","",5,6);
f->ReleaseParameter(1);
hMC->Fit(Form("f%d",count),"L q","",5,6);
hMC->Fit(Form("f%d",count),"L q","",5,6);
hMC->Fit(Form("f%d",count),"L q","",5,6);
hMC->Fit(Form("f%d",count),"L m","",5,6);
f->FixParameter(1,f->GetParameter(1));
f->FixParameter(2,f->GetParameter(2));
f->FixParameter(7,f->GetParameter(7));
f->FixParameter(8,f->GetParameter(8));
h->Fit(Form("f%d",count),"q","",5,6);
h->Fit(Form("f%d",count),"q","",5,6);
f->ReleaseParameter(1);
h->Fit(Form("f%d",count),"L q","",5,6);
h->Fit(Form("f%d",count),"L q","",5,6);
h->Fit(Form("f%d",count),"L q","",5,6);
h->Fit(Form("f%d",count),"L m","",5,6);
h->SetMarkerSize(0.8);
h->SetMarkerStyle(20);
cout <<h->GetEntries()<<endl;
// function for background shape plotting. take the fit result from f
TF1 *background = new TF1(Form("background%d",count),"[0]+[1]*x");
background->SetParameter(0,f->GetParameter(3));
background->SetParameter(1,f->GetParameter(4));
background->SetParameter(2,f->GetParameter(5));
background->SetParameter(3,f->GetParameter(6));
background->SetLineColor(4);
background->SetRange(5,6);
background->SetLineStyle(2);
// function for signal shape plotting. take the fit result from f
TF1 *Bkpi = new TF1(Form("fBkpi%d",count),"[0]*("+iNP+")");
Bkpi->SetParameter(0,f->GetParameter(5));
Bkpi->SetLineColor(kGreen+1);
Bkpi->SetFillColor(kGreen+1);
// Bkpi->SetRange(5.00,5.28);
Bkpi->SetRange(5.00,6.00);
Bkpi->SetLineStyle(1);
Bkpi->SetFillStyle(3004);
// function for signal shape plotting. take the fit result from f
TF1 *mass = new TF1(Form("fmass%d",count),"[0]*([3]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2])+(1-[3])*Gaus(x,[1],[4])/(sqrt(2*3.14159)*[4]))");
mass->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(2),f->GetParameter(7),f->GetParameter(8));
mass->SetParError(0,f->GetParError(0));
mass->SetParError(1,f->GetParError(1));
mass->SetParError(2,f->GetParError(2));
mass->SetParError(7,f->GetParError(7));
mass->SetParError(8,f->GetParError(8));
mass->SetLineColor(2);
mass->SetLineStyle(2);
// cout <<mass->Integral(0,1.2)<<" "<<mass->IntegralError(0,1.2)<<endl;
h->SetMarkerStyle(24);
h->SetStats(0);
h->Draw("e");
h->SetXTitle("M_{B} (GeV/c^{2})");
h->SetYTitle("Entries / (20 MeV/c^{2})");
h->GetXaxis()->CenterTitle();
h->GetYaxis()->CenterTitle();
h->SetTitleOffset(1.5,"Y");
h->SetAxisRange(0,h->GetMaximum()*1.2,"Y");
Bkpi->Draw("same");
background->Draw("same");
//.........这里部分代码省略.........
示例4: compareUpgrade
//.........这里部分代码省略.........
f->ReleaseParameter(6);
f->SetLineColor(kRed);
/*
TCanvas*mycanvas=new TCanvas("mycanvas","mycanvas",1000,500);
mycanvas->Divide(2,1);
mycanvas->cd(1);
hMCSignal->Draw();
mycanvas->cd(2);
hMCSwapped->Draw();
mycanvas->SaveAs("mycanvas.pdf");
*/
h->Fit(Form("f%d",count),"q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"q","",minhisto,maxhisto);
f->ReleaseParameter(1);
//f->ReleaseParameter(2); // you need to release these two parameters if you want to perform studies on the sigma shape
//f->ReleaseParameter(10); // you need to release these two parameters if you want to perform studies on the sigma shape
h->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"L m","",minhisto,maxhisto);
std::cout<<"parameter 10="<<f->GetParameter(10)<<std::endl;
TF1* background = new TF1(Form("background%d",count),"[0]+[1]*x+[2]*x*x+[3]*x*x*x");
background->SetParameter(0,f->GetParameter(3));
background->SetParameter(1,f->GetParameter(4));
background->SetParameter(2,f->GetParameter(5));
background->SetParameter(3,f->GetParameter(6));
background->SetLineColor(4);
background->SetRange(minhisto,maxhisto);
background->SetLineStyle(2);
TF1* mass = new TF1(Form("fmass%d",count),"[0]*([3]*([4]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2])+(1-[4])*Gaus(x,[1],[5])/(sqrt(2*3.14159)*[5])))");
mass->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(2),f->GetParameter(7),f->GetParameter(9),f->GetParameter(10));
mass->SetParError(0,f->GetParError(0));
mass->SetParError(1,f->GetParError(1));
mass->SetParError(2,f->GetParError(2));
mass->SetParError(3,f->GetParError(7));
mass->SetParError(4,f->GetParError(9));
mass->SetParError(5,f->GetParError(10));
mass->SetFillColor(kOrange-3);
mass->SetFillStyle(3002);
mass->SetLineColor(kOrange-3);
mass->SetLineWidth(3);
mass->SetLineStyle(2);
TF1* massSwap = new TF1(Form("fmassSwap%d",count),"[0]*(1-[2])*Gaus(x,[1],[3])/(sqrt(2*3.14159)*[3])");
massSwap->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(7),f->GetParameter(8));
massSwap->SetParError(0,f->GetParError(0));
massSwap->SetParError(1,f->GetParError(1));
massSwap->SetParError(2,f->GetParError(7));
massSwap->SetParError(3,f->GetParError(8));
massSwap->SetFillColor(kGreen+4);
massSwap->SetFillStyle(3005);
massSwap->SetLineColor(kGreen+4);
massSwap->SetLineWidth(3);
massSwap->SetLineStyle(1);
h->SetXTitle("m_{#piK} (GeV/c^{2})");
h->SetYTitle("Entries / (5 MeV/c^{2})");
h->GetXaxis()->CenterTitle();
h->GetYaxis()->CenterTitle();示例5: getYield
TH1D* getYield(TTree* nt, TTree* ntMC, TString triggerpass, TString triggername, TString prescale, TString variable, TString varname, TString varlatex, Int_t BIN_NUM, Double_t BIN_MIN, Double_t BIN_MAX, TString addcut="")
{
TH1D* hDistrib = new TH1D(Form("h%s_Distrib_%s",triggername.Data(),varname.Data()),"",BIN_NUM,BIN_MIN,BIN_MAX);
for(float ivar=0;ivar<BIN_NUM;ivar++)
{
TCanvas* c = new TCanvas(Form("c%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"",500,500);
TH1D* h = new TH1D(Form("h%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),";D^{0} mass (GeV/c^{2});Candidates",60,1.7,2.0);
TH1D* hMC = new TH1D(Form("hMC%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"",60,1.75,1.95);
TH1D* hSW = new TH1D(Form("hSW%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"",60,1.75,1.95);
Float_t varmin = BIN_MIN+ivar*((BIN_MAX-BIN_MIN)/BIN_NUM);
Float_t varmax = BIN_MIN+(ivar+1)*((BIN_MAX-BIN_MIN)/BIN_NUM);
nt->Project(Form("h%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),Form("Dmass%s",prescale.Data()),Form("%s%s&&(%s>%f&&%s<%f)%s",prefilter.Data(),addcut.Data(),variable.Data(),varmin,variable.Data(),varmax,triggerpass.Data()));
ntMC->Project(Form("hMC%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"Dmass",Form("%s%s&&(%s>%f&&%s<%f)%s",prefilterMC.Data(),addcut.Data(),variable.Data(),varmin,variable.Data(),varmax,"&&1"));
ntMC->Project(Form("hSW%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"Dmass",Form("%s%s&&(%s>%f&&%s<%f)%s",prefilterSW.Data(),addcut.Data(),variable.Data(),varmin,variable.Data(),varmax,"&&1"));
h->SetMaximum(h->GetMaximum()*1.20);
h->Draw();
TF1* f = new TF1(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"[0]*([7]*([9]*Gaus(x,[1],[2]*(1+[11]))/(sqrt(2*3.14159)*[2]*(1+[11]))+(1-[9])*Gaus(x,[1],[10]*(1+[11]))/(sqrt(2*3.14159)*[10]*(1+[11])))+(1-[7])*Gaus(x,[1],[8]*(1+[11]))/(sqrt(2*3.14159)*[8]*(1+[11])))+[3]+[4]*x+[5]*x*x+[6]*x*x*x", 1.7, 2.0);
f->SetParLimits(4,-1000,1000);
f->SetParLimits(10,0.001,0.05);
f->SetParLimits(2,0.01,0.1);
f->SetParLimits(8,0.02,0.2);
f->SetParLimits(7,0,1);
f->SetParLimits(9,0,1);
f->SetParameter(0,setparam0);
f->SetParameter(1,setparam1);
f->SetParameter(2,setparam2);
f->SetParameter(10,setparam10);
f->SetParameter(9,setparam9);
f->FixParameter(8,setparam8);
f->FixParameter(7,1);
f->FixParameter(1,fixparam1);
f->FixParameter(3,0);
f->FixParameter(4,0);
f->FixParameter(5,0);
f->FixParameter(6,0);
f->FixParameter(11,0);
h->GetEntries();
hMC->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"q","",1.7,2.0);
hMC->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"q","",1.7,2.0);
f->ReleaseParameter(1);
hMC->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L q","",1.7,2.0);
hMC->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L q","",1.7,2.0);
hMC->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L m","",1.7,2.0);
f->FixParameter(1,f->GetParameter(1));
f->FixParameter(2,f->GetParameter(2));
f->FixParameter(10,f->GetParameter(10));
f->FixParameter(9,f->GetParameter(9));
f->FixParameter(7,0);
f->ReleaseParameter(8);
f->SetParameter(8,setparam8);
hSW->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L q","",1.7,2.0);
hSW->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L q","",1.7,2.0);
hSW->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L q","",1.7,2.0);
hSW->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L m","",1.7,2.0);
f->FixParameter(7,hMC->Integral(0,1000)/(hSW->Integral(0,1000)+hMC->Integral(0,1000)));
f->FixParameter(8,f->GetParameter(8));
f->ReleaseParameter(3);
f->ReleaseParameter(4);
f->ReleaseParameter(5);
f->ReleaseParameter(6);
f->SetLineColor(kRed);
h->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"q","",1.7,2.0);
h->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"q","",1.7,2.0);
f->ReleaseParameter(1);
f->SetParLimits(1,1.86,1.87);
f->ReleaseParameter(11);
f->SetParLimits(11,-1.,1.);
h->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L q","",1.7,2.0);
h->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L q","",1.7,2.0);
h->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L q","",1.7,2.0);
h->Fit(Form("f%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"L m","",1.7,2.0);
h->SetMarkerSize(0.8);
h->SetMarkerStyle(20);
TF1* background = new TF1(Form("background%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"[0]+[1]*x+[2]*x*x+[3]*x*x*x");
background->SetParameter(0,f->GetParameter(3));
background->SetParameter(1,f->GetParameter(4));
background->SetParameter(2,f->GetParameter(5));
background->SetParameter(3,f->GetParameter(6));
background->SetLineColor(4);
background->SetRange(1.7,2.0);
background->SetLineStyle(2);
TF1* mass = new TF1(Form("fmass%s_Fit_%s_%.0f",triggername.Data(),varname.Data(),ivar),"[0]*([3]*([4]*Gaus(x,[1],[2]*(1+[6]))/(sqrt(2*3.14159)*[2]*(1+[6]))+(1-[4])*Gaus(x,[1],[5]*(1+[6]))/(sqrt(2*3.14159)*[5]*(1+[6]))))");
mass->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(2),f->GetParameter(7),f->GetParameter(9),f->GetParameter(10),f->GetParameter(11));
mass->SetParError(0,f->GetParError(0));
mass->SetParError(1,f->GetParError(1));
mass->SetParError(2,f->GetParError(2));
mass->SetParError(3,f->GetParError(7));
mass->SetParError(4,f->GetParError(9));
mass->SetParError(5,f->GetParError(10));
//.........这里部分代码省略.........
示例6: bToDRawYield
//.........这里部分代码省略.........
Float_t binsY[nBinY+1] = {-0.0734,-0.0562,-0.0428,-0.0320,-0.0236,-0.0170,-0.0118,-0.0078,-0.0046,-0.002,0.0,0.002,0.0046,0.0078,0.0118,0.0170,0.0236,0.0320,0.0428,0.0562,0.0734};
for(int i=1; i<=nPtBins; i++)
{
pts[i-1] = 0.5*(ptBins[i-1]+ptBins[i]);
ptErrors[i-1] = 0.5*(ptBins[i]-ptBins[i-1]);
float ptLow = ptBins[i-1];
float ptHigh = ptBins[i];
cout<<endl<<"======================================="<<endl;
cout<<"pT range: "<<ptLow<<" "<<ptHigh<<endl;
TLatex* texPtY = new TLatex(0.32,0.82,Form("%.1f < p_{T} < %.1f GeV/c |y| < 1.0",ptLow,ptHigh));
texPtY->SetNDC();
texPtY->SetTextFont(42);
texPtY->SetTextSize(0.06);
texPtY->SetLineWidth(2);
TLatex* texPt = new TLatex(0.18,0.82,Form("%.1f < p_{T} < %.1f GeV/c",ptLow,ptHigh));
texPt->SetNDC();
texPt->SetTextFont(42);
texPt->SetTextSize(0.06);
texPt->SetLineWidth(2);
TLatex* texY = new TLatex(0.18,0.74,Form("|y| < 1.0"));
texY->SetNDC();
texY->SetTextFont(42);
texY->SetTextSize(0.06);
texY->SetLineWidth(2);
c2->cd(1);
hPtMD0Dca->GetZaxis()->SetRange(1,100);
hPtMD0Dca->GetXaxis()->SetRangeUser(ptLow+0.001,ptHigh-0.001);
hPtMD0DcaMCPSignal->GetXaxis()->SetRangeUser(ptLow+0.001,ptHigh-0.001);
hPtMD0DcaMCPSwapped->GetXaxis()->SetRangeUser(ptLow+0.001,ptHigh-0.001);
TH1D* hMData = (TH1D*)hPtMD0Dca->Project3D("y")->Clone(Form("hM_%1.1f_%1.1f", ptLow, ptHigh));
TH1D* hMMCSignal = (TH1D*)hPtMD0DcaMCPSignal->Project3D("y");
TH1D* hMMCSwapped = (TH1D*)hPtMD0DcaMCPSwapped->Project3D("y");
setColorTitleLabel(hMData);
setColorTitleLabel(hMMCSignal);
setColorTitleLabel(hMMCSwapped);
TF1* fMass = fitMass(hMData, hMMCSignal, hMMCSwapped);
texCms->Draw();
texCol->Draw();
texPt->Draw();
texY->Draw();
TF1* fSignalAndSwapped = new TF1("fSignalAndSwapped","[0]*([3]*([5]*Gaus(x,[1],[2]*(1+[7]))/(sqrt(2*3.1415927)*[2]*(1+[7]))+(1-[5])*Gaus(x,[1],[6]*(1+[7]))/(sqrt(2*3.1415927)*[6]*(1+[7])))+(1-[3])*Gaus(x,[1],[4]*(1+[7]))/(sqrt(2*3.1415927)*[4]*(1+[7])))", 1.7, 2.0);
fSignalAndSwapped->SetParameter(0,fMass->GetParameter(0));
fSignalAndSwapped->SetParameter(1,fMass->GetParameter(1));
fSignalAndSwapped->SetParameter(2,fMass->GetParameter(2));
fSignalAndSwapped->SetParameter(3,fMass->GetParameter(7));
fSignalAndSwapped->SetParameter(4,fMass->GetParameter(8));
fSignalAndSwapped->SetParameter(5,fMass->GetParameter(9));
fSignalAndSwapped->SetParameter(6,fMass->GetParameter(10));
fSignalAndSwapped->SetParameter(7,fMass->GetParameter(11));
TF1* background = new TF1("fBackground","[0]+[1]*x+[2]*x*x+[3]*x*x*x");
background->SetParameter(0,fMass->GetParameter(3));
background->SetParameter(1,fMass->GetParameter(4));
background->SetParameter(2,fMass->GetParameter(5));示例7: TCanvas
TF1 *fit(TTree *nt, TTree *ntMC, Double_t ptmin, Double_t ptmax, int isMC,bool isPbPb,TF1* &total,Float_t centmin, Float_t centmax)
{
//cout<<cut.Data()<<endl;
static Int_t count=0;
count++;
TCanvas* c= new TCanvas(Form("c%d",count),"",600,600);
TH1D* h = new TH1D(Form("h%d",count),"",nbinsmasshisto,minhisto,maxhisto);
// TF1* f = new TF1(Form("f%d",count),"[0]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2]) + [3]*Gaus(x,[4],[5])/(sqrt(2*3.14159)*[5]) + [6]*Gaus(x,[7],[8])/(sqrt(2*3.14159)*[8]) + [9]+[10]*x ");
// TF1* f = new TF1(Form("f%d",count),"[0]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2]) + [3]*Gaus(x,[4],[5])/(sqrt(2*3.14159)*[5]) + [9]+[10]*x ");
TF1* f = new TF1(Form("f%d",count),"[0]*TMath::Erf((x-[1])/[2]) + [0] + [9]+[10]*x ");
if(isMC==1) nt->Project(Form("h%d",count),"Bmass",Form("%s*(%s&&Bpt>%f&&Bpt<%f)","1",seldata.Data(),ptmin,ptmax));
else nt->Project(Form("h%d",count),"Bmass",Form("(%s&&Bpt>%f&&Bpt<%f)",seldata.Data(),ptmin,ptmax));
clean0(h);
h->Draw();
f->SetParLimits(0, 1e-2, 1e4);
f->SetParLimits(1, 5.02, 5.06);
f->SetParLimits(2, 0.001, 0.1);
f->SetParLimits(3, 1e-2, 1e4);
f->SetParLimits(4, 5.06, 5.10);
f->SetParLimits(5, 0.001, 0.1);
f->SetParLimits(6, 0, 1e4);
f->SetParLimits(7, 5.3, 5.4);
f->SetParLimits(8, 0.001, 0.5);
f->SetParLimits(9, 0, 1e5);
f->SetParLimits(10, -500, 100);
f->SetParameter(0,1e2);
f->SetParameter(1,5.03);
f->SetParameter(2,0.05);
f->SetParameter(0,1e2);
f->SetParameter(1,5.03);
f->SetParameter(2,0.05);
f->SetParameter(3,1e2);
f->SetParameter(4,5.07);
f->SetParameter(5,0.05);
f->SetParameter(6,1e2);
f->SetParameter(7,5.35);
f->SetParameter(8,0.05);
f->SetParameter(9,1e3);
f->SetParameter(10,-1);
//error fn
f->SetParLimits(0, 1e1, 1e3);
f->SetParLimits(1, 5., 5.3);
f->SetParLimits(2, -10, 0);
f->SetParameter(0,100);
f->SetParameter(1,5.1);
f->SetParameter(2,0);
h->GetEntries();
h->Fit(Form("f%d",count),"q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"L m","",minhisto,maxhisto);
h->SetMarkerSize(0.8);
h->SetMarkerStyle(20);
TF1 *background = new TF1(Form("background%d",count),"[0]+[1]*x");
background->SetParameter(0,f->GetParameter(9));
background->SetParameter(1,f->GetParameter(10));
background->SetLineColor(4);
background->SetRange(minhisto,maxhisto);
background->SetLineStyle(2);
// TF1 *mass = new TF1(Form("fmass%d",count),"[0]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2]) + [3]*Gaus(x,[4],[5])/(sqrt(2*3.14159)*[5]) + [6]*Gaus(x,[7],[8])/(sqrt(2*3.14159)*[8])");
// mass->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(2),f->GetParameter(3),f->GetParameter(4),f->GetParameter(5),f->GetParameter(6),f->GetParameter(7),f->GetParameter(8));
//TF1 *mass = new TF1(Form("fmass%d",count),"[0]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2]) + [3]*Gaus(x,[4],[5])/(sqrt(2*3.14159)*[5])");
//mass->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(2),f->GetParameter(3),f->GetParameter(4),f->GetParameter(5));
TF1 *mass = new TF1(Form("fmass%d",count),"[0]*TMath::Erf((x-[1])/[2]) + [0]");
mass->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(2));
//mass->SetParError(0,f->GetParError(0));
//mass->SetParError(1,f->GetParError(1));
//mass->SetParError(2,f->GetParError(2));
mass->SetLineColor(2);
h->SetXTitle("m_{#mu#muK} (GeV/c^{2})");
h->SetYTitle("Entries / (5 MeV/c^{2})");
h->GetXaxis()->CenterTitle();
h->GetYaxis()->CenterTitle();
h->SetAxisRange(0,h->GetMaximum()*1.4*1.2,"Y");
h->GetXaxis()->SetTitleOffset(1.3);
h->GetYaxis()->SetTitleOffset(1.8);
h->GetXaxis()->SetLabelOffset(0.007);
h->GetYaxis()->SetLabelOffset(0.007);
h->GetXaxis()->SetTitleSize(0.045);
h->GetYaxis()->SetTitleSize(0.045);
//.........这里部分代码省略.........
示例8: FitProfiles
void ClusterWidthAnalysisTreeMaker::FitProfiles(std::map<ULong64_t , std::vector<TProfile*> > &ProfVsAngle, string output_file){
TFile * myFile = new TFile(output_file.c_str(), "recreate");
ULong64_t detid;
double voltage;
double errvoltage;
double Slope;
double errSlope;
double Origin;
double errOrigin;
double Chi2;
int index;
TTree *tree = new TTree("T", "summary information");
tree->Branch("DetID",&detid, "DetID/l");
tree->Branch("Voltage",&voltage,"Voltage/D");
tree->Branch("Index",&index,"Index/I");
tree->Branch("errVoltage",&errvoltage,"errVoltage/D");
tree->Branch("Slope",&Slope,"Slope/D");
tree->Branch("errSlope",&errSlope,"errSlope/D");
tree->Branch("Origin",&Origin,"Origin/D");
tree->Branch("errOrigin",&errOrigin,"errOrigin/D");
tree->Branch("Chi2",&Chi2,"Chi2/D");
//TCanvas* c1 = new TCanvas();
TH1F* hChi2 = new TH1F("hChi2", "hChi2", 100, 0, 100);
unsigned int nfitrm=0;
for(std::map<ULong64_t , std::vector<TProfile*> >::iterator iter = ProfVsAngle.begin(); iter != ProfVsAngle.end(); ++iter){
unsigned int i=0; // voltage index
std::set< int >::iterator itVolt;
std::set< int > Voltage = VSmaker.getVoltageList();
for( itVolt=Voltage.begin(); itVolt!=Voltage.end(); itVolt++){
//std::cout<<"going through the measurement: " << i << std::endl;
TString thestring;
thestring.Form("DetID_%llu_prof_%u",iter->first,i);
if(i>=iter->second.size())
{ std::cout<<" Wrong number of voltage steps. "<<std::endl; i++; continue;}
TProfile* Prof = iter->second[i];
if(!Prof)
{ std::cout<<" Profile "<<thestring.Data()<<"_"<<i<<" not found."<<std::endl; i++; continue;}
//if(Histo->GetEntries()) hNhits->Fill(Histo->Integral());
/*if(Histo->Integral()<20) //0.1
{ //std::cout<<" Not enought entries for histo "<<thestring.Data()<<std::endl;
i++; continue;}*/
detid = iter->first;
bool rmfit=false;
TF1* pol = new TF1("pol", "pol1", -3, 3);
pol->SetRange(-1,0);
Prof->Fit("pol", "qr");
double chi2 = pol->GetChisquare()/pol->GetNDF();
hChi2->Fill(chi2);
if(chi2>10) rmfit=true;
if( rmfit ||
// TIB modules
// TIB - 1.4.2.5
detid==369121605 || detid==369121606 || detid==369121614 ||
detid==369121613 || detid==369121610 || detid==369121609 ||
// TIB - 1.2.2.1
detid==369121390 || detid==369121382 || detid==369121386 ||
detid==369121385 || detid==369121389 || detid==369121381 ||
// others in TIB
detid==369121437 || detid==369142077 || detid==369121722 ||
detid==369125534 || detid==369137018 || detid==369121689 ||
detid==369121765 || detid==369137045 || detid==369169740 ||
detid==369121689 ||
// TOB modules
// TOB + 4.3.3.8
detid/10==436281512 || detid/10==436281528 || detid/10==436281508 ||
detid/10==436281524 || detid/10==436281520 || detid/10==436281516 ||
// others in TOB
detid/10==436228249 || detid/10==436232694 || detid/10==436228805 ||
detid/10==436244722 || detid/10==436245110 || detid/10==436249546 ||
detid/10==436310808 || detid/10==436312136 || detid/10==436315600 ||
// without 'sensors' option
detid==436281512 || detid==436281528 || detid==436281508 ||
detid==436281524 || detid==436281520 || detid==436281516 ||
detid==436228249 || detid==436232694 || detid==436228805 ||
detid==436244722 || detid==436245110 || detid==436249546 ||
detid==436310808 || detid==436312136 || detid==436315600 ||
// TID modules
detid==402664070 || detid==402664110 ||
// TEC modules in small scans
detid==470148196 || detid==470148200 || detid==470148204 ||
//.........这里部分代码省略.........
示例9: nudgeVpd
void nudgeVpd( string vpdParams, string qaFile, double fitLow = -10.0, double fitHigh = 10.0 ) {
Reporter rp( "VpdNudge.pdf" );
rp.newPage();
ifstream infile;
infile.open( vpdParams.c_str() );
ofstream outfile;
outfile.open( "vpd_4DB.nudged.dat" );
TFile * qa = new TFile( qaFile.c_str() );
TH1D * dz = (TH1D*) qa->Get( "zvertexDelta" );
dz->GetXaxis()->SetRangeUser( fitLow * 1.5, fitHigh * 1.5 );
TF1 *g = new TF1( "gaus", "gaus" );
g->SetRange( fitLow, fitHigh );
dz->Draw();
gPad->SetLogy(1);
dz->Fit( g, "R" );
rp.savePage();
double mean = g->GetParameter( 1 );
cout << "Adjust mean by " << -mean << " [cm]" << endl;
const Float_t c_light = 29.9792458;
double dt = 2 * (mean) / c_light;
cout << "dt = " << dt << " [ns]" << endl;
/**
* Read in and write out new
*/
for ( int i = 0; i < 38; i++ ) {
int channel = -1, nBins = -1;
infile >> channel;
infile >> nBins;
outfile << channel << endl;
outfile << nBins << endl;
//copy the bin edges
for ( int iBin = 0; iBin <= nBins; iBin ++ ) {
double bv = -1;
infile >> bv;
outfile << bv << " ";
}
outfile << endl;
// copy the corrections
for ( int iBin = 0; iBin <= nBins; iBin ++ ) {
double bv = -1;
infile >> bv;
if ( channel < 20 ) // only apply correction to one side
outfile << (bv + dt) << " ";
else
outfile << bv << " ";
}
outfile << endl;
} // loop on channels
infile.close();
outfile.close();
delete qa;
delete g;
}示例10: PlotPhCal
void PlotPhCal(const char *filename = "phCalibration_C0.dat", int col, int row)
{
Init();
int value, a, b, n;
double x[10], y[10];
char string[200];
double aovergain, gain, par1;
TF1 *pol2Fit = new TF1("pol2Fit", "pol2");
pol2Fit->SetRange(50,500);
TF1 *linFit = new TF1("linFit", "pol1");
linFit->SetRange(150,600);
TF1 *ursFit = new TF1("ursFit", Fitfcn, 40., 1500., 4);
ursFit->SetParameter(0,0.00382);
ursFit->SetParameter(1,0.886);
ursFit->SetParameter(2,112.7);
ursFit->SetParameter(3,113.0);
TGraphErrors *graph = new TGraphErrors();
TGraph *gSlope = new TGraph();
FILE *inputFile = fopen(filename, "r");
for (int i = 0; i < 4; i++) fgets(string, 200, inputFile);
for (int icol = 0; icol < 52; ++icol)
{
for (int irow = 0; irow < 80; ++irow)
{
n = 0;
for (int point = 0; point < 10; point++)
{
fscanf(inputFile, "%s", string);
if (strcmp(string, "N/A") == 0) value = 7777;
else
{
value = atoi(string);
}
if ((icol == col) && (irow == row))
{
if (point == 0) x[n] = 50;
else if (point == 1) x[n] = 100;
else if (point == 2) x[n] = 150;
else if (point == 3) x[n] = 200;
else if (point == 4) x[n] = 250;
else if (point == 5) x[n] = 210;
else if (point == 6) x[n] = 350;
else if (point == 7) x[n] = 490;
else if (point == 8) x[n] = 560;
else if (point == 9) x[n] = 1400;
if (value != 7777)
{
// y[n] = value; // in testboard adc range
y[n] = (value + 400) / 7; // in 8 bit experiment adc range
graph->SetPoint(n, x[n], y[n]);
// graph->SetPointError(n, 2, 10); // in testboard adc range
graph->SetPointError(n, 2, 10/6); // in 8 bit experiment adc range
n++;
}
}
}
fscanf(inputFile, "%s %2i %2i", string, &a, &b); //comment
}
}
graph->GetXaxis()->SetTitle("Vcal [low range DAC units]");
graph->GetYaxis()->SetTitle("PH [ADC units]");
graph->GetYaxis()->SetTitleOffset(1.2);
graph->GetXaxis()->SetTitleSize(0.055);
graph->GetYaxis()->SetTitleSize(0.055);
graph->GetXaxis()->SetLabelSize(0.04);
graph->GetYaxis()->SetLabelSize(0.05);
graph->GetXaxis()->SetTitleOffset(1.15);
graph->GetYaxis()->SetTitleOffset(1.2);
graph->SetTitle("");
graph->SetLineStyle(1);
graph->SetLineWidth(2);
// graph->Fit("linFit","R");
// gain = linFit->GetParameter(1);
graph->Fit("ursFit","R");
graph->Draw("A*");
par1 = ursFit->GetParameter(1);
NewLatex()->DrawLatex(0.55, 0.5, Form("p_{1} = %.1f ", par1));
// NewLatex()->DrawLatex(0.45, 0.4, "NON-LINEAR pixel"); // PlotPhCal("/home/l_tester/ptr/moduleDB/M0567-070115.08:23/T-10a/phCalibration_C12.dat",7,23)
NewLatex()->DrawLatex(0.5, 0.4, "LINEAR pixel"); // PlotPhCal("/home/l_tester/ptr/moduleDB/M0493-061206.10:45/T-10a/phCalibration_C1.dat",7,23)
}示例11: drawAvsB
//.........这里部分代码省略.........
}
else if ((samples[is]=="zmmjet" || samples[is]=="zeejet") &&
methods[im]=="ptchs" && nozjptb) {
tex->SetTextColor(kRed);
tex->DrawLatex(0.20,0.63,"Z+jet p_{T}^{bal} excl. from fit");
tex->SetTextColor(kBlack);
}
else if (samples[is]=="multijet") {
g->SetMarkerColor(kGray+1);
g->SetLineColor(kGray+1);
if (methods[im]=="ptchs") gmjb = g;
if (methods[im]=="mpfchs1") gmpf = g;
}
else
mg->Add(g);
} // for is
} // for im
if (nogjmpf) s += "_nogjmpf";
if (nogjptb) s += "_nogptb";
if (nozjptb) s += "_nozptb";
if (mjvsjes) {
s += "_mjvsjes";
tex->SetTextColor(kBlack);
tex->DrawLatex(0.20,0.58,"Multijet vs JES fit");
}
TF1 *fjes = new TF1("fjes",jesFit,30,2200,2);
fjes->SetParameters(0.99,0.05);
mg->Fit(fjes,"RN");
fjes->SetLineColor(kBlack);
fjes->SetLineStyle(kDashed);
fjes->SetLineWidth(2);
fjes->SetRange(10.,3500.);
fjes->Draw("SAME");
//TF1 *ft = new TF1("ft","1-[0]-[1]*pow(x,[2]) + ([3]+[4]*log(x))/x",30,2200);
//ft->SetParameters(0,0.05,-0.5,1,0.1);
//ft->FixParameter(3,0);
// Logarithmic sigmoid
//TF1 *ft = new TF1("ft","[0]+(1-[0])/(1. + exp(-(log(x)-log(abs([1])))"
// "/(log(abs([2])+abs([1]))-log(abs([1])))))", 30,2200);
//ft->SetParameters(0.98, 150, 50);
TF1 *ft = new TF1("ft","[0]+(1-[0])/(1. + exp(-(log(x)-[1])/[2]))",30,2200);
//ft->SetParameters(0.98,log(145),log(190)-log(145));
//ft->SetParameters(0.982,4.967,0.271);
//ft->SetParameters(0.976,5.040,0.370); // ENDCAP
//ft->SetParameters(0.985,5.0,0.3);
ft->SetParameters(0.985,5.025,0.3);
//ft->FixParameter(1,5.03); // semi-weighted average of BCD and EF
//ft->FixParameter(2,0.395); // combined fit to BCD+EF / G+H
// ( 12.9*5.055+6.8*5.000)/(12.9+6.8)
ft->FixParameter(1,5.036); // semi-weighted average of BCD/GH and EF/GH
// ( 12.9*0.344 + 6.8*0.455)/(12.9+6.8)
ft->FixParameter(2,0.391); // combined fit to BCD+EF / GH
// Log-sigmoid + powerlaw
//TF1 *ft = new TF1("ft","[0]+(1-[0])/(1. + exp(-(log(x)-[1])/[2]))"
// "*(1-[3]*pow(x,[4]))",30,2200);
//ft->SetParameters(0.982,4.967,0.271,0.1,-0.2);
// Double powerlaw
//TF1 *ft = new TF1("ft","[4]-[0]*pow(x,[1])-[2]*pow(x,[3])",30,2200);
//ft->SetParameters(0.05,-0.15,0.01,-0.3,1);
示例12: TCanvas
TF1 *fit(TTree *nt, TTree *ntMC, double ptmin,double ptmax)
{
//cout<<cut.Data()<<endl;
static int count=0;
count++;
TCanvas *c= new TCanvas(Form("c%d",count),"",600,600);
TH1D *h = new TH1D(Form("h%d",count),"",30,5.03,5.93);
// TH1D *hBck = new TH1D(Form("hBck%d",count),"",40,5,6);
TH1D *hMC = new TH1D(Form("hMC%d",count),"",30,5.03,5.93);
// Fit function
//QM2014
//TString iNP="6.71675e+00*Gaus(x,5.30142e+00,8.42680e-02)/(sqrt(2*3.14159)*8.42680e-02)+4.06744e+01*Gaus(x,5.00954e+00,8.11305e-02)/(sqrt(2*3.14159)*8.11305e-02)+5.99974e-01*(2.376716*Gaus(x,5.640619,0.095530)/(sqrt(2*3.14159)*0.095530)+3.702342*Gaus(x,5.501706,0.046222)/(sqrt(2*3.14159)*0.046222))+1.31767e-01*(61.195688*Gaus(x,5.127566,0.087439)/(sqrt(2*3.14159)*0.087439)+58.943919*Gaus(x,5.246471,0.041983)/(sqrt(2*3.14159)*0.041983))";
TString iNP="2.28629e1*Gaus(x,5.02606,6.84e-2)/(sqrt(2*3.14159)*(6.84e-2))+3.85695*Gaus(x,5.27701,0.04305)/(sqrt(2*3.14159)*(0.04305))";
TF1 *f = new TF1(Form("f%d",count),"[0]*([7]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2])+(1-[7])*Gaus(x,[1],[8])/(sqrt(2*3.14159)*[8]))+[3]+[4]*x+[6]*("+iNP+")");
nt->Project(Form("h%d",count),"mass",Form("%s&&pt>%f&&pt<%f",seldata_2y_kpi.Data(),ptmin,ptmax));
ntMC->Project(Form("hMC%d",count),"mass",Form("%s&&pt>%f&&pt<%f",seldata_2y_kpi.Data(),ptmin,ptmax));
// nt->Project(Form("hBck%d",count),"mass",Form("%s&&pt>%f&&pt<%f&&(gen==23333||gen==41000)",seldata.Data(),ptmin,ptmax));
// nt2->Project(Form("hBck%d",count),"mass",Form("%s&&pt>%f&&pt<%f&&(gen==23333||gen==41000)",seldata.Data(),ptmin,ptmax));
// cout <<"nsig = "<<hBck->GetEntries();
clean0(h);
h->Draw();
f->SetParLimits(4,-1000,0);
f->SetParLimits(2,0.01,0.08);
f->SetParLimits(8,0.01,0.1);
f->SetParLimits(7,0,1);
f->SetParLimits(6,0,1000);
f->SetParameter(0,setparam0);
f->SetParameter(1,setparam1);
f->SetParameter(2,setparam2);
f->SetParameter(8,setparam3);
f->FixParameter(1,fixparam1);
f->FixParameter(6,0);
h->GetEntries();
hMC->Fit(Form("f%d",count),"q","",5,6);
hMC->Fit(Form("f%d",count),"q","",5,6);
f->ReleaseParameter(1);
hMC->Fit(Form("f%d",count),"L q","",5,6);
hMC->Fit(Form("f%d",count),"L q","",5,6);
hMC->Fit(Form("f%d",count),"L q","",5,6);
hMC->Fit(Form("f%d",count),"L m","",5,6);
f->FixParameter(1,f->GetParameter(1));
f->FixParameter(2,f->GetParameter(2));
f->FixParameter(7,f->GetParameter(7));
f->FixParameter(8,f->GetParameter(8));
f->ReleaseParameter(6);
h->Fit(Form("f%d",count),"q","",5,6);
h->Fit(Form("f%d",count),"q","",5,6);
f->ReleaseParameter(1);
h->Fit(Form("f%d",count),"L q","",5,6);
h->Fit(Form("f%d",count),"L q","",5,6);
h->Fit(Form("f%d",count),"L q","",5,6);
h->Fit(Form("f%d",count),"L m","",5,6);
h->SetMarkerSize(0.8);
h->SetMarkerStyle(20);
cout <<h->GetEntries()<<endl;
cout<<"======= chi2 ======="<<endl;
cout<<f->GetChisquare()<<endl;
cout<<"===== chi2 end ====="<<endl;
// function for background shape plotting. take the fit result from f
TF1 *background = new TF1(Form("background%d",count),"[0]+[1]*x");
background->SetParameter(0,f->GetParameter(3));
background->SetParameter(1,f->GetParameter(4));
background->SetLineColor(4);
background->SetRange(5,6);
background->SetLineStyle(2);
// function for signal shape plotting. take the fit result from f
TF1 *Bkpi = new TF1(Form("fBkpi",count),"[0]*("+iNP+")");
Bkpi->SetParameter(0,f->GetParameter(6));
Bkpi->SetLineColor(kGreen+1);
Bkpi->SetFillColor(kGreen+1);
Bkpi->SetRange(5.00,6.00);
Bkpi->SetLineStyle(1);
Bkpi->SetFillStyle(3005);
// function for signal shape plotting. take the fit result from f
TF1 *mass = new TF1(Form("fmass",count),"[0]*([3]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2])+(1-[3])*Gaus(x,[1],[4])/(sqrt(2*3.14159)*[4]))");
mass->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(2),f->GetParameter(7),f->GetParameter(8));
mass->SetParError(0,f->GetParError(0));
mass->SetParError(1,f->GetParError(1));
mass->SetParError(2,f->GetParError(2));
mass->SetParError(7,f->GetParError(7));
mass->SetParError(8,f->GetParError(8));
mass->SetLineColor(2);
mass->SetLineStyle(2);
// cout <<mass->Integral(0,1.2)<<" "<<mass->IntegralError(0,1.2)<<endl;
h->SetMarkerStyle(24);
h->SetStats(0);
//.........这里部分代码省略.........
示例13: combinedFit
void combinedFit() {
TH1D * hB = new TH1D("hB","histo B",100,0,100);
TH1D * hSB = new TH1D("hSB","histo S+B",100, 0,100);
TF1 * fB = new TF1("fB","expo",0,100);
fB->SetParameters(1,-0.05);
hB->FillRandom("fB");
TF1 * fS = new TF1("fS","gaus",0,100);
fS->SetParameters(1,30,5);
hSB->FillRandom("fB",2000);
hSB->FillRandom("fS",1000);
// perform now global fit
TF1 * fSB = new TF1("fSB","expo + gaus(2)",0,100);
ROOT::Math::WrappedMultiTF1 wfB(*fB,1);
ROOT::Math::WrappedMultiTF1 wfSB(*fSB,1);
ROOT::Fit::DataOptions opt;
ROOT::Fit::DataRange rangeB;
// set the data range
rangeB.SetRange(10,90);
ROOT::Fit::BinData dataB(opt,rangeB);
ROOT::Fit::FillData(dataB, hB);
ROOT::Fit::DataRange rangeSB;
rangeSB.SetRange(10,50);
ROOT::Fit::BinData dataSB(opt,rangeSB);
ROOT::Fit::FillData(dataSB, hSB);
ROOT::Fit::Chi2Function chi2_B(dataB, wfB);
ROOT::Fit::Chi2Function chi2_SB(dataSB, wfSB);
GlobalChi2 globalChi2(chi2_B, chi2_SB);
ROOT::Fit::Fitter fitter;
const int Npar = 6;
double par0[Npar] = { 5,5,-0.1,100, 30,10};
// create before the parameter settings in order to fix or set range on them
fitter.Config().SetParamsSettings(6,par0);
// fix 5-th parameter
fitter.Config().ParSettings(4).Fix();
// set limits on the third and 4-th parameter
fitter.Config().ParSettings(2).SetLimits(-10,-1.E-4);
fitter.Config().ParSettings(3).SetLimits(0,10000);
fitter.Config().ParSettings(3).SetStepSize(5);
fitter.Config().MinimizerOptions().SetPrintLevel(0);
fitter.Config().SetMinimizer("Minuit2","Migrad");
// fit FCN function directly
// (specify optionally data size and flag to indicate that is a chi2 fit)
fitter.FitFCN(6,globalChi2,0,dataB.Size()+dataSB.Size(),true);
ROOT::Fit::FitResult result = fitter.Result();
result.Print(std::cout);
TCanvas * c1 = new TCanvas("Simfit","Simultaneous fit of two histograms",
10,10,700,700);
c1->Divide(1,2);
c1->cd(1);
gStyle->SetOptFit(1111);
fB->SetFitResult( result, iparB);
fB->SetRange(rangeB().first, rangeB().second);
fB->SetLineColor(kBlue);
hB->GetListOfFunctions()->Add(fB);
hB->Draw();
c1->cd(2);
fSB->SetFitResult( result, iparSB);
fSB->SetRange(rangeSB().first, rangeSB().second);
fSB->SetLineColor(kRed);
hSB->GetListOfFunctions()->Add(fSB);
hSB->Draw();
}示例14: fit
TF1* fit(TH1D* h, TH1D* hMCSignal, TH1D* hMCSwapped, Float_t ptmin, Float_t ptmax, Int_t j)
{
TCanvas* c = new TCanvas(Form("c_%.0f_%.0f_%d",ptmin,ptmax,j),"",600,600);
TF1* f = new TF1(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"[0]*([7]*([9]*Gaus(x,[1],[2]*(1+[11]))/(sqrt(2*3.14159)*[2]*(1+[11]))+(1-[9])*Gaus(x,[1],[10]*(1+[11]))/(sqrt(2*3.14159)*[10]*(1+[11])))+(1-[7])*Gaus(x,[1],[8]*(1+[11]))/(sqrt(2*3.14159)*[8]*(1+[11])))+[3]+[4]*x+[5]*x*x+[6]*x*x*x", 1.7, 2.0);
f->SetParLimits(4,-1000,1000);
f->SetParLimits(10,0.001,0.05);
f->SetParLimits(2,0.01,0.5);
f->SetParLimits(8,0.02,0.2);
f->SetParLimits(7,0,1);
f->SetParLimits(9,0,1);
f->SetParameter(0,setparam0);
f->SetParameter(1,setparam1);
f->SetParameter(2,setparam2);
f->SetParameter(10,setparam10);
f->SetParameter(9,setparam9);
f->FixParameter(8,setparam8);
f->FixParameter(7,1);
f->FixParameter(1,fixparam1);
f->FixParameter(3,0);
f->FixParameter(4,0);
f->FixParameter(5,0);
f->FixParameter(6,0);
f->FixParameter(11,0);
h->GetEntries();
hMCSignal->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"q","",minhisto,maxhisto);
hMCSignal->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"q","",minhisto,maxhisto);
f->ReleaseParameter(1);
hMCSignal->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L q","",minhisto,maxhisto);
hMCSignal->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L q","",minhisto,maxhisto);
hMCSignal->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L m","",minhisto,maxhisto);
f->FixParameter(1,f->GetParameter(1));
f->FixParameter(2,f->GetParameter(2));
f->FixParameter(10,f->GetParameter(10));
f->FixParameter(9,f->GetParameter(9));
f->FixParameter(7,0);
f->ReleaseParameter(8);
f->SetParameter(8,setparam8);
hMCSwapped->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L q","",minhisto,maxhisto);
hMCSwapped->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L q","",minhisto,maxhisto);
hMCSwapped->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L q","",minhisto,maxhisto);
hMCSwapped->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L m","",minhisto,maxhisto);
f->FixParameter(7,hMCSignal->Integral(0,1000)/(hMCSwapped->Integral(0,1000)+hMCSignal->Integral(0,1000)));
f->FixParameter(8,f->GetParameter(8));
f->ReleaseParameter(3);
f->ReleaseParameter(4);
f->ReleaseParameter(5);
f->ReleaseParameter(6);
f->SetLineColor(kRed);
h->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"q","",minhisto,maxhisto);
h->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"q","",minhisto,maxhisto);
f->ReleaseParameter(1);
f->SetParLimits(1,1.86,1.87);
/*
f->ReleaseParameter(11);
f->SetParLimits(11,-1.,1.);
*/
h->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L q","",minhisto,maxhisto);
h->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L q","",minhisto,maxhisto);
h->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L q","",minhisto,maxhisto);
h->Fit(Form("f_%.0f_%.0f_%d",ptmin,ptmax,j),"L m","",minhisto,maxhisto);
TF1* background = new TF1(Form("background_%.0f_%.0f_%d",ptmin,ptmax,j),"[0]+[1]*x+[2]*x*x+[3]*x*x*x");
background->SetParameter(0,f->GetParameter(3));
background->SetParameter(1,f->GetParameter(4));
background->SetParameter(2,f->GetParameter(5));
background->SetParameter(3,f->GetParameter(6));
background->SetLineColor(4);
background->SetRange(minhisto,maxhisto);
background->SetLineStyle(2);
TF1* mass = new TF1(Form("mass_%.0f_%.0f_%d",ptmin,ptmax,j),"[0]*([3]*([4]*Gaus(x,[1],[2]*(1+[6]))/(sqrt(2*3.14159)*[2]*(1+[6]))+(1-[4])*Gaus(x,[1],[5]*(1+[6]))/(sqrt(2*3.14159)*[5]*(1+[6]))))");
mass->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(2),f->GetParameter(7),f->GetParameter(9),f->GetParameter(10),f->GetParameter(11));
mass->SetParError(0,f->GetParError(0));
mass->SetParError(1,f->GetParError(1));
mass->SetParError(2,f->GetParError(2));
mass->SetParError(3,f->GetParError(7));
mass->SetParError(4,f->GetParError(9));
mass->SetParError(5,f->GetParError(10));
mass->SetFillColor(kOrange-3);
mass->SetFillStyle(3002);
mass->SetLineColor(kOrange-3);
mass->SetLineWidth(3);
mass->SetLineStyle(2);
TF1* massSwap = new TF1(Form("massSwap_%.0f_%.0f_%d",ptmin,ptmax,j),"[0]*(1-[2])*Gaus(x,[1],[3]*(1+[4]))/(sqrt(2*3.14159)*[3]*(1+[4]))");
massSwap->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(7),f->GetParameter(8),f->GetParameter(11));
massSwap->SetParError(0,f->GetParError(0));
massSwap->SetParError(1,f->GetParError(1));
massSwap->SetParError(2,f->GetParError(7));
massSwap->SetParError(3,f->GetParError(8));
massSwap->SetFillColor(kGreen+4);
//.........这里部分代码省略.........
示例15: fit
TF1* fit(TString variable, TString variableplot, TTree* nt, TTree* ntMC, Double_t ptmin, Double_t ptmax, int isMC)
{
static int count=0;
count++;
TCanvas* c= new TCanvas(Form("c%d",count),"",600,600);
TH1D* h = new TH1D(Form("h-%d",count),"",nbinsmasshisto,minhisto,maxhisto);
TH1D* hMCSignal = new TH1D(Form("hMCSignal-%d",count),"",nbinsmasshisto,minhisto,maxhisto);
TH1D* hMCSwapped = new TH1D(Form("hMCSwapped-%d",count),"",nbinsmasshisto,minhisto,maxhisto);
TF1* f = new TF1(Form("f%d",count),"[0]*([7]*([9]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2])+(1-[9])*Gaus(x,[1],[10])/(sqrt(2*3.14159)*[10]))+(1-[7])*Gaus(x,[1],[8])/(sqrt(2*3.14159)*[8]))+[3]+[4]*x+[5]*x*x+[6]*x*x*x", 1.7, 2.0);
TString mycut=Form("(%s&&(%s)>%f&&(%s)<%f)",seldata.Data(),variable.Data(),ptmin,variable.Data(),ptmax);
if(isMC==1) nt->Project(Form("h-%d",count),"Dmass",TCut(weight)*TCut(mycut));
else nt->Project(Form("h-%d",count),"Dmass",Form("(%s&&(%s)>%f&&(%s)<%f)",seldata.Data(),variable.Data(),ptmin,variable.Data(),ptmax));
ntMC->Project(Form("hMCSignal-%d",count),"Dmass",Form("%s*(%s&&(%s)>%f&&(%s)<%f&&(Dgen==23333))",weight.Data(),selmc.Data(),variable.Data(),ptmin,variable.Data(),ptmax));
ntMC->Project(Form("hMCSwapped-%d",count),"Dmass",Form("%s*(%s&&(%s)>%f&&(%s)<%f&&(Dgen==23344))",weight.Data(),selmc.Data(),variable.Data(),ptmin,variable.Data(),ptmax));
TFile *fout=new TFile(Form("FitsFiles/Fits_%s_%d.root",collisionsystem.Data(),count),"recreate");
fout->cd();
hMCSignal->Write();
hMCSwapped->Write();
h->Write();
fout->Close();
f->SetParLimits(4,-1000,1000);
f->SetParLimits(10,0.001,0.05);
f->SetParLimits(2,0.01,0.1);
f->SetParLimits(8,0.02,0.2);
f->SetParLimits(7,0,1);
f->SetParLimits(9,0,1);
f->SetParameter(0,setparam0);
f->SetParameter(1,setparam1);
f->SetParameter(2,setparam2);
f->SetParameter(10,setparam10);
f->SetParameter(9,setparam9);
f->FixParameter(8,setparam8);
f->FixParameter(7,1);
f->FixParameter(1,fixparam1);
f->FixParameter(3,0);
f->FixParameter(4,0);
f->FixParameter(5,0);
f->FixParameter(6,0);
h->GetEntries();
hMCSignal->Fit(Form("f%d",count),"q","",minhisto,maxhisto);
hMCSignal->Fit(Form("f%d",count),"q","",minhisto,maxhisto);
f->ReleaseParameter(1);
hMCSignal->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
hMCSignal->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
hMCSignal->Fit(Form("f%d",count),"L m","",minhisto,maxhisto);
f->FixParameter(1,f->GetParameter(1));
f->FixParameter(2,f->GetParameter(2));
f->FixParameter(10,f->GetParameter(10));
f->FixParameter(9,f->GetParameter(9));
f->FixParameter(7,0);
f->ReleaseParameter(8);
f->SetParameter(8,setparam8);
hMCSwapped->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
hMCSwapped->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
hMCSwapped->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
hMCSwapped->Fit(Form("f%d",count),"L m","",minhisto,maxhisto);
f->FixParameter(7,hMCSignal->Integral(0,1000)/(hMCSwapped->Integral(0,1000)+hMCSignal->Integral(0,1000)));
f->FixParameter(8,f->GetParameter(8));
f->ReleaseParameter(3);
f->ReleaseParameter(4);
f->ReleaseParameter(5);
f->ReleaseParameter(6);
f->SetLineColor(kRed);
h->Fit(Form("f%d",count),"q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"q","",minhisto,maxhisto);
f->ReleaseParameter(1);
//f->ReleaseParameter(2); // you need to release these two parameters if you want to perform studies on the sigma shape
//f->ReleaseParameter(10); // you need to release these two parameters if you want to perform studies on the sigma shape
h->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"L q","",minhisto,maxhisto);
h->Fit(Form("f%d",count),"L m","",minhisto,maxhisto);
TF1* background = new TF1(Form("background%d",count),"[0]+[1]*x+[2]*x*x+[3]*x*x*x");
background->SetParameter(0,f->GetParameter(3));
background->SetParameter(1,f->GetParameter(4));
background->SetParameter(2,f->GetParameter(5));
background->SetParameter(3,f->GetParameter(6));
background->SetLineColor(4);
background->SetRange(minhisto,maxhisto);
background->SetLineStyle(2);
TF1* mass = new TF1(Form("fmass%d",count),"[0]*([3]*([4]*Gaus(x,[1],[2])/(sqrt(2*3.14159)*[2])+(1-[4])*Gaus(x,[1],[5])/(sqrt(2*3.14159)*[5])))");
mass->SetParameters(f->GetParameter(0),f->GetParameter(1),f->GetParameter(2),f->GetParameter(7),f->GetParameter(9),f->GetParameter(10));
mass->SetParError(0,f->GetParError(0));
//.........这里部分代码省略.........