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Reference Guide
mp_H1_lambdas.C File Reference

Detailed Description

View in nbviewer Open in SWAN Lambdas used to check and fit the result of the H1 analysis. Used by mp104_processH1.C, mp105_processEntryList.C and roottest/root/multicore/tProcessExecutorH1Test.C

// This function is used to check the result of the H1 analysis
auto checkH1 = [](TList *out) {
// Make sure the output list is there
if (!out) {
std::cout << "checkH1 >>> Test failure: output list not found\n";
return -1;
}
// Check the 'hdmd' histo
auto hdmd = dynamic_cast<TH1F *>(out->FindObject("hdmd"));
if (!hdmd) {
std::cout << "checkH1 >>> Test failure: 'hdmd' histo not found\n";
return -1;
}
if ((Int_t)(hdmd->GetEntries()) != 7525) {
std::cout << "checkH1 >>> Test failure: 'hdmd' histo: wrong number"
" of entries ("
<< (Int_t)(hdmd->GetEntries()) << ": expected 7525) \n";
return -1;
}
if (TMath::Abs((hdmd->GetMean() - 0.15512023) / 0.15512023) > 0.001) {
std::cout << "checkH1 >>> Test failure: 'hdmd' histo: wrong mean (" << hdmd->GetMean()
<< ": expected 0.15512023) \n";
return -1;
}
auto h2 = dynamic_cast<TH2F *>(out->FindObject("h2"));
if (!h2) {
std::cout << "checkH1 >>> Test failure: 'h2' histo not found\n";
return -1;
}
if ((Int_t)(h2->GetEntries()) != 7525) {
std::cout << "checkH1 >>> Test failure: 'h2' histo: wrong number"
" of entries ("
<< (Int_t)(h2->GetEntries()) << ": expected 7525) \n";
return -1;
}
if (TMath::Abs((h2->GetMean() - 0.15245688) / 0.15245688) > 0.001) {
std::cout << "checkH1 >>> Test failure: 'h2' histo: wrong mean (" << h2->GetMean() << ": expected 0.15245688) \n";
return -1;
}
// Done
return 0;
};
// This function is used to fit the result of the analysis with graphics
auto doFit = [](TList *out, const char *lfn = 0) -> Int_t {
if (lfn)
gSystem->RedirectOutput(lfn, "a", &redH);
auto hdmd = dynamic_cast<TH1F *>(out->FindObject("hdmd"));
auto h2 = dynamic_cast<TH2F *>(out->FindObject("h2"));
// function called at the end of the event loop
if (hdmd == 0 || h2 == 0) {
std::cout << "doFit: hdmd = " << hdmd << " , h2 = " << h2 << "\n";
return -1;
if (lfn)
gSystem->RedirectOutput(0, 0, &redH);
}
// create the canvas for the h1analysis fit
TCanvas *c1 = new TCanvas("c1", "h1analysis analysis", 10, 10, 800, 600);
c1->SetBottomMargin(0.15);
hdmd->GetXaxis()->SetTitle("m_{K#pi#pi} - m_{K#pi}[GeV/c^{2}]");
hdmd->GetXaxis()->SetTitleOffset(1.4);
// fit histogram hdmd with function f5 using the log-likelihood option
if (gROOT->GetListOfFunctions()->FindObject("f5"))
delete gROOT->GetFunction("f5");
auto fdm5 = [](Double_t *xx, Double_t *par) -> Double_t {
const Double_t dxbin = (0.17 - 0.13) / 40; // Bin-width
Double_t x = xx[0];
if (x <= 0.13957)
return 0;
Double_t xp3 = (x - par[3]) * (x - par[3]);
Double_t res = dxbin * (par[0] * TMath::Power(x - 0.13957, par[1]) +
par[2] / 2.5066 / par[4] * TMath::Exp(-xp3 / 2 / par[4] / par[4]));
return res;
};
auto f5 = new TF1("f5", fdm5, 0.139, 0.17, 5);
f5->SetParameters(1000000, .25, 2000, .1454, .001);
hdmd->Fit("f5", "lr");
// Check the result of the fit
Double_t ref_f5[4] = {959915.0, 0.351114, 1185.03, 0.145569};
for (int i : {0, 1, 2, 3}) {
if ((TMath::Abs((f5->GetParameters())[i] - ref_f5[i]) / ref_f5[i]) > 0.001) {
std::cout << "\n >>> Test failure: fit to 'f5': parameter '" << f5->GetParName(i) << "' has wrong value ("
<< (f5->GetParameters())[i] << ": expected" << ref_f5[i] << ") \n";
if (lfn)
gSystem->RedirectOutput(0, 0, &redH);
return -1;
}
}
// create the canvas for tau d0
auto c2 = new TCanvas("c2", "tauD0", 100, 100, 800, 600);
c2->SetGrid();
c2->SetBottomMargin(0.15);
// Project slices of 2-d histogram h2 along X , then fit each slice
// with function f2 and make a histogram for each fit parameter
// Note that the generated histograms are added to the list of objects
// in the current directory.
if (gROOT->GetListOfFunctions()->FindObject("f2"))
delete gROOT->GetFunction("f2");
auto fdm2 = [](Double_t *xx, Double_t *par) -> Double_t {
const auto dxbin = (0.17 - 0.13) / 40; // Bin-width
const auto sigma = 0.0012;
auto x = xx[0];
if (x <= 0.13957)
return 0;
auto xp3 = (x - 0.1454) * (x - 0.1454);
auto res = dxbin * (par[0] * TMath::Power(x - 0.13957, 0.25) +
par[1] / 2.5066 / sigma * TMath::Exp(-xp3 / 2 / sigma / sigma));
return res;
};
auto f2 = new TF1("f2", fdm2, 0.139, 0.17, 2);
f2->SetParameters(10000, 10);
// Restrict to three bins in this example
std::cout << "doFit: restricting fit to two bins only in this example...\n";
h2->FitSlicesX(f2, 10, 20, 10, "g5 l");
// Check the result of the fit
Double_t ref_f2[2] = {52432.2, 105.481};
for (int i : {0, 1}) {
if ((TMath::Abs((f2->GetParameters())[i] - ref_f2[i]) / ref_f2[i]) > 0.001) {
std::cout << "\n >>> Test failure: fit to 'f2': parameter '" << f2->GetParName(i) << "' has wrong value ("
<< (f2->GetParameters())[i] << ": expected" << ref_f2[i] << ") \n";
if (lfn)
gSystem->RedirectOutput(0, 0, &redH);
return -1;
}
}
auto h2_1 = (TH1D *)gDirectory->Get("h2_1");
h2_1->GetXaxis()->SetTitle("#tau[ps]");
h2_1->SetMarkerStyle(21);
h2_1->Draw();
c2->Update();
auto line = new TLine(0, 0, 0, c2->GetUymax());
line->Draw();
// Have the number of entries on the first histogram (to cross check when running
// with entry lists)
auto psdmd = (TPaveStats *)hdmd->GetListOfFunctions()->FindObject("stats");
psdmd->SetOptStat(1110);
c1->Modified();
if (lfn)
gSystem->RedirectOutput(0, 0, &redH);
return 0;
};
// This is the function invoked during the processing of the trees.
auto doH1 = [](TTreeReader &reader) {
// Histograms
auto hdmd = new TH1F("hdmd", "Dm_d", 40, 0.13, 0.17);
auto h2 = new TH2F("h2", "ptD0 vs Dm_d", 30, 0.135, 0.165, 30, -3, 6);
TTreeReaderValue<Float_t> fPtds_d(reader, "ptds_d");
TTreeReaderValue<Float_t> fEtads_d(reader, "etads_d");
TTreeReaderValue<Float_t> fDm_d(reader, "dm_d");
TTreeReaderValue<Int_t> fIk(reader, "ik");
TTreeReaderValue<Int_t> fIpi(reader, "ipi");
TTreeReaderValue<Int_t> fIpis(reader, "ipis");
TTreeReaderValue<Float_t> fPtd0_d(reader, "ptd0_d");
TTreeReaderValue<Float_t> fMd0_d(reader, "md0_d");
TTreeReaderValue<Float_t> fRpd0_t(reader, "rpd0_t");
TTreeReaderArray<Int_t> fNhitrp(reader, "nhitrp");
TTreeReaderArray<Float_t> fRstart(reader, "rstart");
TTreeReaderArray<Float_t> fRend(reader, "rend");
TTreeReaderArray<Float_t> fNlhk(reader, "nlhk");
TTreeReaderArray<Float_t> fNlhpi(reader, "nlhpi");
TTreeReaderValue<Int_t> fNjets(reader, "njets");
while (reader.Next()) {
// Return as soon as a bad entry is detected
if (TMath::Abs(*fMd0_d - 1.8646) >= 0.04)
continue;
if (*fPtds_d <= 2.5)
continue;
if (TMath::Abs(*fEtads_d) >= 1.5)
continue;
(*fIk)--; // original fIk used f77 convention starting at 1
(*fIpi)--;
if (fNhitrp.At(*fIk) * fNhitrp.At(*fIpi) <= 1)
continue;
if (fRend.At(*fIk) - fRstart.At(*fIk) <= 22)
continue;
if (fRend.At(*fIpi) - fRstart.At(*fIpi) <= 22)
continue;
if (fNlhk.At(*fIk) <= 0.1)
continue;
if (fNlhpi.At(*fIpi) <= 0.1)
continue;
(*fIpis)--;
if (fNlhpi.At(*fIpis) <= 0.1)
continue;
if (*fNjets < 1)
continue;
// Fill the histograms
hdmd->Fill(*fDm_d);
h2->Fill(*fDm_d, *fRpd0_t / 0.029979 * 1.8646 / *fPtd0_d);
}
// Return a list
auto l = new TList;
l->Add(hdmd);
l->Add(h2);
l->SetOwner(kFALSE);
return l;
};
// This is the function invoked during the processing of the trees to create a TEntryList
auto doH1fillList = [](TTreeReader &reader) {
// Entry list
auto elist = new TEntryList("elist", "H1 selection from Cut");
TTreeReaderValue<Float_t> fPtds_d(reader, "ptds_d");
TTreeReaderValue<Float_t> fEtads_d(reader, "etads_d");
TTreeReaderValue<Int_t> fIk(reader, "ik");
TTreeReaderValue<Int_t> fIpi(reader, "ipi");
TTreeReaderValue<Int_t> fIpis(reader, "ipis");
TTreeReaderValue<Float_t> fMd0_d(reader, "md0_d");
TTreeReaderArray<Int_t> fNhitrp(reader, "nhitrp");
TTreeReaderArray<Float_t> fRstart(reader, "rstart");
TTreeReaderArray<Float_t> fRend(reader, "rend");
TTreeReaderArray<Float_t> fNlhk(reader, "nlhk");
TTreeReaderArray<Float_t> fNlhpi(reader, "nlhpi");
TTreeReaderValue<Int_t> fNjets(reader, "njets");
while (reader.Next()) {
// Return as soon as a bad entry is detected
if (TMath::Abs(*fMd0_d - 1.8646) >= 0.04)
continue;
if (*fPtds_d <= 2.5)
continue;
if (TMath::Abs(*fEtads_d) >= 1.5)
continue;
(*fIk)--; // original fIk used f77 convention starting at 1
(*fIpi)--;
if (fNhitrp.At(*fIk) * fNhitrp.At(*fIpi) <= 1)
continue;
if (fRend.At(*fIk) - fRstart.At(*fIk) <= 22)
continue;
if (fRend.At(*fIpi) - fRstart.At(*fIpi) <= 22)
continue;
if (fNlhk.At(*fIk) <= 0.1)
continue;
if (fNlhpi.At(*fIpi) <= 0.1)
continue;
(*fIpis)--;
if (fNlhpi.At(*fIpis) <= 0.1)
continue;
if (*fNjets < 1)
continue;
// Fill the entry list
elist->Enter(reader.GetCurrentEntry(), reader.GetTree());
}
return elist;
};
// This is the function invoked during the processing of the trees using a TEntryList
auto doH1useList = [](TTreeReader &reader) {
// Histograms
auto hdmd = new TH1F("hdmd", "Dm_d", 40, 0.13, 0.17);
auto h2 = new TH2F("h2", "ptD0 vs Dm_d", 30, 0.135, 0.165, 30, -3, 6);
TTreeReaderValue<Float_t> fDm_d(reader, "dm_d");
TTreeReaderValue<Float_t> fPtd0_d(reader, "ptd0_d");
TTreeReaderValue<Float_t> fRpd0_t(reader, "rpd0_t");
while (reader.Next()) {
// Fill the histograms
hdmd->Fill(*fDm_d);
h2->Fill(*fDm_d, *fRpd0_t / 0.029979 * 1.8646 / *fPtd0_d);
}
// Return a list
auto l = new TList;
l->Add(hdmd);
l->Add(h2);
l->SetOwner(kFALSE);
return l;
};
Author
Gerardo Ganis

Definition in file mp_H1_lambdas.C.

l
auto * l
Definition: textangle.C:4
TLine
Definition: TLine.h:22
TH2F
2-D histogram with a float per channel (see TH1 documentation)}
Definition: TH2.h:251
TList::FindObject
virtual TObject * FindObject(const char *name) const
Find an object in this list using its name.
Definition: TList.cxx:577
TF1::GetParameters
virtual Double_t * GetParameters() const
Definition: TF1.h:516
TTreeReaderValue< Float_t >
TH1D
1-D histogram with a double per channel (see TH1 documentation)}
Definition: TH1.h:615
TTreeReaderArray
An interface for reading collections stored in ROOT columnar datasets.
Definition: TTreeReaderArray.h:75
TMath::Exp
Double_t Exp(Double_t x)
Definition: TMath.h:727
Int_t
int Int_t
Definition: RtypesCore.h:45
TH1::GetEntries
virtual Double_t GetEntries() const
Return the current number of entries.
Definition: TH1.cxx:4301
x
Double_t x[n]
Definition: legend1.C:17
TMath::Abs
Short_t Abs(Short_t d)
Definition: TMathBase.h:120
fdm5
Double_t fdm5(Double_t *xx, Double_t *par)
Definition: h1analysisProxy.h:14
TStyle::SetOptFit
void SetOptFit(Int_t fit=1)
The type of information about fit parameters printed in the histogram statistics box can be selected ...
Definition: TStyle.cxx:1544
TPaveStats
Definition: TPaveStats.h:18
RedirectHandle_t
Definition: TSystem.h:203
TF1::SetParameters
virtual void SetParameters(const Double_t *params)
Definition: TF1.h:640
TH1::GetMean
virtual Double_t GetMean(Int_t axis=1) const
For axis = 1,2 or 3 returns the mean value of the histogram along X,Y or Z axis.
Definition: TH1.cxx:7085
TSystem::RedirectOutput
virtual Int_t RedirectOutput(const char *name, const char *mode="a", RedirectHandle_t *h=nullptr)
Redirect standard output (stdout, stderr) to the specified file.
Definition: TSystem.cxx:1711
gStyle
R__EXTERN TStyle * gStyle
Definition: TStyle.h:412
dxbin
const Double_t dxbin
Definition: h1analysisProxy.h:10
kFALSE
const Bool_t kFALSE
Definition: RtypesCore.h:92
TF1::GetParName
virtual const char * GetParName(Int_t ipar) const
Definition: TF1.h:525
TMath::Power
LongDouble_t Power(LongDouble_t x, LongDouble_t y)
Definition: TMath.h:735
TTreeReader
A simple, robust and fast interface to read values from ROOT columnar datasets such as TTree,...
Definition: TTreeReader.h:44
gDirectory
#define gDirectory
Definition: TDirectory.h:236
line
TLine * line
Definition: entrylistblock_figure1.C:235
TStyle::SetOptStat
void SetOptStat(Int_t stat=1)
The type of information printed in the histogram statistics box can be selected via the parameter mod...
Definition: TStyle.cxx:1592
TEntryList
Definition: TEntryList.h:25
gSystem
R__EXTERN TSystem * gSystem
Definition: TSystem.h:559
sigma
const Double_t sigma
Definition: h1analysisProxy.h:11
TObject::Draw
virtual void Draw(Option_t *option="")
Default Draw method for all objects.
Definition: TObject.cxx:197
Double_t
double Double_t
Definition: RtypesCore.h:59
TCanvas
Definition: TCanvas.h:23
TH1F
1-D histogram with a float per channel (see TH1 documentation)}
Definition: TH1.h:572
c2
return c2
Definition: legend2.C:14
TF1
1-Dim function class
Definition: TF1.h:212
fdm2
Double_t fdm2(Double_t *xx, Double_t *par)
Definition: h1analysisProxy.h:25
TList
Definition: TList.h:44
gROOT
#define gROOT
Definition: TROOT.h:406
c1
return c1
Definition: legend1.C:41