gonalyzer

README

TTree GOnalyzer

This is a tool written in go to produce publication-quality plots from ROOT TTrees in an flexible and easy way. This tool is built on top of go-hep.org. The main supported features are:

• histograming variables over many samples and selections,
• displaying one or several signals (overlaid or stacked),
• sample normalisation using cross-section and/or luminosity and/or number of generated events,
• computing of new variables of arbitrary complexity,
• joint trees to the main one, as in TTreeFriend,
• dumping TTree's with float64 and []float64 branches,
• concurent sample processings.

In a nutshell

// Define samples
samples := []*ana.Sample{
	ana.CreateSample("data", "data", `Data`, "data.root", "mytree"),
	ana.CreateSample("bkg1", "bkg", `Proc 1`, "proc1.root", "mytree"),
	ana.CreateSample("bkg2", "bkg", `Proc 2`, "proc2.root", "mytree"),
	ana.CreateSample("bkg3", "bkg", `Proc 3`, "proc3.root", "mytree"),
}

// Define variables
variables := []*ana.Variable{
	ana.NewVariable("plot1", ana.TreeVarBool("branchBool"), 2, 0, 2),
	ana.NewVariable("plot2", ana.TreeVarF32("branchF32"), 25, 0, 1000),
	ana.NewVariable("plot3", ana.TreeVarF64("branchF64"), 50, 0, 1000),
}

// Create analyzer object with some options
analyzer := ana.New(samples, variables, ana.WithHistoNorm(true))

// Produce plots and dump trees
analyzer.Run()

Gallery

Data/Background [code]	Unstacked signals [code]	Stacked signals [code]
Shape distortion [code]	Shape comparison [code]	Systematic variation [code]

Performances

For 2M events and 60 variables, a comparison with similar ROOT-based code (using t->Draw()) gives:

• ROOT -> 6 ms/kEvts
• GOHEP -> 2 ms/kEvts

For 2M event and one variable (avoiding t->Draw() repetition)

• ROOT -> 0.4 ms/kEvts
• GOHEP -> 0.1 ms/kEvts

Documentation

Overview

Package gonalyzer exposes types and functions to ease the analysis of ROOT trees.

// Define samples
samples := []*ana.Sample{
  ana.CreateSample("data", "data", `Data`, "data.root", "mytree"),
  ana.CreateSample("bkg1", "bkg", `Proc 1`, "proc1.root", "mytree"),
  ana.CreateSample("bkg2", "bkg", `Proc 2`, "proc2.root", "mytree"),
}

// Define variables
variables := []*ana.Variable{
  ana.NewVariable("plot1", ana.TreeVarBool("branchBool"), 2, 0, 2),
  ana.NewVariable("plot2", ana.TreeVarF32("branchF32"), 25, 0, 1000),
  ana.NewVariable("plot3", ana.TreeVarF64("branchF64"), 50, 0, 1000),
}

// Create analyzer object with some options
analyzer := ana.New(samples, variables)

// Produce plots
analyzer.Run()

There is also the possibility of doing cutflows in a simple way. Few lines of code can produce this ASCII table:

| Cut name              | Raw Yields                 | Weighted Yields            |
|                       |                 Abs    Rel |                 Abs    Rel |
|-----------------------|----------------------------|----------------------------|
| Electron channel      |         5526   100%   100% |     28230.59   100%   100% |
| pT > 10 GeV           |         5281    96%    96% |     28065.97    99%    99% |
| Phi < 2.0 rad         |         4312    78%    82% |     22874.73    81%    82% |