Generally speaking, the visualization of detector geometry and the screen dump of a Geant4 application can be all regarded as output of a Geant4 simulation. Strictly speaking, the output of a Geant4 simulation includes histograms and/or ntuples of data generated during the simulation, which can be used to reveal statistical distributions of, for example, positions and energy depositions of interactions.
GEARS utilizes Geant4 analysis managers to provide four output formats: ROOT, HDF5, CSV, and AIDA XML.
The output file name can be chosen using the macro command:
One of the following suffix is needed to specify the output file format:
.xml. Note that the output is disabled by default. It will be enabled if the output file name is not empty. So this macro command also works as a switch. Without it, no output file will be created.
Geant4 can print out on screen detailed information of a simulation if you increase the verbose level of tracking using the macro command /tracking/verbose, for example,
# turn on detailed information about tracking /tracking/verbose 2 # run a few events for debugging /run/beamOn 10 # turn off screen dump for fast simulation /tracking/verbose 0 # run a lot of events /run/beamOn 100000
You can re-direct the screen dump to a file for detailed examination:
$ gears macro.mac | tee log $ less log
The ROOT version of ntuples is TTree, which is commonly called a tree. Simply put, a tree is a table. Each row is called an entry (or an event) and each column is called a branch (of course, we are dealing with a tree after all). If you simulate 1000 events using GEARS, your ROOT tree would have 1000 entries. If you save the first interaction position
z in the tree, your tree would have 3 branches, each holds 1000 values of
z. If an event has more than just one hit, you will have a few
z’s for each event (row), and your table would have one more dimension, labeled as
Iteration$ in TTree, the depth of which may change event by event since each event may have a different number of hits.
The ROOT TTree offers the following features that are desired for analyzing data generated by GEARS:
- It is designed to work with large data sets. For example, it can deal with Terra Bytes of data easily. It does so by loading individual branches separately to a PC memory for analysis, which requires relatively small memory compared to loading the whole table as many other analysis tools do.
- It compresses data to save disk space.
- It provide functions to create and analyze statistical distributions of data using multiple dimensional histograms.
Here are some example codes that can be run in a ROOT interactive session to generate histograms:
$ root gears.root # open the output file in root format using ROOT root  .ls TFile** gears.root TFile* gears.root KEY: TTree t;1 Geant4 step points root  t->GetEntries() (long long) 5000 root  t->Show(0) ======> EVENT:0 n = 235 m = 2 trk = (vector<int>*)0x351a520 stp = (vector<int>*)0x398c7b0 vlm = (vector<int>*)0x2d4dba0 pro = (vector<int>*)0x3524f60 pdg = (vector<int>*)0x34302c0 pid = (vector<int>*)0x3972e80 xx = (vector<double>*)0x3548ce0 yy = (vector<double>*)0x2d4ef10 zz = (vector<double>*)0x354e600 dt = (vector<double>*)0x3549db0 de = (vector<double>*)0x34b2d90 dl = (vector<double>*)0x2f63630 l = (vector<double>*)0x2f636f0 x = (vector<double>*)0x2d50760 y = (vector<double>*)0x351a450 z = (vector<double>*)0x3543f10 t = (vector<double>*)0x351eed0 k = (vector<double>*)0x3a907c0 p = (vector<double>*)0x2f307c0 q = (vector<double>*)0x2ae30c0 et = (vector<double>*)0x35293f0 root  t->Draw("x","k*(pdg==22)")
ROOT is less known than Python outside of the high energy physics community. The good news for people who are not familiar with ROOT is that GEARS does not depend on ROOT to compile or run, even though its output can be saved in ROOT TTree format, and that the analysis of GEARS output can be done in Python instead of ROOT thanks to the uproot Python package. The best way to get started with analyzing GEARS output in Python would be to follow the uproot tutorial.
If you are familiar with ROOT and would like to migrate to Python for analyzing GEARS output, you can find here a brief list of Python equivalence of ROOT commands:
- Open file:
- Check file contents:
- List variables in TTree ntuples:
- Draw the distribution of a variable as a histogram:
- Draw the distribution of a selected subset of the variable as a histogram:
Geant4 tracks a particle step by step as it passes through the simulated world until it goes out of it, gets absorbed in a material, or changes to other particles, as shown in the following figure. A step point is a point in a particle track where the particle is generated or changed.
Geant4 artificially adds a step point on the boundary of two volumes when the track goes from one volume into the other, even if there is no change of the particle.
A step point in GEARS contains the following information:
- Track id (
- Step number, starting from 0 (
- Detector volume copy number (
- Process id (
- Particle id (
- Track id of the parent particle (
- Local position
xx[mm] (origin: center of the volume)
- Local position
yy[mm] (origin: center of the volume)
- Local position
zz[mm] (origin: center of the volume)
- Local time
dt[ns] (time elapsed from previous step point)
- Energy deposited [keV] (
- Step length [mm] (
- Trajectory length [mm] (
- Global position
x[mm] (origin: center of the world)
- Global position
y[mm] (origin: center of the world)
- Global position
z[mm] (origin: center of the world)
- Global time
t[ns] (time elapsed from the beginning of event)
- Kinetic energy of the particle [keV] (
- Momentum of the particle [keV] (
- Charges (
They are saved in separated C++ vectors (arrays with various sizes). Such a flat data structure and very short variable names are chosen on purpose to make plotting of those variables in a ROOT interactive session easy.
Notice that the variable
n is the total number of step points recorded in each event.
m is the maximal copy number of a sensitive volume
The physics process generating each step point is saved in a variable
i is the index of the step point. It equals to (process type) * 1000 + (sub type). The Process types are defined in G4ProcessType.hh, sub types are defined in G4HadronicProcessType.hh, G4DecayProcessType.hh, G4EmProcessSubType.hh, G4TransportationProcessType.hh, G4FastSimulationProcessType.hh, G4OpProcessSubType.hh, etc. They can be found in http://www-geant4.kek.jp/lxr/find?string=Type.hh.
- less than 1000: not defined
- 1000 to 2000: transportation
- 1000: initial step (step 0)
- 1091: transportation
- 2000 to 3000: electromagnetic
- 2001: Coulomb scattering
- 2002: ionization
- 2003: Bremsstrahlung
- 2004: pair production by charged particles
- 2005: annihilation
- 2010: multiple scattering
- 2011: Rayleigh scattering
- 2012: photoelectric effect
- 2013: Compton scattering
- 2014: gamma conversion (pair production)
- 2016: gamma general process, include 2010 to 2014
- 2021: Cherenkov
- 2022: scintillation
- 2023: synchrotron radiation
- 3000 to 4000: optical
- 3031: absorption
- 3032: boundary
- 3033: Rayleigh scattering
- 3034: WLS
- 3035: Mie scattering
- 3036: WLS2
- 4000 to 5000: hadronic
- 4111: hadron elastic
- 4121: hadron inelastic
- 4131: capture
- 4132: muon atomic capture
- 4141: fission
- 4151: hadron decay at rest
- 4142: lepton decay at rest
- 4161: charge exchange
- 4210: radioactive decay
- 5000 to 6000: photolepton_hadron
- 6000 to 7000: decay
- 6201: decay
- 6202: decay with spin
- 6203: pion decay with spin
- 6210: radioactive decay
- 7000 to 8000: general
- 7403: neutron killer
- 8000 to 9000: Parameterisation
- 9000 to 10000: user defined
- 10000 to 11000: parallel
- 11000 to 12000: phonon
- 12000 to 13000: UCN
The type of particle related to a step point is saved in a variable
pdg. It is the same as the PDG encoding of the particle. A Google search will give more information about it. The name
pid is used for the parent particle’s track id. A complete list of nuclei PDG encoding can be found here.
Record information of step 0
One cannot get access to step 0 (initStep printed on screen if
/tracking/verbose is set to be more than 0) through G4UserSteppingAction, which only provides access to step 1 and afterwards. However, step 0 contains some very important information that is constantly requested by the user. For example, the energy of a gamma ray from a radioactive decay is only available from step 0. Such information can be easily displayed using the following ROOT command with the Output ROOT tree,
// draw kinetic energy, "k", of a gamma (pdg==22) // created by radioactive decay process (pro==6210) t->Draw("k","pro==6210 && pdg==22")
This is achieved by using G4SteppingVerbose instead of G4UserSteppingAction for data recording. The former provides a function called TrackingStarted() to print verbose information about step 0 on screen if
/tracking/verbose is set to be more than 0. It also provides a function called StepInfo() to print verbose information about steps after step 0 on screen if
/tracking/verbose is more than 0. G4SteppingVerbose::StepInfo() is called right before G4UserSteppingAction::UserSteppingAction(G4Step) is called in G4SteppingManager::Stepping(), it hence can be used to fully replace the functionality of G4UserSteppingAction::UserSteppingAction(G4Step).
In fact, G4UserSteppingAction::UserSteppingAction(G4Step*) is not used at all in GEARS. The Output class inherits TrackingStarted() and StepInfo() from G4SteppingVerbose to record data from all steps. There is another advantage of using G4SteppingVerbose instead of G4UserSteppingAction for recording, that is, G4SteppingVerbose is provided as a globally available singleton, which can be easily accessed at different places in the codes using:
This is used in G4UserRunAction to open and close a TFile, in G4UserEventAction to fill a TTree.
The catch is that functions in G4SteppingVerbose will not be called in G4SteppingManager unless
/tracking/verbose is set, which will print too much information on screen for a long run. This is solved in EventAction::BeginOfEventAction by turning on tracking verbose all the time so that all functions in G4SteppingVerbose will be called, while at the same time, turning on G4SteppingVerbose local verbose flag Silent to run them in silent mode.
In addition to arrays of parameters of individual step points, a GEARS output file also contains an array of the total energies deposited in the sensitive volumes of the simulated detector. The index of the array is the same as the copy numbers of those volumes. The name of the array is called
et. Since the copy number of a sensitive volume has to start from 1,
et is used to store the total energy deposited in all sensitive volumes. You can use the following command to draw the total energy deposited in a sensitive volume with a copy number
root  t->Draw("et")
One can use the following command to generate
gears.root in GEARS/tutorials/output/:
$ gears radiate.mac
radiate.mac demonstrates how to use Geant4 macro commands to save step points and total energies in sensitive volumes. It uses the detector geometry defined in detector.tg.
Here are some sample ROOT commands that one can use to generate plots from
// draw tracks of the primary particle on x-y plane in event 1 root t->Draw("x:y", "trk==1","l", 1, 1) // show physics processes creating secondary particles root t->Draw("pro","trk>1 && stp==0") // display hits distribution in volume with copy number 1 root t->Draw("x:y:z", "vlm==1") // show how many types of particles are involved in the simulation root t->Draw("pdg"); // show physics process related to gamma-rays root t->Draw("pro", "pdg==22 && stp!=0"); // show spatial distributions of secondary particles root t->Draw("x:y", "trk>1") // plot dE/dx versus momentum root t->Draw("de/dl:p") // draw energy spectrum recorded by volume (detector) 1 root t->Draw("et")
Combine step points to hits in detector
Many of the step points in a Geant4 simulation are very close to each other, especially those of charged particles, as they quickly lose energy through multiple scattering or ionizing surrounding atoms in a very small range. The space resolution of a real-life detector is normally not enough to resolve these details. As seen by such a detector, all nearby step points act as a single hit, the energy of which is a sum of deposited energies from all these step points, the position of which is an energy-weighted average of all these step point positions. The modeling of detector response normally start with combined hits instead of the original step points directly from Geant4 to save computational power.
A ROOT script combineStepPointsToHits.C, is provided to demonstrate the combining procedure. It takes the output from GEARS and save the combined hits to another ROOT file
hits.root. Another ROOT script, drawHits.C, is used to demonstrate the final result shown in the following plot.
These ROOT scripts can be directly executed without compilation:
$ root -q combineStepPointsToHits.C $ root drawHits.C
Note that they have to be run after you execute
gears radiate.mac, since they need the Geant4 output as input.