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examples/extended/analysis/.README.txt
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///\file "analysis/.README.txt"
///\brief Examples analysis README page
/*! \page Examples_analysis Category "analysis"
Examples in this directory demonstrate how to make histograms and ntuples
\link ExampleAnaEx01 AnaEx01 \endlink
Simple example showing use of g4tools.
\link ExampleAnaEx02 AnaEx02 \endlink
As AnaEx01, but direct interface to ROOT.
\link ExampleB1Con B1Con \endlink
B1Con shows how to use the statistical tool G4ConvergenceTester.
It does not make histograms.
It has the same geometry as B1.
*/
examples/extended/analysis/AnaEx01/.README.txt
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///\file "analysis/AnaEx01/.README.txt"
///\brief Example AnaEx01 README page
/*! \page ExampleAnaEx01 Example AnaEx01
Examples AnaEx01 and AnaEx02 show the usage of histogram and tuple
manipulations using G4Analysis and ROOT compliant systems on the same
scenario. All analysis manipulations (histo booking, filling, saving histos
in a file, etc...) are located in one class : HistoManager, implementation of
which is different in each example. All the other classes are same in all
three examples.
This example shows the usage of histogram and tuple manipulations using
G4Analysis system.
The example is an adaptation of examples/novice/N03. It describes a simple
sampling calorimeter setup.
\section AnaEx01_s1 Detector description
The calorimeter is a box made of a given number of layers. A layer
consists of an absorber plate and of a detection gap. The layer is
replicated.
Six parameters define the calorimeter :
- the material of the absorber,
- the thickness of an absorber plate,
- the material of the detection gap,
- the thickness of a gap,
- the number of layers,
- the transverse size of the calorimeter (the input face is a square).
The default geometry is constructed in DetectorConstruction class,
but all of the above parameters can be modified interactively via
the commands defined in the DetectorMessenger class.
<pre>
|<----layer 0---------->|<----layer 1---------->|<----layer 2---------->|
| | | |
==========================================================================
|| | || | || | ||
|| | || | || | ||
beam || absorber | gap || absorber | gap || absorber | gap ||
======> || | || | || | ||
|| | || | || | ||
==========================================================================
</pre>
\section AnaEx01_s2 Physics list
The particle's type and the physic processes which will be available
in this example are set in the FTFP_BERT physics list.
\section AnaEx01_s3 Action Initialization
A newly introduced class, ActionInitialization,
instantiates and registers to Geant4 kernel all user action classes
which are defined thread-local and a run action class
which is defined both thread-local and global.
The thread-local action classes are defined in
ActionInitialization::Build()
and the global run action class is defined in
ActionInitialization::BuildForMaster().
Note that ActionInitialization::Build() is also used to
instatiate user action clasess in sequential mode.
\section AnaEx01_s4 An event : PrimaryGeneratorAction
The primary kinematic consists of a single particle which hits the
calorimeter perpendicular to the input face. The type of the particle
and its energy are set in the PrimaryGeneratorAction class, and can
be changed via the G4 build-in commands of ParticleGun class.
\section AnaEx01_s5 Histograms
AnaEx01 can produce 4 histograms :
- EAbs : total energy deposit in absorber per event
- EGap : total energy deposit in gap per event
- LAbs : total track length of charged particles in absorber per event
- LGap : total track length of charged particles in gap per event
And 2 Ntuples :
- Ntuple1:
- one row per event : EnergyAbs EnergyGap
- Ntuple2:
- one row per event : TrackLAbs TrackLGap
These histos and ntuples are booked in HistoManager and filled from
EventAction.
One can control the name of the histograms file and its format:
- default name : AnaEx01
The format of the histogram file can be : root (default),
xml, csv. Include correct g4nnn.hh in HistoManager.hh
\section AnaEx01_s7 How to build
An additional step is needed when building the example with GNUmake
due to using the extra shared directory:
\verbatim
% cd path_to_AnaEx01/AnaEx01
% gmake setup
% gmake
\endverbatim
This will copy the files from shared in the example include and src;
to remove these files:
\verbatim
% gmake clean_setup
\endverbatim
\section AnaEx01_s8 HOW TO RUN
- Execute AnaEx01 in the 'interactive mode' with visualization
\verbatim
% ./AnaEx01
and type in the commands from run.mac line by line:
Idle> /control/verbose 2
Idle> /tracking/verbose 1
Idle> /run/beamOn 10
Idle> ...
Idle> exit
\endverbatim
or
\verbatim
Idle> /control/execute run.mac
....
Idle> exit
\endverbatim
- Execute AnaEx01 in the 'batch' mode from macro files
(without visualization)
\verbatim
% ./AnaEx01 run.mac
% ./AnaEx01 run.mac > run.out
\endverbatim
The AnaEx01.in macro is used in Geant4 testing.
*/
examples/extended/analysis/AnaEx01/README
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--------------------------------------------------
=========================================================
Geant4 - an Object-Oriented Toolkit for Simulation in HEP
=========================================================
AnaEx01
-------
Examples AnaEx01 and AnaEx02 show the usage of histogram and tuple
manipulations using G4Analysis and ROOT compliant systems on the same
scenario. All analysis manipulations (histo booking, filling, saving histos
in a file, etc...) are located in one class : HistoManager, implementation of
which is different in each example. All the other classes are same in all
three examples.
This example shows the usage of histogram and tuple manipulations using
G4Analysis system.
The example is an adaptation of examples/novice/N03. It describes a simple
sampling calorimeter setup.
1- Detector description
-----------------------
The calorimeter is a box made of a given number of layers. A layer
consists of an absorber plate and of a detection gap. The layer is
replicated.
Six parameters define the calorimeter :
- the material of the absorber,
- the thickness of an absorber plate,
- the material of the detection gap,
- the thickness of a gap,
- the number of layers,
- the transverse size of the calorimeter (the input face is a square).
The default geometry is constructed in DetectorConstruction class,
but all of the above parameters can be modified interactively via
the commands defined in the DetectorMessenger class.
|<----layer 0---------->|<----layer 1---------->|<----layer 2---------->|
| | | |
==========================================================================
|| | || | || | ||
|| | || | || | ||
beam || absorber | gap || absorber | gap || absorber | gap ||
======> || | || | || | ||
|| | || | || | ||
==========================================================================
2- Physics list
---------------
The particle's type and the physic processes which will be available
in this example are set in the FTFP_BERT physics list.
3- Action Initialization
------------------------
A newly introduced class, ActionInitialization,
instantiates and registers to Geant4 kernel all user action classes
which are defined thread-local and a run action class
which is defined both thread-local and global.
The thread-local action classes are defined in
ActionInitialization::Build()
and the global run action class is defined in
ActionInitialization::BuildForMaster().
Note that ActionInitialization::Build() is also used to
instatiate user action clasess in sequential mode.
4- An event : PrimaryGeneratorAction
------------------------------------
The primary kinematic consists of a single particle which hits the
calorimeter perpendicular to the input face. The type of the particle
and its energy are set in the PrimaryGeneratorAction class, and can
be changed via the G4 build-in commands of ParticleGun class.
5- Histograms
-------------
AnaEx01 can produce 4 histograms :
EAbs : total energy deposit in absorber per event
EGap : total energy deposit in gap per event
LAbs : total track length of charged particles in absorber per event
LGap : total track length of charged particles in gap per event
And 2 Ntuples :
- Ntuple1:
- one row per event : EnergyAbs EnergyGap
- Ntuple2:
- one row per event : TrackLAbs TrackLGap
These histos and ntuples are booked in HistoManager and filled from
EventAction.
One can control the name of the histograms file and its format:
default name : AnaEx01
The format of the histogram file can be : root (default),
xml, csv. Include correct g4nnn.hh in HistoManager.hh
6- How to build
---------------
An additional step is needed when building the example with GNUmake
due to using the extra shared directory:
% cd path_to_AnaEx01/AnaEx01
% gmake setup
% gmake
This will copy the files from shared in the example include and src;
to remove these files:
% gmake clean_setup
7- How to run
--------------
- Execute AnaEx01 in the 'interactive mode' with visualization
% ./AnaEx01
and type in the commands from run.mac line by line:
Idle> /control/verbose 2
Idle> /tracking/verbose 1
Idle> /run/beamOn 10
Idle> ...
Idle> exit
or
Idle> /control/execute run.mac
....
Idle> exit
- Execute AnaEx01 in the 'batch' mode from macro files
(without visualization)
% ./AnaEx01 run.mac
% ./AnaEx01 run.mac > run.out
The AnaEx01.in macro is used in Geant4 testing.
examples/extended/analysis/AnaEx02/.README.txt
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///\file "analysis/AnaEx02/.README.txt"
///\brief Example AnaEx02 README page
/*! \page ExampleAnaEx02 Example AnaEx02
Examples AnaEx01 and AnaEx02 show the usage of histogram and tuple
manipulations using G4Analysis and ROOT compliant systems on the same
scenario. All analysis manipulations (histo booking, filling, saving histos
in a file, etc...) are located in one class : HistoManager, implementation of
which is different in each example. All the other classes are same in all
three examples.
This example shows the usage of histogram and tuple manipulations using
ROOT system. Please install ROOT before building this example:
http://root.cern.ch
The example is an adaptation of examples/novice/N03. It describes a simple
sampling calorimeter setup.
\section AnaEx02_s1 Detector description
The calorimeter is a box made of a given number of layers. A layer
consists of an absorber plate and of a detection gap. The layer is
replicated.
Six parameters define the calorimeter :
- the material of the absorber,
- the thickness of an absorber plate,
- the material of the detection gap,
- the thickness of a gap,
- the number of layers,
- the transverse size of the calorimeter (the input face is a square).
The default geometry is constructed in DetectorConstruction class,
but all of the above parameters can be modified interactively via
the commands defined in the DetectorMessenger class.
<pre>
|<----layer 0---------->|<----layer 1---------->|<----layer 2---------->|
| | | |
==========================================================================
|| | || | || | ||
|| | || | || | ||
beam || absorber | gap || absorber | gap || absorber | gap ||
======> || | || | || | ||
|| | || | || | ||
==========================================================================
</pre>
\section AnaEx02_s2 Physics list
The particle's type and the physic processes which will be available
in this example are set in the FTFP_BERT physics list.
\section AnaEx02_s3 Action Initialization
A newly introduced class, ActionInitialization,
instantiates and registers to Geant4 kernel all user action classes
which are defined thread-local and a run action class
which is defined both thread-local and global.
The thread-local action classes are defined in
ActionInitialization::Build()
and the global run action class is defined in
ActionInitialization::BuildForMaster().
Note that ActionInitialization::Build() is also used to
instatiate user action clasess in sequential mode.
\section AnaEx02_s4 An event : PrimaryGeneratorAction
The primary kinematic consists of a single particle which hits the
calorimeter perpendicular to the input face. The type of the particle
and its energy are set in the PrimaryGeneratorAction class, and can
be changed via the G4 build-in commands of ParticleGun class.
\section AnaEx02_s5 Histograms
To produce histograms, ROOT system must be installed
AnaEx02 can produce 4 histograms :
- EAbs : total energy deposit in absorber per event
- EGap : total energy deposit in gap per event
- LAbs : total track length of charged particles in absorber per event
- LGap : total track length of charged particles in gap per event
And 2 Ntuples :
- Ntuple1:
- one row per event : EnergyAbs EnergyGap
- Ntuple2:
- one row per event : TrackLAbs TrackLGap
These histos and ntuples are booked in HistoManager and filled from
EventAction.
One can control the name of the histograms file :
- default name : AnaEx02
Format : root
See HistoManager constructor
\section AnaEx02_s6 How to build
An additional step is needed when building the example with GNUmake
due to using the extra shared directory:
\verbatim
% cd path_to_AnaEx02/AnaEx02
% gmake setup
% gmake
\endverbatim
This will copy the files from shared in the example include and src;
to remove these files:
\verbatim
% gmake clean_setup
\endverbatim
\section AnaEx02_s8 HOW TO RUN
- Execute AnaEx02 in the 'interactive mode' with visualization
\verbatim
% ./AnaEx02
and type in the commands from run.mac line by line:
Idle> /control/verbose 2
Idle> /tracking/verbose 1
Idle> /run/beamOn 10
Idle> ...
Idle> exit
\endverbatim
or
\verbatim
Idle> /control/execute run.mac
....
Idle> exit
\endverbatim
- Execute AnaEx02 in the 'batch' mode from macro files
(without visualization)
\verbatim
% ./AnaEx02 run.mac
% ./AnaEx02 run.mac > run.out
\endverbatim
The AnaEx02.in macro is used in Geant4 testing.
*/
examples/extended/analysis/AnaEx02/README
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--------------------------------------------------
=========================================================
Geant4 - an Object-Oriented Toolkit for Simulation in HEP
=========================================================
AnaEx02
-------
Examples AnaEx01 and AnaEx02 show the usage of histogram and tuple
manipulations using G4Analysis and ROOT compliant systems on the same
scenario. All analysis manipulations (histo booking, filling, saving histos
in a file, etc...) are located in one class : HistoManager, implementation of
which is different in each example. All the other classes are same in all
three examples.
This example shows the usage of histogram and tuple manipulations using
ROOT system. Please install ROOT before building this example:
http://root.cern.ch
The example is an adaptation of examples/novice/N03. It describes a simple
sampling calorimeter setup.
1- Detector description
-----------------------
The calorimeter is a box made of a given number of layers. A layer
consists of an absorber plate and of a detection gap. The layer is
replicated.
Six parameters define the calorimeter :
- the material of the absorber,
- the thickness of an absorber plate,
- the material of the detection gap,
- the thickness of a gap,
- the number of layers,
- the transverse size of the calorimeter (the input face is a square).
The default geometry is constructed in DetectorConstruction class,
but all of the above parameters can be modified interactively via
the commands defined in the DetectorMessenger class.
|<----layer 0---------->|<----layer 1---------->|<----layer 2---------->|
| | | |
==========================================================================
|| | || | || | ||
|| | || | || | ||
beam || absorber | gap || absorber | gap || absorber | gap ||
======> || | || | || | ||
|| | || | || | ||
==========================================================================
2- Physics list
---------------
The particle's type and the physic processes which will be available
in this example are set in the FTFP_BERT physics list.
3- Action Initialization
------------------------
A newly introduced class, ActionInitialization,
instantiates and registers to Geant4 kernel all user action classes
which are defined thread-local and a run action class
which is defined both thread-local and global.
The thread-local action classes are defined in
ActionInitialization::Build()
and the global run action class is defined in
ActionInitialization::BuildForMaster().
Note that ActionInitialization::Build() is also used to
instatiate user action clasess in sequential mode.
4- An event : PrimaryGeneratorAction
------------------------------------
The primary kinematic consists of a single particle which hits the
calorimeter perpendicular to the input face. The type of the particle
and its energy are set in the PrimaryGeneratorAction class, and can
be changed via the G4 build-in commands of ParticleGun class.
5- Histograms
-------------
To produce histograms, ROOT system must be installed
AnaEx02 can produce 4 histograms :
EAbs : total energy deposit in absorber per event
EGap : total energy deposit in gap per event
LAbs : total track length of charged particles in absorber per event
LGap : total track length of charged particles in gap per event
And 2 Ntuples :
- Ntuple1:
- one row per event : EnergyAbs EnergyGap
- Ntuple2:
- one row per event : TrackLAbs TrackLGap
These histos and ntuples are booked in HistoManager and filled from
EventAction.
One can control the name of the histograms file :
default name : AnaEx02
format : root
See HistoManager constructor
6- How to build
---------------
An additional step is needed when building the example with GNUmake
due to using the extra shared directory:
% cd path_to_AnaEx02/AnaEx02
% gmake setup
% gmake
This will copy the files from shared in the example include and src;
to remove these files:
% gmake clean_setup
7- How to run
--------------
- Execute AnaEx02 in the 'interactive mode' with visualization:
% ./AnaEx02
and type in the commands from run.mac line by line:
Idle> /control/verbose 2
Idle> /tracking/verbose 1
Idle> /run/beamOn 10
Idle> ...
Idle> exit
or
Idle> /control/execute run.mac
....
Idle> exit
- Execute AnaEx02 in the 'batch' mode from macro files
(without visualization)
% ./AnaEx02 run.mac
% ./AnaEx02 run.mac > run.out
The AnaEx02.in macro is used in Geant4 testing.
examples/extended/analysis/B1Con/.README.txt
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///\file "analysis/B1Con/.README.txt"
///\brief Example B1Con README page
/*! \page ExampleB1Con Example B1Con
Example of Convergence Tester
Koi, Tatsumi \n
SLAC National Accelerator Laboratory / PPA \n
tkoi@slac.stanford.eedu \n
This example shows how to use convergece tester in Geant4.
The aim of Convergence Tester
- After a Monte Carlo simulation, we get an answer. However how to estimate quality of the answer.
The answer is usually given in a form of average value.
But sometimes the value is strongly affected by single or a few events in the full calculation.
In such case, we must concern about quality of the value.
What we must remember is
- Large number of history does not valid result of simulation.
- Small Relative Error does not valid result of simulation
Convergence tester provides statistical information
to assist establishing valid confidence intervals for Monte Carlo results for users.
Geometry and Physics are same to exampleB1. Please see \ref ExampleB1.
Note that in this example, the classes with the code added for
the purpose of demonstration of the Convergence Tester start with a prefix
B1Con instead of B1 and also the executable and the test macro names are changed
in exampleB1Con and exampleB1Con.in.
Known problem:
Computing time of T cannot be gotten properly in current MT migration of example of B1Con. Therefore
FOM (=1/(R^2T) where R is relative error and T is computing time) relates numbers are unusable.
\verbatim
***********************************************************************************************************************
Output example
// Part I.A
// Basic statistics values
G4ConvergenceTester Output Result of DOSE_TALLY
EFFICIENCY = 0.601
MEAN = 4.81721e-12
VAR = 2.15334e-23
SD = 4.64041e-12
R = 0.0304622
SHIFT = 2.22459e-13
VOV = 0.000166754
FOM = 1238.68
// Part I.B
// If the largeset scored events happen at next to the last event,
// then how much the event effects the statistics values of the calculation
THE LARGEST SCORE = 1.07301e-11 and it happend at 487th event
Affected Mean = 4.82311e-12 and its ratio to orignal is 1.00123
Affected VAR = 2.15468e-23 and its ratio to orignal is 1.00062
Affected R = 0.0304192 and its ratio to orignal is 0.998587
Affected SHIFT = 2.1804e-13 and its ratio to orignal is 0.980133
Affected FOM = 1238.68 and its ratio to orignal is 1
// Part I.C
// Convergence tests results
MEAN distribution is RANDOM
r follows 1/std::sqrt(N)
r is monotonically decrease
r is less than 0.1. r = 0.0304622
VOV follows 1/std::sqrt(N)
VOV is monotonically decrease
FOM distribution is not RANDOM
SLOPE is not large enough
This result passes 6 / 8 Convergence Test.
// Part II
// Profile of statistics values in the history
G4ConvergenceTester Output History of DOSE_TALLY
i/16 till_ith mean var sd r vov fom shift e r2eff r2int
1 62 4.94618e-12 2.04631e-23 4.52362e-12 0.115225 0.00313634 86.5745 -1.73435e-14 0.619048 0.00976801 0.00329797
2 124 4.69364e-12 2.10698e-23 4.59018e-12 0.0874712 0.001597 150.228 3.11143e-13 0.6 0.00533333 0.00225666
3 187 4.72161e-12 2.14009e-23 4.62612e-12 0.0714575 0.00101852 225.105 3.1009e-13 0.590426 0.00368986 0.00138916
4 249 4.95617e-12 2.13982e-23 4.62582e-12 0.0590299 0.000690138 329.865 9.71971e-14 0.62 0.00245161 0.00101898
5 312 4.8529e-12 2.13482e-23 4.62041e-12 0.0538155 0.000573301 396.887 1.95662e-13 0.607029 0.00206827 0.000818582
6 374 5.14255e-12 2.15736e-23 4.64474e-12 0.046641 0.000432121 528.379 -6.42963e-14 0.637333 0.00151743 0.000652145
7 437 5.03849e-12 2.13484e-23 4.62043e-12 0.0438173 0.000379317 598.673 2.54207e-14 0.636986 0.00130112 0.000614447
8 499 4.96962e-12 2.1429e-23 4.62914e-12 0.0416574 0.000329007 662.364 9.27708e-14 0.63 0.0011746 0.000557264
9 562 4.91513e-12 2.14709e-23 4.63367e-12 0.0397316 0.000285324 728.13 1.33544e-13 0.623446 0.0010728 0.000502991
10 624 4.82995e-12 2.13825e-23 4.62412e-12 0.0382954 0.000272664 783.766 2.19101e-13 0.616 0.000997403 0.000466792
11 687 4.79197e-12 2.13975e-23 4.62574e-12 0.0368022 0.000251788 848.661 2.48547e-13 0.606105 0.000944593 0.000407838
12 749 4.77183e-12 2.15116e-23 4.63807e-12 0.0354912 0.000227501 912.513 2.6728e-13 0.601333 0.000883962 0.000373986
13 812 4.76087e-12 2.14479e-23 4.63119e-12 0.0341162 0.000212259 987.548 2.70437e-13 0.597786 0.000827601 0.000334885
14 874 4.81359e-12 2.13296e-23 4.6184e-12 0.0324353 0.0001976 1092.56 2.14521e-13 0.603429 0.000751082 0.000299767
15 937 4.82018e-12 2.14558e-23 4.63204e-12 0.0313767 0.000181379 1167.52 2.18545e-13 0.601279 0.000706952 0.000276498
16 999 4.81721e-12 2.15334e-23 4.64041e-12 0.0304622 0.000166754 1238.68 2.22459e-13 0.601 0.000663894 0.000263125
**************************************************************************************************************************
\endverbatim
Reference of this Convergence tests: \n
MCNP(TM) -A General Monte Carlo N-Particle Transport Code \n
Version 4B \n
Judith F. Briesmeister, Editor \n
LA-12625-M, Issued: March 1997, UC 705 and UC 700 \n
CHAPTER 2. GEOMETRY, DATA, PHYSICS, AND MATHEMATICS \n
VI. ESTIMATION OF THE MONTE CARLO PRECISION \n
*/
examples/extended/analysis/B1Con/README
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Example of Convergence Tester
Koi, Tatsumi
SLAC National Accelerator Laboratory / PPA
tkoi@slac.stanford.eedu
This example shows how to use convergece tester in Geant4.
The aim of Convergence Tester
After a Monte Carlo simulation, we get an answer. However how to estimate quality of the answer.
The answer is usually given in a form of average value.
But sometimes the value is strongly affected by single or a few events in the full calculation.
In such case, we must concern about quality of the value.
What we must remember is
Large number of history does not valid result of simulation.
Small Relative Error does not valid result of simulation
Convergence tester provides statistical information
to assist establishing valid confidence intervals for Monte Carlo results for users.
Geometry and Physics are same to exampleB1. Please see README.B1
Note that in this example, the classes with the code added for
the purpose of demonstration of the Convergence Tester start with a prefix
B1Con instead of B1 and also the executable and the test macro names are changed
in exampleB1Con and exampleB1Con.in.
Known problem:
Computing time of T cannot be gotten properly in current MT migration of example of B1Con. Therefore
FOM (=1/(R^2T) where R is relative error and T is computing time) relates numbers are unusable.
***********************************************************************************************************************
Output example
// Part I.A
// Basic statistics values
G4ConvergenceTester Output Result of DOSE_TALLY
EFFICIENCY = 0.601
MEAN = 4.81721e-12
VAR = 2.15334e-23
SD = 4.64041e-12
R = 0.0304622
SHIFT = 2.22459e-13
VOV = 0.000166754
FOM = 1238.68
// Part I.B
// If the largeset scored events happen at next to the last event,
// then how much the event effects the statistics values of the calculation
THE LARGEST SCORE = 1.07301e-11 and it happend at 487th event
Affected Mean = 4.82311e-12 and its ratio to orignal is 1.00123
Affected VAR = 2.15468e-23 and its ratio to orignal is 1.00062
Affected R = 0.0304192 and its ratio to orignal is 0.998587
Affected SHIFT = 2.1804e-13 and its ratio to orignal is 0.980133
Affected FOM = 1238.68 and its ratio to orignal is 1
// Part I.C
// Convergence tests results
MEAN distribution is RANDOM
r follows 1/std::sqrt(N)
r is monotonically decrease
r is less than 0.1. r = 0.0304622
VOV follows 1/std::sqrt(N)
VOV is monotonically decrease
FOM distribution is not RANDOM
SLOPE is not large enough
This result passes 6 / 8 Convergence Test.
// Part II
// Profile of statistics values in the history
G4ConvergenceTester Output History of DOSE_TALLY
i/16 till_ith mean var sd r vov fom shift e r2eff r2int
1 62 4.94618e-12 2.04631e-23 4.52362e-12 0.115225 0.00313634 86.5745 -1.73435e-14 0.619048 0.00976801 0.00329797
2 124 4.69364e-12 2.10698e-23 4.59018e-12 0.0874712 0.001597 150.228 3.11143e-13 0.6 0.00533333 0.00225666
3 187 4.72161e-12 2.14009e-23 4.62612e-12 0.0714575 0.00101852 225.105 3.1009e-13 0.590426 0.00368986 0.00138916
4 249 4.95617e-12 2.13982e-23 4.62582e-12 0.0590299 0.000690138 329.865 9.71971e-14 0.62 0.00245161 0.00101898
5 312 4.8529e-12 2.13482e-23 4.62041e-12 0.0538155 0.000573301 396.887 1.95662e-13 0.607029 0.00206827 0.000818582
6 374 5.14255e-12 2.15736e-23 4.64474e-12 0.046641 0.000432121 528.379 -6.42963e-14 0.637333 0.00151743 0.000652145
7 437 5.03849e-12 2.13484e-23 4.62043e-12 0.0438173 0.000379317 598.673 2.54207e-14 0.636986 0.00130112 0.000614447
8 499 4.96962e-12 2.1429e-23 4.62914e-12 0.0416574 0.000329007 662.364 9.27708e-14 0.63 0.0011746 0.000557264
9 562 4.91513e-12 2.14709e-23 4.63367e-12 0.0397316 0.000285324 728.13 1.33544e-13 0.623446 0.0010728 0.000502991
10 624 4.82995e-12 2.13825e-23 4.62412e-12 0.0382954 0.000272664 783.766 2.19101e-13 0.616 0.000997403 0.000466792
11 687 4.79197e-12 2.13975e-23 4.62574e-12 0.0368022 0.000251788 848.661 2.48547e-13 0.606105 0.000944593 0.000407838
12 749 4.77183e-12 2.15116e-23 4.63807e-12 0.0354912 0.000227501 912.513 2.6728e-13 0.601333 0.000883962 0.000373986
13 812 4.76087e-12 2.14479e-23 4.63119e-12 0.0341162 0.000212259 987.548 2.70437e-13 0.597786 0.000827601 0.000334885
14 874 4.81359e-12 2.13296e-23 4.6184e-12 0.0324353 0.0001976 1092.56 2.14521e-13 0.603429 0.000751082 0.000299767
15 937 4.82018e-12 2.14558e-23 4.63204e-12 0.0313767 0.000181379 1167.52 2.18545e-13 0.601279 0.000706952 0.000276498
16 999 4.81721e-12 2.15334e-23 4.64041e-12 0.0304622 0.000166754 1238.68 2.22459e-13 0.601 0.000663894 0.000263125
**************************************************************************************************************************
Reference of this Convergence tests
MCNP(TM) -A General Monte Carlo N-Particle Transport Code
Version 4B
Judith F. Briesmeister, Editor
LA-12625-M, Issued: March 1997, UC 705 and UC 700
CHAPTER 2. GEOMETRY, DATA, PHYSICS, AND MATHEMATICS
VI. ESTIMATION OF THE MONTE CARLO PRECISION
examples/extended/analysis/B1Con/README.B1
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-------------------------------------------------------------------
=========================================================
Geant4 - an Object-Oriented Toolkit for Simulation in HEP
=========================================================
Example B1
-----------
This example demonstrates a very simple application where an energy
deposit is accounted in user actions and their associated objects
and a dose in a selected volume is calculated.
1- GEOMETRY DEFINITION
The geometry is constructed in the B1DetectorConstruction class.
The setup consists of a an envelope of box shape containing two
volumes: a spherical cone and a trapezoid.
In this example we use some common materials materials for medical
applications. The envelope is made of water and the two inner volumes
are made from tissue and bone materials.
The materials are created with the help of the G4NistManager class,
which allows to build a material from the NIST database using their
names. All available materials can be found in the Geant4 User's Guide
for Application Developers, Appendix 10: Geant4 Materials Database.
2- PHYSICS LIST
The particle's type and the physic processes which will be available
in this example are set in the QBBC physics list. This physics list
requires data files for electromagnetic and hadronic processes.
See more on installation of the datasets in Geant4 Installation Guide,
Chapter 3.3: Note On Geant4 Datasets:
http://geant4.web.cern.ch/geant4/UserDocumentation/UsersGuides
/InstallationGuide/html/ch03s03.html
The following datasets: G4LEDATA, G4LEVELGAMMADATA, G4NEUTRONXSDATA and
G4SAIDXSDATA are mandatory for this example.
In addition the build-in interactive command:
/process/(in)activate processName
allows to activate/inactivate the processes one by one.
3- ACTION INITALIZATION
A newly introduced class, B1ActionInitialization, instantiates and registers
to Geant4 kernel all user action classes.
While in sequential mode the action classes are instatiated just once,
via invoking the method:
B1ActionInitialization::Build()
in multi-threading mode the same method is invoked for each thread worker
and so all user action classes are defined thread-local.
A run action class is instantiated both thread-local
and global that's why its instance has is created also in the method
B1ActionInitialization::BuildForMaster()
which is invoked only in multi-threading mode.
4- PRIMARY GENERATOR
The primary generator is defined in the B1PrimaryGeneratorAction class.
The default kinematics is a 6 MeV gamma, randomly distributed in front
of the envelope across 80% of the transverse (X,Y) envelope size.
This default setting can be changed via the Geant4 built-in commands
of the G4ParticleGun class.
5- DETECTOR RESPONSE
This example demonstrates a simple scoring implemented directly
in the user action classes and B1Run object.
Alternative ways of scoring via Geant4 classes can be found in the
other examples.
The energy deposited is collected step by step for a selected volume
in B1SteppingAction and accumulated event by event in B1EventAction.
At end of event, the value acummulated in B1EventAction is added in B1Run
and summed over the whole run (see B1EventAction::EndOfevent()).
Total dose deposited is computed at B1RunAction::EndOfRunAction(),
and printed together with informations about the primary particle.
In multi-threading mode the energy accumulated in B1Run objects per
workers is merged to the master in B1Run::Merge() and the final
result is printed on the screen.
An example of creating and computing new units (e.g., dose) is also shown
in the class constructor.
The following paragraphs are common to all basic examples
A- VISUALISATION
The visualization manager is set via the G4VisExecutive class
in the main() function in exampleB1.cc.
The initialisation of the drawing is done via a set of /vis/ commands
in the macro vis.mac. This macro is automatically read from
the main function when the example is used in interactive running mode.
By default, vis.mac opens an OpenGL viewer (/vis/open OGL).
The user can change the initial viewer by commenting out this line
and instead uncommenting one of the other /vis/open statements, such as
HepRepFile or DAWNFILE (which produce files that can be viewed with the
HepRApp and DAWN viewers, respectively). Note that one can always
open new viewers at any time from the command line. For example, if
you already have a view in, say, an OpenGL window with a name
"viewer-0", then
/vis/open DAWNFILE
then to get the same view
/vis/viewer/copyView viewer-0
or to get the same view *plus* scene-modifications
/vis/viewer/set/all viewer-0
then to see the result
/vis/viewer/flush
The DAWNFILE, HepRepFile drivers are always available
(since they require no external libraries), but the OGL driver requires
that the Geant4 libraries have been built with the OpenGL option.
From Release 9.6 the vis.mac macro in example B1 has additional commands
that demonstrate additional functionality of the vis system, such as
displaying text, axes, scales, date, logo and shows how to change
viewpoint and style. Consider copying these to other examples or
your application. To see even more commands use help or
ls or browse the available UI commands in the Application
Developers Guide, Section 7.1.
For more information on visualization, including information on how to
install and run DAWN, OpenGL and HepRApp, see the visualization tutorials,
for example,
http://geant4.slac.stanford.edu/Presentations/vis/G4[VIS]Tutorial/G4[VIS]Tutorial.html
(where [VIS] can be replaced by DAWN, OpenGL and HepRApp)
The tracks are automatically drawn at the end of each event, accumulated
for all events and erased at the beginning of the next run.
B- USER INTERFACES
The user command interface is set via the G4UIExecutive class
in the main() function in exampleB1.cc
The selection of the user command interface is then done automatically
according to the Geant4 configuration or it can be done explicitly via
the third argument of the G4UIExecutive constructor (see exampleB4a.cc).
C- HOW TO RUN
- Execute exampleB1 in the 'interactive mode' with visualization:
% ./exampleB1
and type in the commands from run1.mac line by line:
Idle> /control/verbose 2
Idle> /tracking/verbose 1
Idle> /run/beamOn 10
Idle> ...
Idle> exit
or
Idle> /control/execute run1.mac
....
Idle> exit
- Execute exampleB1 in the 'batch' mode from macro files
(without visualization)
% ./exampleB1 run2.mac
% ./exampleB1 exampleB1.in > exampleB1.out
examples/extended/analysis/README
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Geant4 extended examples - analysis
-----------------------------------
Examples in this directory demonstrate how to make histograms and ntuples
AnaEx01
--------
Simple example showing use of g4tools.
AnaEx02
--------
As AnaEx01, but direct interface to ROOT.
B1Con
------
B1Con shows how to use the statistical tool G4ConvergenceTester.
It does not make histograms.
It has the same geometry as B1.