GAMOS 5.1.0 User's Guide

GAMOS Collaboration

Version: 5.1.0

Table of Contents

Introduction

About this document
Introduction to GAMOS
Structure of GAMOS
The plug-in concept

Getting started

Getting the code and installing it

Installing in Linux and Mac OS
Installing in Windows

Running an example in Linux or Mac OS

Running an example in Windows

Compiling GAMOS

Compiling your new code

Geometry

Building your geometry with a text file

Description of geometry text file format
Dumping your Geant4 geometry in text file format
Adding new tags to your input text file
Parallel geometries

Building simple geometries

Building a simple geometry with one material

Building your geometry with C++ code

Reading DICOM files

Converting DICOM files to simulation files
DICOM file format
Reading a DICOM file in a GAMOS job
Reading DICOM CT structures
Managing RT plan data
Partial phantom geometries
Utilities to check and draw DICOM files
Simple phantom geometries
Setting off visualization of phantom geometries

Movements

Movement description from a file

Geometry utilities

Commands to print geometrical objects
C++ utilities

Magnetic and electric fields

Uniform magnetic and electric fields
Non uniform magnetic fields

Generator

Using GAMOS generator

Introduction
Particle sources
Distributions

Reading your generator particles from a text file

Reading your generator particles from a binary file

Event generator changing energy and material

Event generator histograms

Biasing generator distributions

Building your generator with C++

Using ions

Physics

GAMOS electromagnetic physics lists

Basic electromagnetic physics list
GAMOS electromagnetic extended physics list
Standard electromagnetic physics list options
Multiple scattering models
Bremsstrahlung angular distributions

GAMOS hadrontherapy physics list

Microdosimetry physics list

Other physics lists

Optical photons

Using optical photons as primary generator

X-ray refraction

Coulomb scattering

Atomic deexcitation processes

Decay process

Radioactive decay process

Cerenkov process

Coulomb scattering

Nuclear processes of electromagnetic particles

Replacing process models

Replacing a set process models
Replacing one process model

Removing a process from a physics list

Production cuts

Production cuts by region
Energy cuts to range cuts conversion
Minimum and maximum production cuts
Apply cuts for all processes

User limits

Automatic optimisation of cuts

Range rejection

Building your physics list with C++ code

User Actions

Adding a filter
Adding a classifier
User action name
Creating your GAMOS user action

Sensitive Detector and Hits

Sensitive detectors

Attaching a sensitive detector to a volume
Building your sensitive detector with C++ code

Hits

Hits digitization and reconstruction

Hits digitization
Hits and digits reconstruction
Examples of reconstructed hit builders

Detector effects

Energy resolution
Time resolution
Detector measuring time
Detector dead time
Minimum hit energy

Identifying each sensitive detector copy

Storing and retrieving hits

File format
Storing reconstructed hits

Hits histograms

Scoring

Creating a scorer

Scorer classes

Scoring in voxelised phantoms

Filter classes

Scorer printers

Classifiers

Multiplying by data

Multiplying by distribution

Convergence testing

Point detector scorer

Theoretical basis
GAMOS implementation
Variance reduction techniques
Sum scoring results and plot them

Variance reduction techniques

Introduction

Importance sampling

Geometrical biasing

Biasing operations

Cross section biasing
Force collision
Uniform bremsstrahlung splitting
Directional bremsstrahlung splitting
Equal weight particle splitting

Histogramming

Histogram formats

Histograms in CSV format

Changing histogram minimum, maximum and number of bins

Histograms name separator

Output files name

Analysing your histograms with ROOT

Printing the histograms in graphics files
Comparing histograms in two files

Creating your own histogram

Analysis (extracting data)

Introduction: GAMOS data

Data users

Behaviour as a function of information object
Behaviour as a function of output format
Selection of data list for a data user
Saving GAMOS data in a ROOT TTree
Filter from data
Classifier by data
Primitive scorer from data

List of available data

Position
Direction
Momentum
Energy
Geometrical objects
Material variables
Particle and process
Secondary tracks
Ancestor data
Others

Output file names

Merging results from different jobs

Example of Analysing text output files

Filters

Introduction
Simple filters
Volume filters
Filters of filters
Applying filters to a user action
Checking filters at a user action
Filtering steps in the future

Classifiers

Introduction
Setting indices to classifiers
Classifiying on secondary data

Distributions

Introduction

Creating a distribution

Assigning a GAMOS data

Reading values from a file

Numeric distributions

String distributions

String data distribution
Geometrical biasing distribution

Ratio of distributions

Utility user actions

Counting the number of tracks and events
Counting the processes
Shower shape studies
Killing all tracks
Table of tracks and steps
Material budget studies
Detailed report of where CPU time is spent
Changing the weight using a distribution
Copying the weight to the secondary particles
Stop run after a certain CPU time
Visualising only a set of events
Setting the correlation between the gammas of a radioactive decay chain
Printing electromagnetic parameters

Managing the verbosity

GAMOS verbosity managers

Controlling GAMOS verbosity by event

Using a GAMOS verbosity manager in your code

Creating your own verbosity manager

Controlling the Geant4 verbosity by event and track

Dumping the standard output and error in log files

Detector applications

Identifying Compton interactions

Compton studies histograms
Histograms of data about the interactions and the reconstructed hits
Classification of good and bad identification histograms as a function of variable

Histograms of gammas at sensitive detectors

Automatic determination of production cuts for a detector

Automatic determination of user limits for a detector

PET application

PET geometry

PET event classification

PET histograms: event classification

PET output for reconstruction

List-mode binary file
Projection data file

PET histograms: positrons

Detector histograms: distance between two gammas

SPECT application

SPECT event classification
SPECT histograms: event classification
SPECT output for reconstruction

Compton camera application

Compton camera geometry
Compton camera Event Classification
Compton camera histograms: event classification
Compton camera output for reconstruction

Image reconstruction utilities

List-mode to projection data: lm2pd

Summing projection data files: sumProjdata

Analytic image reconstruction: ssrb_fbp

Visualization tools

Stochastic Image Ensemble method

Introduction
Getting Started
Program Parameters and Flags
Analysis

Radiotherapy application

Geometrical modules

JAWS module
MLC module

Using phase spaces

Writing phase spaces
Phase space text file
Phase space histograms
Reading phase spaces
Adding extra information to a phase space
Reusing a particle at a phase space without filling the phase space file

Optimisation of a linac simulation

Cuts optimisation
Electromagnetic parameters optimisation
Particle splitting
Killing particles at big X/Y

Scoring dose in phantom

Saving scores and scores squared in binary file
Saving scores and score errors in text file
Saving scores in histograms

Analysis utilities

Summing phase space files
Making histograms out of a phase space file
Merging 'sqdose' files
Merging '3ddose' files
Making histograms out of a 'sqdose' file
Automatic determination of production cuts for an accelerator simulation
Automatic determination of production cuts for a dose in a phantom simulation
Automatic determination of user limits for an accelerator simulation
Automatic determination of user limits for a dose in phantom simulation

Shielding application

Studying penetration

Activation studies

Sum activation results and plot them

Print channel by channel cross sections

Counting hadronic cross sections

Make histograms of secondary particles from the neutron_hp or particle_hp databases

Print yields of production of secondary particles from charged particles traversing a thich material

Analysis utilities

Summing scoring results
Summing activation results

Optimising the CPU time of your application

Knowing where the time is spent
Production cuts
Killing particles of small energy
Killing particles
Optimising the particle generation
Limiting the number of user actions
Using variance reduction techniques

Extracting detailed information from a MCNP run

Source (primary generator)

Extracting information

Tallying (scoring)

F1 and F2 tallies
F4 tally

Appendix A

Using parameters

Checking the usage of parameters

Managing the input data files

Random number seeds

Setting the initial random number seeds
Restoring the initial random number seeds
Changing the random engine

Sending several jobs in the same machine

Identifying touchables

Using asterisks to get volume, particle and material names

Using particle names

Appendix B: Extending GAMOS functionality with C++ utilities

Converting a Geant4 example into a GAMOS example
Creating your plug-in
Using a parameter in your C++ code
Event classification by interaction types
Structure of GAMOS

Bibliography

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