PSIPositronProduction

This repository collects the codes (Python, Matlab, ...) developed in relation to the PSI Positron Production (P-cubed) Project. Most of the codes have been developed to

run simulations and
analyze and publish the related results.

Getting started

Clone the repository

Warning In addition to a common installation of Git, you also need Git Large File Storage in order to download the large data files (usually compressed as .tar.xz) in the subfolder GIT_PSIPositronProduction/Data. Important: Execute the git-lfs installer as administrator.

If you have no github.com account yet and you only want to download the code, execute the following command in a shell (Git Bash in Windows):

$ git clone https://github.com/paulscherrerinstitute/PSIPositronProduction.git GIT_PSIPositronProduction

If you already have an account and an SSH key set up, run:

$ git clone git@github.com:paulscherrerinstitute/PSIPositronProduction.git GIT_PSIPositronProduction

In this documentation, we indicate the root folder of the repository with GIT_PSIPositronProduction.

Initial configuration of the repository

Some environment variables must be set:

P3_REPO
PYTHONPATH
JUPYTER_PATH

Follow the procedure for your operating system.

Linux

To temporarily set the environment variables:

$ cd GIT_PSIPositronProduction/RepoSetup
$ source Set_EnvVariables_Linux.sh

To permanently set the environment variables (recommended), add the following line to your ~/.bashrc file:

$ source PSIPositronProduction/RepoSetup/Set_EnvVariables_Linux.sh

Windows

Surf to PSIPositronProduction/RepoSetup and execute the batch script Set_EnvVariables_Windows.bat by double-clicking it.

Warning This batch script does not check whether the desired paths are already present in the environment variables. Paths might be inserted multiple times in the same environment variable (should not be a problem). To avoid duplications, check the environment variables first:

$ set

Note It is a good practice to also do this after execution of the script. Important: open a NEW command window!

Prerequisites

For the analysis of simulation results

Python3 and
Jupyter lab (or Jupyter notebooks)

The latest versions can be easily installed with conda (use Anaconda on Windows). A conda environment file is available at GIT_PSIPositronProduction/RepoSetup/Conda/JupyterNb.yml. In a shell (Anaconda prompt in Windows) execute:

$ cd GIT_PSIPositronProduction/RepoSetup/Conda
$ conda env create -f JupyterNb.yml

Note In Windows, this can also be done from the Anaconda Navigator GUI, following the procedure under Environments > Import.

For more details, see:

https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-from-an-environment-yml-file

To build Geant4 simulations

Geant4, version 10.04.p03

See How to build Geant4 on PSI RHEL7.

To edit codes with VSCode

The installation of VSCode on Linux or Windows is generally very simple.

This is not true if you are running a PSI RHEL7 Linux system. See How to build VSCode from source on PSI RHEL7 if you want (try) to keep going with VSCode on RHEL7...

Features

Jupyter notebooks (.ipynb)

To run an analysis:

Open the Jupyter notebook in JupyterLab (recommended) or JupyterNotebook.
Check which data files are required by the analysis and make sure that all necessary .tar.xz files stored in GIT_PSIPositronProduction/Data have been decompressed (usually to a .dat file).
In the menu: Run > Run All Cells.
Wait for the evaluation up to the last cell.

FCCeeInjectorBeamApp

Use it directly through

Geant4 simulations

FCC-ee Target Tracking (reference example)

RF-Track simulations

(To be documented)

Elegant simulations

(To be documented)

ASTRA simulations

(to be documented)

Code documentation

(To-do)

Unit testing

(To-do)

Contributing

Create your own branch and start contributing:

$ git checkout -b MyBranch

Please contact mattia.schaer@psi.ch to discuss the details.

Deploying / Publishing

No active pipeline and no Git Pages at the moment.