accelduck

Docker container based on debian providing a debian linux environment for the developement and usage of code for accelerator pyhsics - start working on your actual problems in minutes

Getting Started

Prerequisites

• Install and setup Docker CE
• Install git

  >>  apt-get install git

Installation

• get your local copy of this git repository

  >> git clone git@github.com:farmborst/accelduck.git

• download required accelerator software to the directory "3rdparty"
• comment other proprietary software in the Dockerfile
• build the docker image

  >> docker build . -t debianstretch:accelduck

Usage

• make runfile executable

  >> chmod +x run 

• run the docker image

  >> ./run

• activate the python 3 virtualenv

  >> source /opt/python/venv_python3.5.3/bin/activate

• start JupyterLab

>> jupyter-lab --notebook-dir=/mnt/dockershare/ --no-browser --NotebookApp.token='yourpassword' 

• access jupyter lab from the webbrowser of your host machine and start working...

  >> localhost:8888

Distribution of the created Docker Image to colleagues (skip download heavy build process)

• Save the Docker image existing in your local Docker registry after the installation procedure.

  >> docker save -o accelduck.tar debian:stretch_accelduck

• Copy the created tar file and the runfile to your colleagues machine
• Add the Docker image built on your machine to your colleagues local repository

  >> docker load -i accelduck.tar

• Follow Usage Instructions

included opensource tools

accelerator specific

• accpy
• ocelot

  generic

• jupyter-lab
• python 2.7
• python 3.5
• numpy
• scipy
• pandas
• tensorflow
• octave
• mayavi
• vtk
• blender
• julia

tested but proprietary tools

accelerator specific

• elegant
• mad-x
• femm
• pyepics
• epics

  generic

• matlab
• mathematica

Authors

• Felix Armborst - Initial Work

License

This project is licensed under the copyleft GNU GENERAL PUBLIC LICENSE Version 3 - see the LICENSE.md file for details