OCELOT is a multiphysics simulation toolkit designed for studying FEL and storage ring-based light sources.
Accelerator, radiation and x-ray optics simulation framework
Ocelot is a multiphysics simulation toolkit designed for studying Free Electron Lasers (FEL) and storage ring-based light sources. Implemented in Python, Ocelot caters to researchers seeking the flexibility provided by high-level languages like Matlab and Python. Its core principle revolves around scripting beam physics simulations in Python, utilizing Ocelot’s modules and extensive collection of Python libraries.
Users developing high-level control applications can accelerate development by using physics models from Ocelot and Python graphics libraries such as PyQt and PyQtGraph to create a GUI.
Developing machine learning (ML) applications for accelerators can also benefit from using Ocelot, as many popular ML frameworks are written in Python. Ocelot provides a seamless connection between physics and ML methods, making it easier to integrate physical accelerator simulators with machine learning algorithms.
Ocelot extensively uses Python’s NumPy (Numerical Python) and SciPy (Scientific Python) libraries, which enable efficient in-core numerical and scientific computation within Python and give you access to various mathematical and optimization techniques and algorithms. To produce high quality figures Python’s matplotlib library is used.
It is an open source project and it is being developed by physicists from The European XFEL, DESY (Germany), NRC Kurchatov Institute (Russia).
We still have no documentation but you can find a lot of examples in /demos/ folder and jupyter tutorials
numpy version 1.8 or higher: http://www.numpy.org/scipy version 0.15 or higher: http://www.scipy.org/matplotlib version 1.5 or higher: http://matplotlib.org/h5py version 3.10 or higher, https://www.h5py.orgOptional, but highly recommended for speeding up calculations
Orbit Correction module is required
pandasClone OCELOT from GitHub:
$ git clone https://github.com/ocelot-collab/ocelot.git
or download last release zip file.
Now you can install OCELOT from the source:
$ python setup.py install
The easiest way to install OCELOT is to use Anaconda cloud. In that case use command:
$ conda install -c ocelot-collab ocelot
Another way is download ocelot from GitHub
Add ../your_working_dir/ocelot-master to PYTHONPATH
Windows 7: go to Control Panel -> System and Security -> System -> Advance System Settings -> Environment Variables.
and in User variables add /your_working_dir/ocelot-master/ to PYTHONPATH. If variable PYTHONPATH does not exist, create it
Variable name: PYTHONPATH
Variable value: ../your_working_dir/ocelot-master/
$ export PYTHONPATH=/your_working_dir/ocelot-master:$PYTHONPATH
If you want to play with these tutorials they can be found in ocelot/demos/ipython_tutorials.
Run the following commands in the command line:
$ ipython notebook
or
jupyter lab
The API documentation can be build using sphinx.
To do so, you have to clone the repository or download the zip file, as explained in the ocelot installation section.
Then you can install all dependencies by running
python -m pip install -r docs/requirements.txtpython setup.py install
Now you can build the documentation by running
python setup.py build_sphinx
If these steps succeeded (yes, there are still very many errors and warnings during building the documentation),
you can browse the HTML documentation by opening build/sphinx/html/index.html in your browser.
Disclaimer: The OCELOT code comes with absolutely NO warranty. The authors of the OCELOT do not take any responsibility for any damage to equipments or personnel injury that may result from the use of the code.