OCELOT是一个多物理场仿真工具包，专为研究FEL和.zip

Accelerator, radiation and x-ray optics simulation framework # An Introduction to Ocelot Ocelot is a multiphysics simulation toolkit designed for studying FEL and storage ring-based light sources. Ocelot is written in Python. Its central concept is the writing of python's scripts for simulations with the usage of Ocelot's modules and functions and the standard Python libraries. Ocelot includes following main modules: * **Charged particle beam dynamics module (CPBD)** - optics - tracking - matching - collective effects (description can be found [here](http://vrws.de/ipac2017/papers/wepab031.pdf) and [here](https://journals.aps.org/prab/abstract/10.1103/PhysRevAccelBeams.22.024401)) - Space Charge (3D Laplace solver) - CSR (Coherent Synchrotron Radiation) (1D model with arbitrary number of dipoles). - Wakefields (Taylor expansion up to second order for arbitrary geometry). - MOGA (Multi Objective Genetics Algorithm) [ref](http://accelconf.web.cern.ch/AccelConf/ipac2016/papers/thpmb034.pdf). * **Native module for spontaneous radiation calculation** (some details can be found [here](http://accelconf.web.cern.ch/AccelConf/ipac2019/papers/wepts017.pdf) and [here](http://scripts.iucr.org/cgi-bin/paper?S1600577519002509)) * **FEL calculations: interface to GENESIS and pre/post-processing** * **Modules for online beam control and online optimization of accelerator performances.** [ref1](http://accelconf.web.cern.ch/accelconf/IPAC2014/papers/mopro086.pdf), [ref2](https://jacowfs.jlab.org/conf/y15/ipac15/prepress/TUPWA037.PDF), [ref3](http://accelconf.web.cern.ch/AccelConf/ipac2016/papers/wepoy036.pdf), [ref4](https://arxiv.org/pdf/1704.02335.pdf). - This module is being developed in collaboration with other accelerator groups. The module has been migrated to a separate [repository](https://github.com/ocelot-collab/optimizer) (in [ocelot-collab](https://github.com/ocelot-collab) organization) for ease of collaborative development. Ocelot extensively uses Python's [NumPy (Numerical Python)](http://numpy.org) and [SciPy (Scientific Python)](http://scipy.org) 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](http://matplotlib.org/index.html) library is used. It is an open source project and it is being developed by physicists from [The European XFEL](http://www.xfel.eu/), [DESY](http://www.desy.de/) (Germany), [NRC Kurchatov Institute](http://www.nrcki.ru/) (Russia). We still have no documentation but you can find a lot of examples in /demos/ folder including this tutorial ## Ocelot user profile Ocelot is designed for researchers who want to have the flexibility that is given by high-level languages such as Matlab, Python (with Numpy and SciPy) or Mathematica. However if someone needs a GUI it can be developed using Python's libraries like a [PyQtGraph](http://www.pyqtgraph.org/) or [PyQt](http://pyqt.sourceforge.net/Docs/PyQt4/). ## Preliminaries The tutorial includes 9 examples dedicated to the beam dynamics and optics and 5 to Photon Field Simulation. However, you should have a basic understanding of Computer Programming terminologies. A basic understanding of Python language is a plus. ##### This tutorial requires the following packages: - Python 3.6 - 3.8 - `numpy` version 1.8 or later: http://www.numpy.org/ - `scipy` version 0.15 or later: http://www.scipy.org/ - `matplotlib` version 1.5 or later: http://matplotlib.org/ - `ipython` version 2.4 or later, with notebook support: http://ipython.org **Optional**, but highly recommended for speeding up calculations - numexpr (version 2.6.1) - pyfftw (version 0.10) - numba **Orbit Correction module** - pandas The easiest way to get these is to download and install the (large) [Anaconda software distribution](https://www.continuum.io/). Alternatively, you can download and install [miniconda](https://docs.conda.io/en/latest/miniconda.html). The following command will install all required packages: ``` $ conda install numpy scipy matplotlib jupyter ``` ## Ocelot installation ##### Anaconda Cloud **recommended** The easiest way to install OCELOT is to use Anaconda cloud. In that case use command: ``` $ conda install -c ocelot-collab ocelot ``` ##### GitHub Clone OCELOT from GitHub: ``` $ git clone https://github.com/ocelot-collab/ocelot.git ``` or download last release [zip file](https://github.com/ocelot-collab/ocelot/archive/v18.02.0.zip). Now you can install OCELOT from the source: ``` $ python setup.py install ``` ##### PythonPath Another way is download ocelot from [GitHub](https://github.com/ocelot-collab/ocelot) 1. you have to download from GitHub [zip file](https://github.com/ocelot-collab/ocelot/archive/master.zip). 2. Unzip ocelot-master.zip to your working folder **/your_working_dir/**. 3. 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/ - Linux: ``` $ export PYTHONPATH=/your_working_dir/ocelot-master:$PYTHONPATH ``` #### To launch "ipython notebook" or "jupyter notebook" in command line run following commands: ``` $ ipython notebook ``` or ``` $ ipython notebook --notebook-dir="path_to_your_directory" ``` or ``` $ jupyter notebook --notebook-dir="path_to_your_directory" ``` #### OCELOT jupyter tutorials You can download OCELOT jupyter tutorials (release v18.02) using GitHub link [zip file](https://github.com/ocelot-collab/ocelot/releases/download/v18.02.0/ocelot_jupyter_tutorial.zip). ## Tutorials * Preliminaries: Setup & introduction #### Beam dynamics * [Introduction. Tutorial N1. Linear optics](http://nbviewer.jupyter.org/github/ocelot-collab/ocelot/blob/master/demos/ipython_tutorials/1_introduction.ipynb) - Linear optics. Double Bend Achromat (DBA). Simple example of usage OCELOT functions to get periodic solution for a storage ring cell. * [Tutorial N2. Tracking](http://nbviewer.jupyter.org/github/ocelot-collab/ocelot/blob/master/demos/ipython_tutorials/2_tracking.ipynb) - Linear optics of the European XFEL Injector. - Tracking. First and second order. - Artificial beam matching - BeamTransform * [Tutorial N3. Space Charge](http://nbviewer.jupyter.org/github/ocelot-collab/ocelot/blob/master/demos/ipython_tutorials/3_space_charge.ipynb) - Tracking through RF cavities with SC effects and RF focusing. * [Tutorial N4. Wakefields](http://nbviewer.jupyter.org/github/ocelot-collab/ocelot/blob/master/demos/ipython_tutorials/4_wake.ipynb) - Tracking through corrugated structure (energy chirper) with Wakefields * [Tutorial N5. CSR](http://nbviewer.jupyter.org/github/ocelot-collab/ocelot/blob/master/demos/ipython_tutorials/5_CSR.ipynb) - Tracking trough bunch compressor with CSR effect. * [Tutorial N6. RF Coupler Kick](http://nbviewer.jupyter.org/github/ocelot-collab/ocelot/blob/master/demos/ipython_tutorials/6_coupler_kick.ipynb) - Coupler Kick. Example of RF coupler kick influence on trajjectory and optics. * [Tutorial N7. Lattice design](http://nbviewer.jupyter.org/github/ocelot-collab/ocelot/blob/master/demos/ipython_tutorials/7_lattice_design.ipynb) - Lattice design, twiss matching, twiss backtracking * [Tutorial N8. Physics process addition. Laser heater](http://nbviewer.jupyter.org/github/ocelot-collab/ocelot/blob/master/demos/ipython_tutorials/8_laser_heater.ipynb) - Theory of Laser Heater, implementation of new Physics Process, track particles w/o laser heater effect. * [Tutorial N9. Simple accelerator based THz source](http://nbviewer.ju