- Authors
Miguel Zumalacarregui, Emilio Bellini
(based on the CLASS code by Julien Lesgourgues, with several major inputs from other people, especially Thomas Tram)
hi_class can be used freely, provided that you cite the CLASS paper and
"hi_class: Horndeski in the Cosmic Linear Anisotropy Solving System" M. Zumalacarregui, E. Bellini, I. Sawicki, J, Lesgourgues
For further information please visit http://hiclass-code.net and http://class-code.net
See also hi_class.ini for details on the available models and features
(the information below can also be found on the CLASS webpage, just below the download button)
After downloading the code, unpack the archive (tar -zxvf class_v*.tar.gz), go to the class directory (cd class_v*/) and compile (make clean; make class). If the first compilation attempt fails, you may need to open the Makefile and adapt the name of the compiler (default: gcc), of the optization flag (default: -O4) and of the OpenMP flag (default: -fopenmp; this flag is facultative, you are free to compile without OpenMP if you don't want parallel execution; note that you need the version 4.2 or higher of gcc to be able to compile with -fopenmp. Several details on the CLASS compilation are given on the wiki page
https://github.com/lesgourg/class_public/wiki/Installation
(in particular, for compiling on Mac 10.9 Mavericks).
To check that the code runs, type:
./class explanatory.ini
The explanatory.ini file is a reference input file, containing and explaning the use of all possible input parameters. We recommend to read it, to keep it unchanged (for future reference), and to create for your own purposes some shorter input files, containing only the input lines which are useful for you. Input files must have a *.ini extension.
If you want to play with the precision/speed of the code, you can use one of the provided precision files (e.g. cl_permille.pre) or modify one of them, and run with two input files, for instance:
./class test.ini cl_permille.pre
A simplified documentation can be found in the paper CLASS I: Overview. On top of that, if you wish to modify the code, you will find lots of comments directly into the files. Other CLASS papers dedicated to various aspects of the code are listed in the CLASS web page. Slides from CLASS-dedicated courses can be seen at
http://lesgourg.web.cern.ch/lesgourg/class-tour/class-tour.html
To use CLASS from python, or ipython notebooks, or from the Monte Python parameter extraction code, you need to compile not only the code, but also its python wrapper. This can be done by typing just 'make' instead of 'make class'. More details on the wrapper and its compilation are found on the wiki page
https://github.com/lesgourg/class_public/wiki
Since version 2.3, the package includes an improved plotting script called CPU.py (Class Plotting Utility), written by Benjamin Audren and Jesus Torrado. It can plot the Cl's, the P(k) or any other CLASS puput, for one or several models, as well as their ratio or percentage difference. The syntax and list of available options is obtained by typing 'pyhton CPU.py --help'. There is a similar script for MATLAB, written by Thomas Tram. To use it, once in MATLAB, type 'help plot_CLASS_output.m'
If you want to develop the code, we suggest that you download it from the github webpage
https://github.com/lesgourg/class_public
rather than from class-code.net. Then you will enjoy all the feature of git repositories. You can even develop your own branch and get it merged to the public distribution. For related instructions, check
https://github.com/lesgourg/class_public/wiki/Public-Contributing
You can use CLASS freely, provided that in your publications, you cite at least the paper CLASS II: Approximation schemes. Feel free to cite more CLASS papers!
To get support, please open a new issue on the
https://github.com/lesgourg/class_public
webpage!