|corrfunc logo| ======================= Corrfunc Documentation ======================= Corrfunc is a set of high-performance routines to measure clustering statistics. The main features of Corrfunc are: * **Fast** All theory pair-counting is at least an order of magnitude faster than all existing public codes. Particularly suited for MCMC. * **OpenMP Parallel** All pair-counting codes can be done in parallel (with strong scaling efficiency >~ 95% up to 10 cores) * **Python Extensions** Python extensions allow you to do the compute-heavy bits using C while retaining all of the user-friendliness of python. * **Modular** The code is written in a modular fashion and is easily extensible to compute arbitrary clustering statistics. * **Future-proof** As I get access to newer instruction-sets, the codes will get updated to use the latest and greatest CPU features. The source code is publicly available at https://github.com/manodeep/Corrfunc. ********************* Overview of Corrfunc ********************* .. toctree:: :maxdepth: 1 install quickstart modules/index development/index ********* Reference ********* .. toctree:: :maxdepth: 1 api/modules ********************* License and Credits ********************* .. toctree:: :maxdepth: 1 development/contributors development/citing_corrfunc .. |corrfunc logo| image:: corrfunc_logo_320px_240px.png :width: 160 :alt: Corrfunc logo