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libsemigroups - Version 2.7.3

Documentation Status Launch Binder https://img.shields.io/conda/dn/conda-forge/libsemigroups

C++ library for semigroups and monoids

What is libsemigroups?

libsemigroups is a C++14 library containing implementations of several algorithms for computing finite, and finitely presented, semigroups and monoids. Namely:

libsemigroups is partly based on Algorithms for computing finite semigroups, Expository Slides, and Semigroupe 2.01 by Jean-Eric Pin.

libsemigroups is used in the Semigroups package for GAP, and it is possible to use libsemigroups directly in Python 3 via the package libsemigroups_pybind11. The development version of libsemigroups is available on github, and some related projects are here.

The main classes in libsemigroups are named after the algorithms they implement; see, for example, libsemigroups::FroidurePin, libsemigroups::Konieczny, libsemigroups::congruence::ToddCoxeter, libsemigroups::fpsemigroup::Kambites, libsemigroups::fpsemigroup::KnuthBendix, and libsemigroups::SchreierSims, libsemigroups::Sims1, or libsemigroups::Stephen.

The implementations in libsemigroups::FroidurePin, libsemigroups::Konieczny, and libsemigroups::SchreierSims are generic and easily adapted to user-defined types.

libsemigroups uses: HPCombi which uses the SSE and AVX instruction sets for very fast manipulation of transformations, partial permutations, permutations, and boolean matrices of small size; catch for tests; fmt for reporting; and eigen for some linear algebra computations.

How to use it

See the documentation https://libsemigroups.readthedocs.io/en/latest/

Installation instructions are here https://libsemigroups.readthedocs.io/en/latest/install.html

Issues

If you find any problems with libsemigroups, or have any suggestions for features that you'd like to see, please use the issue tracker.

Author

James Mitchell ([email protected])

Contributors

Acknowledgements

We acknowledge financial support from the OpenDreamKit Horizon 2020 European Research Infrastructures project (#676541) (primarily for the python bindings).

We thank the Carnegie Trust for the Universities of Scotland for funding the PhD scholarship of Julius Jonušas when he worked on this project.

We thank the Engineering and Physical Sciences Research Council (EPSRC) for funding the PhD scholarships of Michael Young and Finn Smith when they worked on this project (EP/M506631/1, EP/N509759/1).

Packages

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Languages

  • C++ 96.8%
  • M4 1.6%
  • Makefile 0.9%
  • Shell 0.3%
  • Python 0.2%
  • GAP 0.1%
  • Other 0.1%