paganini is a lightweight python library for tuning multiparametric combinatorial specifications. Installation is easy:

pip install --user paganini
  • [Tutorial]

  • [Documentation]

  • Source code on [Github]

  • If you use paganini or its components for published work, we encourage you to cite the accompanying paper Polynomial tuning of multiparametric combinatorial samplers. You can import the following BibTeX citation:

       title        = {Polynomial tuning of multiparametric combinatorial samplers},
       author       = {Bendkowski, Maciej and Bodini, Olivier and Dovgal, Sergey},
       booktitle    = {2018 Proceedings of the Fifteenth Workshop on Analytic Algorithmics and Combinatorics (ANALCO)},
       pages        = {92--106},
       year         = {2018},
       organization = {SIAM}

Boltzmann Brain

Boltzmann Brain is a Haskell library and standalone application meant for random generation of combinatorial structures. It can be used together with paganini for multiparametric random generation.

  • The input specification format mimics that of Haskell algebraic data types where in addition each type constructor may be annotated with an additional weight parameter. For instance:
    -- Motzkin trees
    MotzkinTree = Leaf
              | Unary MotzkinTree (2) [0.3]
              | Binary MotzkinTree MotzkinTree.
  • In the above example, a MotzkinTree data type is defined. It contains three constructors:

    • a constant Leaf of weight one (default value if not annotated);
    • a unary Unary constructor of weight two, and
    • a binary contructor Binary of default weight one.

    Here, the Unary construct is given weight 2 and a target frequency of 0.3. In consequence, the system is to be tuned such that the Unary node contributes, on average, 30% of the total size of constructed Motzkin trees. It is hence possible to distort the natural frequency of each constructor in the given system.

  • See the source code and installation instructions on [Github]

  • You can find a bunch of combinatorial examples [in another repository].