Paganini

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:

   @inproceedings{paganini,
     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].