pyapproxmc 4.1.9

Bindings to ApproxMC, an approximate model counter

pyapproxmc: bindings to the ApproxMC model counter

This directory provides Python bindings to ApproxMC on the C++ level, i.e. when importing pyapproxmc, the ApproxMC counter becomes part of the Python process itself.

Installing

pip install pyapproxmc

Compiling

If you don't want to use the pip package, you can compile it:

apt-get install python-dev
cd python
git clone https://github.com/msoos/cryptominisat
git clone https://github.com/meelgroup/arjun
cd ..
python -m build

You will then find the files under "dist/".

Usage

The pyapproxmc module has one object, Counter that has two functions count and add_clause.

The function add_clause() takes an iterable list of literals such as [1, 2] which represents the truth 1 or 2 = True. For example, add_clause([1]) sets variable 1 to True.

The function count() counts the number of solutions to the system of constraints that have been added with add_clause():

>>> from pyapproxmc import Counter
>>> s = Counter()
>>> s.add_clause([1, 2])
>>> cells, hashes = s.count()
>>> print("There are approx ", cells*2**hashes, " solutions")
There are 55 solutions, approximately

The return value is a tuple of cells and hashes. Which gives how many solutions there are, probabilistically approximately

You can give the following arguments to Counter:

• seed -- sets the random seed
• verbosity -- sets the verbosity of the system (default = 0)
• epsilon -- Tolerance parameter, i.e. sets how approximate the returned count is. Default = 0.8
• delta -- Confidence parameter, i.e. sets how probabilistically correct the returned count is. Default = 0.20