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Sentential Decision Diagrams

Project description

Python wrapper package to interactively use Sentential Decision Diagrams (SDD).

Full documentation available on http://pysdd.readthedocs.io.

Installation

$ pip install PySDD

Python package

The wrapper can be used as a Python package and allows for interactive use.

The following example builds an SDD for the formula a∧b ∨ b∧c ∨ c∧d.

from pysdd.sdd import SddManager, Vtree, WmcManager
vtree = Vtree(var_count=4, var_order=[2,1,4,3], vtree_type="balanced")
sdd = SddManager.from_vtree(vtree)
a, b, c, d = sdd.vars

# Build SDD for formula
formula = (a & b) | (b & c) | (c & d)

# Model Counting
wmc = formula.wmc(log_mode=False)
print(f"Model Count: {wmc.propagate()}")
wmc.set_literal_weight(a, 0.5)
print(f"Weighted Model Count: {wmc.propagate()}")

# Visualize SDD and Vtree
with open("output/sdd.dot", "w") as out:
    print(formula.dot(), file=out)
with open("output/vtree.dot", "w") as out:
    print(vtree.dot(), file=out)

The SDD and Vtree are visualized using Graphviz DOT:

https://people.cs.kuleuven.be/wannes.meert/pysdd/sdd.png https://people.cs.kuleuven.be/wannes.meert/pysdd/vtree.png

More examples are available in the examples directory. An interactive Jupyter notebook is available in notebooks/examples.ipynb

Command Line Interface

A Python CLI application is installed if you use pip, pysdd. Or it can be used directly from the source directory where it is called pysdd-cli.py. This script mimicks the original sdd binary and adds additional features (e.g. weighted model counting)

$ pysdd -h
$ ./pysdd-cli.py -h
usage: pysdd-cli.py [-h] [-c FILE | -d FILE | -s FILE] [-v FILE] [-W FILE]
                [-V FILE] [-R FILE] [-S FILE] [-m] [-t TYPE] [-r K] [-q]
                [-p] [--log_mode]

Sentential Decision Diagram, Compiler

optional arguments:
  -h, --help  show this help message and exit
  -c FILE     set input CNF file
  -d FILE     set input DNF file
  -s FILE     set input SDD file
  -v FILE     set input VTREE file
  -W FILE     set output VTREE file
  -V FILE     set output VTREE (dot) file
  -R FILE     set output SDD file
  -S FILE     set output SDD (dot) file
  -m          minimize the cardinality of compiled sdd
  -t TYPE     set initial vtree type (left/right/vertical/balanced/random)
  -r K        if K>0: invoke vtree search every K clauses. If K=0: disable
              vtree search. By default (no -r option), dynamic vtree search is
              enabled
  -q          perform post-compilation vtree search
  -p          verbose output
  --log_mode  weights in log

Weighted Model Counting is performed if the NNF file containts a line
formatted as follows: "c weights PW_1 NW_1 ... PW_n NW_n".

Memory management

Python’s memory management is not used for the internal datastructures. Use the SDD library’s garbage collection commands (e.g. ref, deref) to perform memory management.

Compilation from source

To install from source, make sure to have the correct development tools installed:

  • C compiler (see Installing Cython)

  • The Python development version that includes Python header files and static library (e.g. libpython3-dev, python-dev, …)

The build process will download Cython and numpy in an isolated environment.

Then run:

$ pip install build
$ python -m build

To install the main branch:

$ pip install git+https://github.com/wannesm/PySDD.git#egg=PySDD

References

This package is inspired by the SDD wrapper used in the probabilistic programming language ProbLog.

References:

Other languages:

Contact

License

Python SDD wrapper:

Copyright 2017-2024, KU Leuven and Regents of the University of California. Licensed under the Apache License, Version 2.0.

SDD package:

Copyright 2013-2018, Regents of the University of California Licensed under the Apache License, Version 2.0.

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