PySDD
Python package for Sentential Decision Diagrams (SDD)
Install / Use
/learn @ML-KULeuven/PySDDREADME
===== PySDD
Python wrapper package to interactively use Sentential Decision Diagrams (SDD) <http://reasoning.cs.ucla.edu/sdd/>_.
Full documentation available on http://pysdd.readthedocs.io.
Installation
.. code-block:: shell
$ 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.
.. code-block:: python
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:
.. image:: https://people.cs.kuleuven.be/wannes.meert/pysdd/sdd.png .. image:: 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 <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)
.. code-block:: shell
$ 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 <https://cython.readthedocs.io/en/latest/src/quickstart/install.html>_) - 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:
.. code-block:: shell
$ pip install build $ python -m build
To install the main branch:
.. code-block:: shell
$ 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 <https://dtai.cs.kuleuven.be/problog/>_.
References:
- Wannes Meert & Arthur Choi, PySDD,
in
Recent Trends in Knowledge Compilation <http://drops.dagstuhl.de/opus/volltexte/2018/8589/pdf/dagrep_v007_i009_p062_17381.pdf>_, Report from Dagstuhl Seminar 17381, Sep 2017. Eds. A. Darwiche, P. Marquis, D. Suciu, S. Szeider.
Other languages:
- C: http://reasoning.cs.ucla.edu/sdd/
- Java: https://github.com/jessa/JSDD
Contact
- Wannes Meert, KU Leuven, https://people.cs.kuleuven.be/wannes.meert
- Arthur Choi, UCLA, http://web.cs.ucla.edu/~aychoi/
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.
