Metadata-Version: 2.1
Name: pycddlib
Version: 3.0.0b6
Summary: A Python wrapper for cddlib
Author-email: "Matthias C. M. Troffaes" <matthias.troffaes@gmail.com>
Project-URL: Homepage, https://github.com/mcmtroffaes/pycddlib
Project-URL: Documentation, https://pycddlib.readthedocs.io/
Project-URL: Repository, https://github.com/mcmtroffaes/pycddlib.git
Project-URL: Issues, https://github.com/mcmtroffaes/pycddlib/issues
Project-URL: Changelog, https://github.com/mcmtroffaes/pycddlib/blob/develop/CHANGELOG.rst
Keywords: convex, polyhedron, linear programming, double description method
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: GNU General Public License v2 or later (GPLv2+)
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Programming Language :: C
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/x-rst
License-File: LICENSE.md
License-File: AUTHORS
Provides-Extra: test
Requires-Dist: pytest; extra == "test"
Requires-Dist: numpy; extra == "test"
Requires-Dist: mypy; extra == "test"
Requires-Dist: black; extra == "test"
Requires-Dist: isort; extra == "test"
Requires-Dist: flake8; extra == "test"
Provides-Extra: doc
Requires-Dist: sphinx; extra == "doc"

The pycddlib package provides Python bindings for
`cddlib <https://people.inf.ethz.ch/fukudak/cdd_home/>`_,
which is a C implementation of the double description method
for generating all extreme points of a general convex polyhedron
given by a system of linear inequalities.
The library also supports the reverse operation
(i.e. convex hull computation).
This means that one can move back and forth between an
inequality representation and an extreme point
representation of a polyhedron.

The library can also solve a variety of other problems related to linear algebra.
This includes linear programming,
Fourier elimination,
computing ranks,
computing adjacencies and incidences,
and removing redundancies from systems of linear inequalities.

* Download: https://pypi.org/project/pycddlib/#files

* Documentation: https://pycddlib.readthedocs.io/en/latest/

* Development: https://github.com/mcmtroffaes/pycddlib/
