passagemath-polyhedra 10.4.60

passagemath: Convex polyhedra in arbitrary dimension, mixed integer linear optimization

About SageMath

“Creating a Viable Open Source Alternative to

Magma, Maple, Mathematica, and MATLAB”

Copyright (C) 2005-2024 The Sage Development Team

https://www.sagemath.org

SageMath fully supports all major Linux distributions, recent versions of macOS, and Windows (Windows Subsystem for Linux).

See https://doc.sagemath.org/html/en/installation/index.html for general installation instructions.

About this pip-installable source distribution

This pip-installable source distribution passagemath-polyhedra is a distribution of a part of the Sage Library. It provides a small subset of the modules of the Sage library (“sagelib”, passagemath-standard), sufficient for computations with convex polyhedra in arbitrary dimension (in exact rational arithmetic), and linear and mixed integer linear optimization (in floating point arithmetic).

What is included

• Combinatorial and Discrete Geometry: Polyhedra, lattice polyhedra, lattice points in polyhedra, triangulations, fans, polyhedral complexes, hyperplane arrrangements

• Parma Polyhedra Library (PPL) backends for rational polyhedra, lattice polygons, lattice polytopes; via pplpy

• Python backend for polyhedra over general ordered fields

• Linear, Mixed Integer Linear, and Semidefinite Optimization frontends

• GNU Linear Programming Kit (GLPK) backend for large-scale linear and mixed integer linear optimization (floating point arithmetic)

• Interactive Simplex Method

• see https://github.com/passagemath/passagemath/blob/main/pkgs/sagemath-polyhedra/MANIFEST.in

Examples

A quick way to try it out interactively:

$ pipx run --pip-args="--prefer-binary" --spec "passagemath-polyhedra[test]" ipython

In [1]: from sage.all__sagemath_polyhedra import *

Available as extras, from other distributions

Additional features:

pip install “passagemath-polyhedra[graphs]”

Face lattices, combinatorial polyhedra, graph-theoretic constructions

pip install “passagemath-polyhedra[groups]”

Constructing symmetric polyhedra, computing automorphisms, lattice point counting modulo group actions

pip install “passagemath-polyhedra[toric]”

Toric Varieties

Other backends for polyhedral computations can be installed:

pip install “passagemath-polyhedra[normaliz]”

Normaliz, via PyNormaliz, provides very fast computations in particular for polyhedra with data in algebraic number fields.

$ pipx run --pip-args="--prefer-binary" --spec "passagemath-polyhedra[normaliz,test]" ipython

In [1]: from sage.all__sagemath_polyhedra import *

In [2]: gap_norm = polytopes.grand_antiprism(backend='normaliz'); gap_norm

In [3]: gap_norm.f_vector()

pip install “passagemath-polyhedra[cddlib]”

cddlib provides support for computations with polyhedra in floating-point arithmetic.

passagemath-polyhedra also provides integration with other packages for additional functionality:

pip install “passagemath-polyhedra[latte]” installs LattE integrale for lattice point counting and volume computation using generating functions.

$ pipx run --pip-args="--prefer-binary" --spec "passagemath-polyhedra[latte,test]" ipython

In [1]: from sage.all__sagemath_polyhedra import *

In [2]: P = polytopes.cube()

In [3]: P.integral_points_count()
Out[3]:
27

In [4]: (1000000000*P).integral_points_count(verbose=True)
This is LattE integrale...
...
Total time:...
Out[4]:
8000000012000000006000000001

pip install “passagemath-polyhedra[polymake]”

Polymake, via JuPyMake

lrslib

Optional backends for optimization:

pip install “passagemath-polyhedra[cbc]”

COIN/OR CBC Mixed Integer Linear Optimization solver, via sage_numerical_backends_coin

pip install “passagemath-polyhedra[cplex]”

CPLEX Mixed Integer Optimization solver (proprietary; requires licensed installation), via sage_numerical_backends_cplex

pip install “passagemath-polyhedra[cvxpy]”

CVXPy as middle-end for various backends

pip install “passagemath-polyhedra[gurobi]”

Gurobi Mixed Integer Optimization solver (proprietary; requires licensed installation), via sage_numerical_backends_gurobi

pip install “passagemath-polyhedra[scip]”

SCIP Mixed Integer Optimization solver, via PySCIPOpt

Development

$ git clone --origin passagemath https://github.com/passagemath/passagemath.git
$ cd passagemath
passagemath $ ./bootstrap
passagemath $ python3 -m venv polyhedra-venv
passagemath $ source polyhedra-venv/bin/activate
(polyhedra-venv) passagemath $ pip install -v -e pkgs/sagemath-polyhedra