PICOS 1.2.0.post14

A Python interface to conic optimization solvers.

A Python Interface to Conic Optimization Solvers

PICOS is a user friendly Python API to several conic and integer programming solvers, very much like YALMIP or CVX under MATLAB.

PICOS allows you to enter a mathematical optimization problem as a high level model, with painless support for (complex) vector and matrix variables and multidemensional algebra. Your model will be transformed to the standard form understood by an appropriate solver that is available at runtime. This makes your application portable as users have the choice between several commercial and open source solvers.

Features

PICOS runs under both Python 2 and Python 3 and supports the following solvers and problem types. To use a solver, you need to seperately install it along with the Python interface listed here.

Solver	Interface	LP	SOCP	SDP	QCQP	EXP	MIP	License
CPLEX	included	Yes	Yes		Yes		Yes	non-free
CVXOPT	native	Yes	Yes	Yes	Yes	Yes¹		GPL-3
ECOS	ecos-python	Yes	Yes		Yes	Yes	Yes	GPL-3
GLPK	swiglpk	Yes					Yes	GPL-3
Gurobi	included	Yes	Yes		Yes		Yes	non-free
MOSEK	included	Yes	Yes	Yes	Yes		Yes	non-free
SMCP	native	Yes²	Yes²	Yes	Yes²			GPL-3
SCIP	PySCIPOpt	Yes	Yes		Yes		Yes	ZIB/MIT

¹ only geometric programming, ² experimental

Example

This is what it looks like to solve a multidimensional mixed integer program with PICOS:

>>> import picos
>>> P = picos.Problem()
>>> x = P.add_variable("x", 2, vtype="integer")
>>> C = P.add_constraint(x <= 5.5)
>>> P.set_objective("max", 1|x) # 1|x is the sum over x
>>> solution = P.solve(verbose = 0)
>>> print(solution["status"])
'integer optimal solution'
>>> print(P.obj_value())
10.0
>>> print(x)
[ 5.00e+00]
[ 5.00e+00]
>>> print(C.slack)
[ 5.00e-01]
[ 5.00e-01]

Documentation & Source

• The full documentation can be browsed online or downloaded in PDF form.
• The API documentation without the tutorial and examples is also available as a separate PDF.
• The source code lives on GitLab.

Installation

Via pip

If you are using pip you can run pip install picos to get the latest version.

Via Anaconda

If you are using Anaconda you can run conda install -c picos picos to get the latest version.

Via your system's package manager

On Arch Linux, there are seperate packages in the AUR for the latest version and the latest release. Both are split packages that ship both Python 2 and Python 3 versions of PICOS.

If you are packaging PICOS for additional systems, please tell us so we can list your package here!

From source

If you are installing PICOS manually, you can choose between a number of development versions and source releases. You will need to have at least the following Python packages installed:

• NumPy
• CVXOPT

Credits

Developers

• Guillaume Sagnol is PICOS' initial author and primary developer since 2012.
• Maximilian Stahlberg is extending and maintaining PICOS since 2017.

Contributors

For an up-to-date list of all code contributors, please refer to the contributors page. Should a reference from before 2019 be unclear, you can refer to the old contributors page on GitHub as well.

License

PICOS is free and open source software and available to you under the terms of the GNU GPL v3.