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PICOS: A Python Interface for Conic Optimization Solvers
========================================================
.. image:: _static/picos_big_trans.gif
Welcome to the documentation of PICOS,
a user-friendly python interface to many linear and conic optimization solvers,
see more about PICOS in the :ref:`introduction `.
The latest version can be downloaded :ref:`here `,
and can be installed by following :ref:`these instructions `.
Alternatively, you can clone the latest development version from **github**:
``$ git clone https://github.com/gsagnol/picos.git``.
This documentation contains a :ref:`tutorial ` and some :ref:`examples `,
which should already be enough for a quick start with PICOS.
There is also a :ref:`summary ` of useful implemented functions.
To go deeper,
have a look at the :ref:`picos reference `, which provides information
on every function of PICOS.
**News**
* 15 Apr. 15: **Picos** :ref:`1.1.0 ` **Released**
* PICOS is now compatible with **python 3+** (and remains compatible with python 2.6+). Many thanks to `Sergio Callegari `_ for this compatibility layer ! If you plan to work with PICOS and python3, think to install the most recent version of your solver (Mosek, Cplex, Gurobi, or Cvxopt). SCIP is not supported in python3+ at this point (but remains supported with python 2.x).
* PICOS is now available on `github `_.
* 30 Jan. 15: **Picos** :ref:`1.0.2 ` **Released**
Major release with following new functionalities:
* Support (read and write) for ``.cbf`` problem files (`conic benchmark format `_ ), which should be the standard for (mixed integer) conic optimization problems, cf. :func:`write_to_file ` and :func:`import_cbf ` .
* Improved support for complex SDP (more efficient implementation of :func:`to_real() ` , corrected bug in the implementation of the scalar product for Hermitian matrices and the conjugate of a complex expression, support for equality constraints involving complex coefficients)
* Support for inequalities involving the sum of k largest elements of an affine expression, or the k largest eigenvalues of a symmetric matrix expression, cf. the functions :func:`sum_k_largest() ` , :func:`sum_k_smallest() ` , :func:`sum_k_largest_lambda() `, :func:`sum_k_smallest_lambda() `, :func:`lambda_max() ` and :func:`lambda_min() ` .
* Support for inequalities involving the :math:`L_{p,q}-` norm of an affine expresison, cf. :func:`norm() ` .
* New ``vtype`` for antisymmetric matrix variables ( :attr:`vtype ` ``= antisym``).
* Constraints can be specified as membership in a :class:`Set ` . Sets can be created by the functions :func:`ball() ` , :func:`simplex() `, and :func:`truncated_simplex() ` .
* New functions :func:`maximize ` and :func:`maximize ` to specify the objective function of a problem and solve it.
And many thanks to `Petter Wittek `_ for the following improvements, who were motivated by the use of PICOS in the package `ncpol2sdpa `_ for optimization over noncommutative polynomials:
* More efficient implementation of the writer to the sparse - SDPA file format (:func:`write_to_file `)
* Hadamard (elementwise) product of affine expression is implemented, as an overload of the ``^`` operator, cf. an example :ref:`here ` .
* Partial transposition of an Affine Expression, cf. :func:`partial_transpose() ` or the :attr:`Tx ` attribute.
* Former changes are listed :ref:`here `.
.. _contents:
**PICOS Documentation contents**
.. toctree::
:maxdepth: 2
intro
tuto_summary
examples
api
download
changes
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`