+ +
+

PICOS: A Python Interface for Conic Optimization Solvers

+_images/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 introduction.

+

The latest version can be downloaded here, +and can be installed by following these instructions. +Alternatively, you can clone the latest development version from github: +$ git clone https://github.com/gsagnol/picos.git.

+

This documentation contains a tutorial and some examples, +which should already be enough for a quick start with PICOS. +There is also a summary of useful implemented functions. +To go deeper, +have a look at the picos reference, which provides information +on every function of PICOS.

+

News

+
+
    +
  • +
    15 Apr. 15: Picos 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 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. write_to_file and import_cbf .
    • +
    • Improved support for complex SDP (more efficient implementation of 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 sum_k_largest() , sum_k_smallest() , sum_k_largest_lambda(), sum_k_smallest_lambda(), lambda_max() and lambda_min() .
    • +
    • Support for inequalities involving the L_{p,q}- norm of an affine expresison, cf. norm() .
    • +
    • New vtype for antisymmetric matrix variables ( vtype = antisym).
    • +
    • Constraints can be specified as membership in a Set . Sets can be created by the functions ball() , simplex(), and truncated_simplex() .
    • +
    • New functions maximize and 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 (write_to_file)
    • +
    • Hadamard (elementwise) product of affine expression is implemented, as an overload of the ^ operator, cf. an example here .
    • +
    • Partial transposition of an Affine Expression, cf. partial_transpose() or the Tx attribute.
    • +
    +
    +
    +
    +
    +
  • +
  • Former changes are listed here.

    +
  • +
+
+

PICOS Documentation contents

+ +
+
+

Indices and tables

+ +
+ + +