A modeling toolfor convex piecewise-linear optimization problems.Upgrades of the GLPK and MOSEK interfaces.Upgrade of the MOSEK interface to MOSEK version 6. CVXOPT has separate dense and sparse matrix objects. A few bug fixes inthe matrix class.Several bug fixes.
Interfaces to the MOSEK andGLPK integer LP solvers (these features are documented in the sourcedocstrings).Upgrade to SuiteSparse version 4.4.5. It can be used with the interactive Pythoninterpreter, on the command line by executing Python scripts, orintegrated in other software via Python extension modules. efficient Python classes for dense and sparse matrices (real and complex),with Python indexing and slicing and overloaded operations for matrixarithmetican interface to most of the double-precision real and complex BLASroutines for linear, second-order cone, and semidefinite programmingproblemsa modeling tool for specifying convex piecewise-linear optimizationproblems.CVXOPT is a free software package for convex optimization based on thePython programming language. Performanceimprovements in the optimization routines. Several bug fixes.Several bug fixes. Its main purposeis to make the development of software for convex optimization applicationsstraightforward by building on Python’s extensive standard libraryand on the strengths of Python as a high-level programming language.interfaces to the linear programming solver in GLPK, the semidefiniteprogramming solver in DSDP5, and the linear, quadratic and second-ordercone programming solvers in MOSEKinterfaces to the sparse LU and Cholesky solvers from UMFPACK and CHOLMODan interface to the fast Fourier transform routines from FFTWCVXOPT was originally developed for use in our own work, and is being madeavailable in the hope that it may be useful to others.We welcome feedback, bug reports, and suggestions for improvements, butcan only offer very limited support.Python Software for Convex Optimizationroutines for nonlinear convex optimization
Python Software for Convex Optimization . matrix(), spmatrix(), and the other functions in cvxopt.base can now be directly imported from cvxopt (“ from cvxopt import matrix ” replaces “ from cvxopt.base import matrix ”, although the older code still works). Upgrade to SuiteSparseversion 4.1.0. Several bug fixes.Interfaces to the LP solvers in MOSEK and GLPK.Removed the SuiteSparse source code from the distribution.The CHOLMOD interface. Additional LAPACK routines forLQ factorization and QR factorization with column pivoting.Fixed a Mac OS X BLAS compatibility issue.Dense and sparse matrix class. As an example, we can solve the QP Indexing of matrices¶.
A linearprogramming solver. Quadratic programs can be solved via the solvers.qp() function. A Numpy array is created from a matrix using Numpy… Improved Windows compatibility (Python 3.5+).Several bug fixes (int/int_t issues). There are two approaches for indexing dense and sparse matrices: single-argument indexing and double-argument indexing. The LAPACKsolvers for banded and tridiagonal equations. Improved SunOS/Solariscompatibility (“complex double” instead of “complex”).Performance improvements in the sparse matrix arithmetic. Numpy and CVXOPT¶ In Python 2.7, Numpy arrays and CVXOPT matrices are compatible and exchange information using the Array Interface.
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