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Python package for convex optimization

CVXOPT is a Python package for convex optimization. It includes * Python classes for storing and manipulating dense and sparse matrices * an interface to most of the double-precision real and complex BLAS * an interface to the dense linear equation solvers and eigenvalue routines from LAPACK * interfaces to the sparse LU and Cholesky solvers from UMFPACK and CHOLMOD. * routines for solving convex optimization problems, an interface to the linear programming solver in GLPK, and interfaces to the linear and quadratic programming solvers in MOSEK * a modeling tool for specifying convex piecewise-linear optimization problems.
Package version:1.1.4-1


This directory contains examples from the book "Convex Optimization" 
by Boyd and Vandenberghe (Cambridge University Press, 2004, and

The scripts require the plotting library Matplotlib, available at  


This directory contains some examples from the following chapters of 
the CVXOPT documentation.

Chapter 4. The LAPACK interface.
Chapter 7. Sparse linear equations.
Chapter 8. Cone programming.
Chapter 9. Nonlinear convex optimization.
Chapter 10. Modeling.


The filterdemo computes a FIR lowpass filter by solving a linear program.  
It solves a discretization of the  problem

minimize     d2
subject to   -1/d1 <= H(wk) <= d1,   0 <= w <=  wc
	     max(abs(H(wk))) <= d2,  ws <= w <= pi

where H(w) = h_0 + sum_{i=1}^{n-1} h_i*cos(2*pi/n*i*w).
The variables are h and d2.

'filterdemo_cli' uses a simple a simple command-line interface. 
'filterdemo_gui' u


cvxopt (1.1.4-1) unstable; urgency=low

  * New upstream release.

 -- Soeren Sonnenburg <sonne@debi


This package was debianized by Soeren Sonnenburg <> on
Wed Jul  4 21:48:22 CEST 2007

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