[SciPy-user] lagrange multipliers in python

[dmitrey]

fdu.xiaojf at gmail.com wrote:
> Hi dmitrey:
>
> dmitrey wrote:
>  > afaik scipy hasn't NLP solvers with equality constraints, as well as CVXOPT.
>  > I had seen somewhere a Python package (seems like binding to c-code)
>  > where rSQP had been implemented, it allows to have nonlin equality
>  > constraints. Try web search "python rsqp optimization solver" or "python
>  > sqp optimization solver"
>
>   The equailty constraints in my problem are linear equations. Does
>   this make things easier?
>   
afaik no, at least for those free Python solvers that I knew
Maybe some weeks later free (BSD) NLP linearization-based Python solver 
will be available in openopt module, that will be capable of handling 
both equality & inequality NL constraints.
HTH, D.

>  >
>  > for example visit
>  > http://trilinos.sandia.gov/packages/moocho/
>  > and python binding to the latter
>  > http://trilinos.sandia.gov/packages/pytrilinos/
>  >
>  > However, I didn't use the ones.
>  > Another one approach is use penalty coefficients (instead of Lagrange
>  > multipliers) with Naum Z. Shor r-alg implemented in scikits.openopt ralg
>  > solver (it doesn't contain c- or f-code, BSD lic.). It can handle
>  > gradient/subgradient provided by user and plot graphics output for NLP
>  > UC ralg solver.
>  > Currently it's unconstrained, but it allows to handle very huge
>  > penalties rather well.
>  >
>  > svn co http://svn.scipy.org/svn/scikits/trunk/openopt openopt
>  > sudo python setup.py install
>  >
>  > from scikits.openopt import NLP
>  > help(NLP)
>  >
>  > however, it doesn't produce pyc-files in the site-packages directory while 
> installation, you'd better to do it by hands now.
>  > this is very preliminary version, only some months has been spent.
>  >
>  >
>  > WBR, D.
>
>   Thanks a lot!
>
>   Regards,
>
>   Xiao Jianfeng
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