Hello. I am interested in using OpenOpt, a numerical optimization framework in Python.
I've been reading the official documentation about OpenOpt, but it seems a little confusing to me. So, this is a question about OpenOpt; sorry if it is too specific for this forum, but I thought maybe someone reading this forum could know anything about OpenOpt. My question is: if I want to use OpenOpt, what must I do? In fact, if I want to develop a new optimization algorithm in Python, how can I use OpenOpt? I mean, in which part of the process can / should I use OpenOpt? What are the advantages of using OpenOpt? Is it just a "bunch" or library of available optimization algorithms, or does it also provide a general framework (a general predefined Object Oriented structure, for example, some general functions in order to manage algorithms...) in order to build an test or run our own algorithms? I hope I've been clear enough about my questions. Any answer will be appreciated. Thank you very much in advance. -- Vicent Giner-Bosch, Valencia (Spain) -- http://mail.python.org/mailman/listinfo/python-list
