l_bfgs_b from scipy.optimize have been connected to openopt

One more box-bounded NLP solver have been connected to openopt as scipy_lbfgsb.
Is solves the example from previous post much faster: ~0.1 sec.

I tried to connect cobyla, but some problems have been encountered. The main one is: all constraints should be passed as sequence of funcs. As far as I learned, even linear constraints Ax<=b or x>=lb should be separated into funcs, each one returning single value. At least, current python-cobyla binding requires this approach. Of course, I can implement the trick, but it can slow calculations very much; maybe, some changes in Python-cobyla binding will turn out to be much more effective solution. But I have no time for now, I'm busy with other things.

One more example have been added to /examples directory: nlp1.py. It uses lincher, but any other solver, capable of handling all constraints, can be use instead.