goldenSection vs scipy.optimize fminbound

For some numerical experiments (intended by our chief Petro I. Stetsyuk and me) with r-algorithm (that is implemented in OO ralg solver) a good line-search optimizer is required.

As you know scipy.optimize has single-variable box-bounded optimization routine "fminbound" (connected to OO as scipy_fminbound). Unfortunately, it has 2 drawbacks:
- it uses mix of golden section and quadratic spline approximation, and latter works very bad for non-smooth and/or noisy funcs, that we deal with
- sometimes solution returned is out of lb-ub bounds.

So I have implemented pure golden section algorithm into OO solver "goldenSection" (nothing special, just several lines of code).