def mixed x0 func rosenbrock 30 80 eps 0000000001 rb Cb 10 10 cons con

def mixed(x0, func=rosenbrock(30, 2, 80), eps=0.0000000001):
    rb = 0.5
    Cb = 10

    r = 1
    C = 10

    cons = constraints()
    while True:
        bar = barier(rb, cons)
        pen = penalty(r, cons)
        added = lambda x: pen(x) - bar(x)
        f = lambda x: func(x) + added(x)

        x0 = scipy.optimize.minimize(f, x0, method='CG').x

        if abs(added(x0)) <= eps:
            return x0
        else:
            rb = rb / Cb
            r = r * C