Mastering Python for Finance - Second Edition

Root-finding scalar functions

Some root-finding functions that can be found in the scipy.optimize modules include bisect, newton, brentq, and ridder. Let's set up the examples that we have discussed in the Incremental search section using the implementations by SciPy:

In [ ]:    """    Documentation at    http://docs.scipy.org/doc/scipy/reference/optimize.html    """    import scipy.optimize as optimize    y = lambda x: x**3 + 2.*x**2 - 5.    dy = lambda x: 3.*x**2 + 4.*x    # Call method: bisect(f, a, b[, args, xtol, rtol, maxiter, ...])    print("Bisection method:", optimize.bisect(y, -5., 5., xtol=0.00001))    # Call method: newton(func, x0[, fprime, args, tol, ...])    print("Newton's method:", optimize.newton(y, 5., fprime=dy)) # When fprime=None, then the secant method ...