scipy.optimize.newton

scipy.optimize.newton(func, x0, fprime=None, args=(), tol=1.48e-08, maxiter=50)

Given a function of a single variable and a starting point, find a nearby zero using Newton-Raphson.

fprime is the derivative of the function. If not given, the Secant method is used.

See also:

fmin, fmin_powell, fmin_cg,

fmin_bfgs, fmin_ncg – multivariate local optimizers

leastsq – nonlinear least squares minimizer

fmin_l_bfgs_b, fmin_tnc,

fmin_cobyla – constrained multivariate optimizers

anneal, brute – global optimizers

fminbound, brent, golden, bracket – local scalar minimizers

fsolve – n-dimenstional root-finding

brentq, brenth, ridder, bisect, newton – one-dimensional root-finding

fixed_point – scalar and vector fixed-point finder