[SciPy-user] Inexact Newton methods in scipy

Hi all, A standard method to solve nonlinear equations f(x) = 0 is Newton's method. Given a suitable initial guess one iterates f'(x_k) \Delta x_k = -f(x_k) x_{k+1} = x_k + \Delta x_k If the Jacobian is not available in a direct manner, we can apply f'(x_k) to a vector \Delta x_k by a finite difference formula (see my previous mail fdf package) BTW, most publications deal with real Jacobians. How can I extend finite difference formulas to complex Jacobians ? help (linalg.gmres) yields A -- An array or an object with a matvec(x) method to represent A * x A small example illustrating an object with a matvec(x) method would be appreciated. Nils