scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
See Also:
disp
[bool] Print convergence message if True.
retall
[bool] Return a list of results at each iteration if True.
Notes
Optimize the function, f, whose gradient is given by fprime using the quasi-Newton method
of Broyden, Fletcher, Goldfarb, and Shanno (BFGS) See Wright, and Nocedal ‘Numerical
Optimization’, 1999, pg. 198.
OpenOpt
[a tool which offers a unified syntax to call] this and other solvers with possibility of automatic
differentiation.
fmin_ncg(f, x0, fprime, fhess_p=None, fhess=None, args=(), avextol=1.0000000000000001e-05,
epsilon=1.4901161193847656e-08, maxiter=None, full_output=0, disp=1, retall=0, callback=None)
Minimize a function using the Newton-CG method.
Parameters
f
x0
[callable f(x,*args)] Objective function to be minimized.
[ndarray] Initial guess.
fprime
[callable f’(x,*args)] Gradient of f.
fhess_p
[callable fhess_p(x,p,*args)] Function which computes the Hessian of f times an arbitrary
vector, p.
fhess
[callable fhess(x,*args)] Function to compute the Hessian matrix of f.
args
[tuple] Extra arguments passed to f, fprime, fhess_p, and fhess (the same set of extra
arguments is supplied to all of these functions).
epsilon
[float or ndarray] If fhess is approximated, use this value for the step size.
callback
[callable] An optional user-supplied function which is called after each iteration. Called
as callback(xk), where xk is the current parameter vector.
Returns
(xopt, {fopt, fcalls, gcalls, hcalls, warnflag},{allvecs})
xopt
[ndarray] Parameters which minimizer f, i.e. f(xopt) == fopt.
fopt
[float] Value of the function at xopt, i.e. fopt = f(xopt).
fcalls
[int] Number of function calls made.
302 Chapter 3. Reference