scipy.optimize.fmin_bfgs¶
- scipy.optimize.fmin_bfgs(f, x0, fprime=None, args=(), gtol=1.0000000000000001e-05, norm=inf, epsilon=1.4901161193847656e-08, maxiter=None, full_output=0, disp=1, retall=0, callback=None)¶
Minimize a function using the BFGS algorithm.
Parameters: - f : callable f(x,*args)
Objective function to be minimized.
- x0 : ndarray
Initial guess.
- fprime : callable f’(x,*args)
Gradient of f.
- args : tuple
Extra arguments passed to f and fprime.
- gtol : float
Gradient norm must be less than gtol before succesful termination.
- norm : float
Order of norm (Inf is max, -Inf is min)
- epsilon : int or ndarray
If fprime is approximated, use this value for the step size.
- callback : callable
An optional user-supplied function to call after each iteration. Called as callback(xk), where xk is the current parameter vector.
Returns: (xopt, {fopt, gopt, Hopt, func_calls, grad_calls, warnflag}, <allvecs>)
- xopt : ndarray
Parameters which minimize f, i.e. f(xopt) == fopt.
- fopt : float
Minimum value.
- gopt : ndarray
Value of gradient at minimum, f’(xopt), which should be near 0.
- Bopt : ndarray
Value of 1/f’‘(xopt), i.e. the inverse hessian matrix.
- func_calls : int
Number of function_calls made.
- grad_calls : int
Number of gradient calls made.
- warnflag : integer
1 : Maximum number of iterations exceeded. 2 : Gradient and/or function calls not changing.
- allvecs : list
Results at each iteration. Only returned if retall is True.
- Other Parameters:
- maxiter : int
- Maximum number of iterations to perform.
- full_output : bool
- If True,return fopt, func_calls, grad_calls, and warnflag in addition to xopt.
- 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. See Also:
- scikits.openopt : SciKit which offers a unified syntax to call
- this and other solvers.
