scipy.optimize._optimize:fmin_powell

Parameters

func : callable f(x,*args)

Objective function to be minimized.

x0 : ndarray

Initial guess.

args : tuple, optional

Extra arguments passed to func.

xtol : float, optional

Line-search error tolerance.

ftol : float, optional

Relative error in func(xopt) acceptable for convergence.

maxiter : int, optional

Maximum number of iterations to perform.

maxfun : int, optional

Maximum number of function evaluations to make.

full_output : bool, optional

If True, fopt, xi, direc, iter, funcalls, and warnflag are returned.

disp : bool, optional

If True, print convergence messages.

retall : bool, optional

If True, return a list of the solution at each iteration.

callback : callable, optional

An optional user-supplied function, called after each iteration. Called as callback(xk), where xk is the current parameter vector.

direc : ndarray, optional

Initial fitting step and parameter order set as an (N, N) array, where N is the number of fitting parameters in x0. Defaults to step size 1.0 fitting all parameters simultaneously (np.eye((N, N))). To prevent initial consideration of values in a step or to change initial step size, set to 0 or desired step size in the Jth position in the Mth block, where J is the position in x0 and M is the desired evaluation step, with steps being evaluated in index order. Step size and ordering will change freely as minimization proceeds.