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object --+ | FminWrapper --+ | FminPowell
Abstract class to generate wrappers around scipy.optimize fmin_* functions. Parameters ----------- criterion : Criterion A criterion function with __call__ and gradient methods. x0 : ndarray (None) First guess args=() : tuple Extra arguments for the criterion function kwargs : dict Parameters of the fmin_function fmin function docstring ------------------------ Minimize a function using modified Powell's method. Parameters ---------- func : callable f(x,*args) Objective function to be minimized. x0 : ndarray Initial guess. args : tuple Extra arguments passed to func. callback : callable An optional user-supplied function, called after each iteration. Called as ``callback(xk)``, where ``xk`` is the current parameter vector. direc : ndarray Initial direction set. Returns ------- xopt : ndarray Parameter which minimizes `func`. fopt : number Value of function at minimum: ``fopt = func(xopt)``. direc : ndarray Current direction set. iter : int Number of iterations. funcalls : int Number of function calls made. warnflag : int Integer warning flag: 1 : Maximum number of function evaluations. 2 : Maximum number of iterations. allvecs : list List of solutions at each iteration. Other Parameters ---------------- xtol : float Line-search error tolerance. ftol : float Relative error in ``func(xopt)`` acceptable for convergence. maxiter : int Maximum number of iterations to perform. maxfun : int Maximum number of function evaluations to make. full_output : bool If True, fopt, xi, direc, iter, funcalls, and warnflag are returned. disp : bool If True, print convergence messages. retall : bool If True, return a list of the solution at each iteration. Notes ----- Uses a modification of Powell's method to find the minimum of a function of N variables.
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__doc__ = FminWrapper.__doc__+ opt.fmin_powell.__doc__
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Inherited from |
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