scipy.optimize.fmin_powell¶

scipy.optimize.fmin_powell(func, x0, args=(), xtol=0.0001, ftol=0.0001, maxiter=None, maxfun=None, full_output=0, disp=1, retall=0, callback=None, direc=None)

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 Eextra 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. (xopt, {fopt, xi, direc, iter, funcalls, warnflag}, {allvecs}) 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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