Class FminPowell

source code

 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.