def __init__(self, max_iter=None, fun_margin=None, grad_margin=None, step_min=None):
self.max_iter = max_iter<EOL>self.fun_margin = fun_margin<EOL>self.grad_margin = grad_margin<EOL>self.step_min = step_min<EOL>self.reset()<EOL>
Optional arguments:
 | ``max_iter``  --  the maximum number of iterations allowed
 | ``fun_margin``  --  if the function to be minimized goes above the
                       lowest value so far plus this margin, the
                       minimization is aborted
 | ``grad_margin``  --  if the RMS value of the gradient components
                        goes above the lowest value plus this
                        threshold, the minimization is aborted
 | ``step_min``  --  If the RMS step size drops below this margin, the
                     optimization is interrupted.

Only the present arguments define when the minimization has lost
track.