code: def fixed_point(
      func, x0, args=(), xtol=1e-8, maxiter=500, method="del2"
  ):
      """
      Find a fixed point of the function.
  
      Given a function of one or more variables and a starting point, find a
      fixed-point of the function: i.e. where ``func(x0) == x0``.
  
      Parameters
      ----------
      func : function
          Function to evaluate.
      x0 : array_like
          Fixed point of function.
      args : tuple, optional
          Extra arguments to `func`.
      xtol : float, optional
          Convergence tolerance, defaults to 1e-08.
      maxiter : int, optional
          Maximum number of iterations, defaults to 500.
      method : {"del2", "iteration"}, optional
          Method of finding the fixed-point, defaults to "del2"
          which uses Steffensen's Method with Aitken's ``Del^2``
          convergence acceleration [1]_. The "iteration" method simply iterates
          the function until convergence is detected, without attempting to
          accelerate the convergence.
  
      References
      ----------
      .. [1] Burden, Faires, "Numerical Analysis", 5th edition, pg. 80
  
      Examples
      --------
      >>> from scipy import optimize
      >>> def func(x, c1, c2):
      ...    return np.sqrt(c1/(x+c2))
      >>> c1 = np.array([10,12.])
      >>> c2 = np.array([3, 5.])
      >>> optimize.fixed_point(func, [1.2, 1.3], args=(c1,c2))
      array([ 1.4920333 ,  1.37228132])
  
      """
      use_accel = {"del2": True, "iteration": False}[method]
      x0 = _asarray_validated(x0, as_inexact=True)
      return _fixed_point_helper(
          func, x0, args, xtol, maxiter, use_accel
      )
  
imports: from __future__ import division, print_function, absolute_import
  import threading
  import warnings
  from .None import _minpack
  import numpy
  from numpy import atleast_1d, dot, take, triu, shape, eye, transpose, zeros, product, greater, array, all, where, isscalar, asarray, inf, abs, finfo, inexact, issubdtype, dtype
  from scipy.linalg import svd, cholesky, solve_triangular, LinAlgError
  from scipy._lib._util import _asarray_validated, _lazywhere
  from .optimize import OptimizeResult, _check_unknown_options, OptimizeWarning
  from ._lsq import least_squares
  from ._lsq.common import make_strictly_feasible
  from ._lsq.least_squares import prepare_bounds
label_desc: Use image node_id 13 for calling a global function with example usage: fixed_point(func, x0, args, xtol, maxiter, method) and returns: _fixed_point_helper