code: def _root_diagbroyden_doc():
      """
      Options
      -------
      nit : int, optional
          Number of iterations to make. If omitted (default), make as many
          as required to meet tolerances.
      disp : bool, optional
          Print status to stdout on every iteration.
      maxiter : int, optional
          Maximum number of iterations to make. If more are needed to
          meet convergence, `NoConvergence` is raised.
      ftol : float, optional
          Relative tolerance for the residual. If omitted, not used.
      fatol : float, optional
          Absolute tolerance (in max-norm) for the residual.
          If omitted, default is 6e-6.
      xtol : float, optional
          Relative minimum step size. If omitted, not used.
      xatol : float, optional
          Absolute minimum step size, as determined from the Jacobian
          approximation. If the step size is smaller than this, optimization
          is terminated as successful. If omitted, not used.
      tol_norm : function(vector) -> scalar, optional
          Norm to use in convergence check. Default is the maximum norm.
      line_search : {None, 'armijo' (default), 'wolfe'}, optional
          Which type of a line search to use to determine the step size in
          the direction given by the Jacobian approximation. Defaults to
          'armijo'.
      jac_options : dict, optional
          Options for the respective Jacobian approximation.
  
          alpha : float, optional
              initial guess for the jacobian is (-1/alpha).
      """
      pass
  
file_path: scipy/scipy/optimize/_root.py
imports: import numpy
  from warnings import warn
  from ._optimize import MemoizeJac, OptimizeResult, _check_unknown_options
  from ._minpack_py import _root_hybr, leastsq
  from ._spectral import _root_df_sane
  from .None import _nonlin
label_desc: Use image node_id 9 for calling a global function with example usage: _root_diagbroyden_doc() without return types