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# root(method=’broyden1’)

`scipy.optimize.``root`(fun, x0, args=(), method='broyden1', tol=None, callback=None, options={})

  See also

  For documentation for the rest of the parameters, see `scipy.optimize.root`

  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).

  >   reduction_method : str or tuple, optional

  >     Method used in ensuring that the rank of the Broyden matrix stays low. Can either be a string giving the name of the method, or a tuple of the form `(method, param1, param2, ...)` that gives the name of the method and values for additional parameters.

  >     Methods available:
  >       - `restart`: drop all matrix columns. Has no
  >           extra parameters.
  >       - `simple`: drop oldest matrix column. Has no
  >           extra parameters.
  >       - `svd`: keep only the most significant SVD
  >           components.
  >         Extra parameters:
  >           - `to_retain`: number of SVD components to
  >               retain when rank reduction is done. Default is `max_rank - 2`.
  >   max_rank : int, optional

  >     Maximum rank for the Broyden matrix. Default is infinity (ie., no rank reduction).