`scipy.optimize._root:_root_broyden1_doc`

source: /scipy/optimize/_root.py :385

Signature

def _root_broyden1_doc ( )

Parameters

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.

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: alpha
reduction_method: reduction_method
max_rank: max_rank

Examples

def func(x):
    return np.cos(x) + x[::-1] - [1, 2, 3, 4]
from scipy import optimize
res = optimize.root(func, [1, 1, 1, 1], method='broyden1', tol=1e-14)
x = res.x

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np.cos(x) + x[::-1]

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Aliases

scipy.optimize._root._root_broyden1_doc