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approx_derivative(fun, x0, method='3-point', rel_step=None, abs_step=None, f0=None, bounds=(-inf, inf), sparsity=None, as_linear_operator=False, args=(), kwargs={})



fun : callable
x0 : array_like of shape (n,) or float
method : {'3-point', '2-point', 'cs'}, optional
rel_step : None or array_like, optional
abs_step : array_like, optional
f0 : None or array_like, optional
bounds : tuple of array_like, optional
sparsity : {None, array_like, sparse matrix, 2-tuple}, optional
as_linear_operator : bool, optional
args, kwargs : tuple and dict, optional


J : {ndarray, sparse matrix, LinearOperator}

See Also



See :

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GitHub : /scipy/optimize/
type: <class 'function'>