scipy.optimize.golden(func, args=(), brack=None, tol=1.4901161193847656e-08, full_output=0)[source]

Return the minimum of a function of one variable.

Given a function of one variable and a possible bracketing interval, return the minimum of the function isolated to a fractional precision of tol.


func : callable func(x,*args)

Objective function to minimize.

args : tuple, optional

Additional arguments (if present), passed to func.

brack : tuple, optional

Triple (a,b,c), where (a<b<c) and func(b) < func(a),func(c). If bracket consists of two numbers (a, c), then they are assumed to be a starting interval for a downhill bracket search (see bracket); it doesn’t always mean that obtained solution will satisfy a<=x<=c.

tol : float, optional

x tolerance stop criterion

full_output : bool, optional

If True, return optional outputs.

See also

Interface to minimization algorithms for scalar univariate functions. See the ‘Golden’ method in particular.


Uses analog of bisection method to decrease the bracketed interval.

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