scipy.optimize.golden¶

scipy.optimize.golden(func, args=(), brack=None, tol=1.4901161193847656e-08, full_output=0, maxiter=5000)[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.

Parameters:

Parameters:	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. maxiter : int Maximum number of iterations to perform.

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.

maxiter : int

Maximum number of iterations to perform.