minimize_scalar(method=’brent’)

scipy.optimize.minimize_scalar(fun, args=(), method='brent', tol=None, options={'func': None, 'brack': None, 'xtol': 1.48e-08, 'maxiter': 500, 'disp': 0})

See also

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

Options

——-

maxiterint

Maximum number of iterations to perform.

xtolfloat

Relative error in solution xopt acceptable for convergence.

disp: int, optional

If non-zero, print messages.

0 : no message printing. 1 : non-convergence notification messages only. 2 : print a message on convergence too. 3 : print iteration results.

Notes

—–

Uses inverse parabolic interpolation when possible to speed up

convergence of golden section method.