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.