# minimize_scalar(method=’bounded’)

scipy.optimize.minimize_scalar(fun, bounds=None, args=(), method='bounded', tol=None, options={'func': None, 'xatol': 1e-05, 'maxiter': 500, 'disp': 0})

  See also

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

  Options
    maxiter int

      Maximum number of iterations to perform.

    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.

    xatol float

      Absolute error in solution xopt acceptable for convergence.

minimize_scalar(method=’brent’) minimize_scalar(method=’golden’)