code: def branin():
      """
      The Branin, or Branin-Hoo, function has three global minima,
      and is roughly an angular trough across a 2D input space.
  
          f(x, y) = a (y - b x ** 2 + c x - r ) ** 2 + s (1 - t) cos(x) + s
  
      The recommended values of a, b, c, r, s and t are:
          a = 1
          b = 5.1 / (4 pi ** 2)
          c = 5 / pi
          r = 6
          s = 10
          t = 1 / (8 * pi)
  
      Global Minima:
        [(-pi, 12.275),
         (pi, 2.275),
         (9.42478, 2.475)]
  
      Source: http://www.sfu.ca/~ssurjano/branin.html
      """
      x = hp.uniform("x", -5.0, 10.0)
      y = hp.uniform("y", 0.0, 15.0)
      pi = float(np.pi)
      loss = (
          (y - (5.1 / (4 * pi**2)) * x**2 + 5 * x / pi - 6) ** 2
          + 10 * (1 - 1 / (8 * pi)) * scope.cos(x)
          + 10
      )
      return {
          "loss": loss,
          "loss_variance": 0,
          "status": base.STATUS_OK,
      }
  
imports: import unittest
  import numpy
  from hyperopt import Trials, Domain, fmin, hp, base
  from hyperopt.rand import suggest
  from hyperopt.pyll import as_apply
  from hyperopt.pyll import scope
label_desc: Use image node_id 11 for calling a global function with example usage: branin() and returns: dict