code: def test_landing_screen():
      # define an objective function
      def objective(args):
          case, val = args
          if case == "case 1":
              return val
          else:
              return val**2
  
      # define a search space
      from hyperopt import hp
  
      space = hp.choice(
          "a",
          [
              ("case 1", 1 + hp.lognormal("c1", 0, 1)),
              ("case 2", hp.uniform("c2", -10, 10)),
          ],
      )
  
      # minimize the objective over the space
      import hyperopt
  
      best = hyperopt.fmin(
          objective, space, algo=hyperopt.tpe.suggest, max_evals=100
      )
  
      print(best)
      # -> {'a': 1, 'c2': 0.01420615366247227}
  
      print(hyperopt.space_eval(space, best))
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_landing_screen() and returns: val, unknown