code: def test_sa_update():
      def square(x):
          return np.sum(x**2)
  
      new_sa = sa.SA()
  
      search_space = search.SearchSpace(
          n_agents=10,
          n_variables=2,
          lower_bound=[0, 0],
          upper_bound=[10, 10],
      )
  
      new_sa.update(search_space, square)
      new_sa.update(search_space, square)
  
imports: import numpy
  from opytimizer.optimizers.science import sa
  from opytimizer.spaces import search
label_desc: Use image node_id 3 for calling a global function with example usage: test_sa_update() and returns: np