input: Write a function to optimize the given objective function using the minimize function from the scipy.optimize module. The function should set up the optimization problem with specified initial parameters and return the optimized values of the variables. If the given objective function is empty, it should print a message indicating that the objective function needs to be defined.
  assert optimize()==[0.0, 0.0, 0.0]
  assert optimize()==[1.0, 1.0, 1.0]
  assert optimize()==[0.5, 0.5, 0.5]
  assert optimize()==[0.25, 0.25, 0.25]
  assert optimize()==[0.75, 0.75, 0.75]
  assert optimize()==[]
output: def optimize():
      from scipy.optimize import minimize
      def objective(x):
          return sum(x)
      
      initial_guess = [0.0, 0.0, 0.0]
      result = minimize(objective, initial_guess)
      return result.x