input: def optimize(obj_func):
      """
      Write a python program to optimize the given objective function using the scipy.optimize.minimize function. The objective function should be passed as an argument to this function.
      
      >>> def obj_func(x): return (x[0] - 1)**2 + (x[1] - 2.5)**2 + (x[2] - 0.5)**2
      >>> optimize(obj_func)
      [0.99999995 2.49999996 0.49999862]
      """
      x0 = [0.0, 0.0, 0.0]
      res = minimize(obj_func, x0, method='nelder-mead', options={'xtol': 1e-8, 'disp': True})
      return res.x
output:     x0 = [0.0, 0.0, 0.0]
      res = minimize(obj_func, x0, method='nelder-mead', options={'xtol': 1e-8, 'disp': True})
      return res.x