input: Write a function to optimize a given multivariate function using the SciPy optimization library. The function should return the optimized values of the independent variables.
  
  def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x
  
  assert list(optimize_function(lambda x: (x[0] - 1)**2 + (x[1] - 2.5)**2, [2, 0]))==[1.0, 2.5]
  assert list(optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1]))==[0.0, 0.0]
output: def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x