input: Write a function to optimize a given multivariate function using the scipy.optimize module. The function should take a function to optimize and an initial guess as input. If the given function is successfully optimized, return the optimized values of the variables. The function will return the optimized values of the variables in a form of an array.
  assert optimize_function(lambda x: (x[0] - 1)**2 + (x[1] - 3)**2, [0, 0])==[1, 3]
  assert optimize_function(lambda x: x[0]**2 + x[1]**2 + x[2]**2, [1, 1, 1])==[0, 0, 0]
  assert optimize_function(lambda x: (x[0] - 1)**2 + x[1]**2, [2, 2])==[1, 0]
  assert optimize_function(lambda x: x[0]**2 - x[1]**2, [1, 1])==[0, 0]
output: def optimize_function(func, initial_guess):
      from scipy.optimize import minimize
      result = minimize(func, initial_guess)
      return result.x