input: Write a function that optimizes a given multivariate function using the scipy.optimize.minimize method. The function should take two arguments: the function to be optimized and an initial guess for the optimization. The function should return the optimized values of the variables.
  
  assert optimize_function(lambda x: (x[0] - 1)**2 + (x[1] - 2.5)**2, [2, 0]) == [1.0, 2.5]
  assert optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1]) == [0.0, 0.0]
  assert optimize_function(lambda x: (x[0] - 3)**2 + (x[1] + 2)**2, [-1, -1]) == [3.0, -2.0]
output: def optimize_function(func, initial_guess):
      from scipy.optimize import minimize
      result = minimize(func, initial_guess)
      return result.x