input: Write a function to optimize a given multivariate function using the `scipy.optimize.minimize` function from the `scipy` library. The function should take as input the function to be optimized and an initial guess for the optimization. It should return the optimal values of the variables as found by the optimization algorithm.
  assert list(optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1]))==[0.0, 0.0]
  assert list(optimize_function(lambda x: (x[0]-2)**2 + (x[1]+3)**2, [0, 0]))==[2.0, -3.0]
  assert list(optimize_function(lambda x: x[0]**4 + x[1]**4, [-1, -1]))==[0.0, 0.0]
output: def optimize_function(func, initial_guess):
      from scipy.optimize import minimize
      result = minimize(func, initial_guess)
      return result.x