input: Write a function to optimize a given multivariate function using the scipy.optimize library. The function should take the function to be optimized and an initial guess as input and return the optimized result as an array.
  assert optimize_function(lambda x: x[0]**2 + x[1]**2, [2, 3])==array([-4.44002034e-16, -3.43201330e-18])
  assert optimize_function(lambda x: (x[0]-3)**2 + (x[1]+2)**2, [0, 0])==array([3., -2.])
  assert optimize_function(lambda x: x[0]**4 + x[1]**4, [-1, 1])==array([4.25155249e-20, -3.49618912e-20])
output: def optimize_function(func, initial_guess):
      from scipy.optimize import minimize
      result = minimize(func, initial_guess)
      return result.x