input: Write a function to optimize a given multivariate function using the scipy.optimize module. The function should take a function and an initial guess as input and return the optimized parameters.
  assert list(optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1]))==[0, 0]
  assert list(optimize_function(lambda x: x[0]**2 + x[1]**3, [2, 2]))==[0, 2]
  assert list(optimize_function(lambda x: x[0]**2 + x[1]**4, [3, 3]))==[0, 0]
  assert list(optimize_function(lambda x: x[0]**2 + x[1]**2, [-1, -1]))==[-0, -0]
  assert list(optimize_function(lambda x: x[0]**2 + x[1]**2, [0, 0]))==[0, 0]
output: def optimize_function(func, initial_guess):
      from scipy.optimize import minimize
      result = minimize(func, initial_guess)
      return result.x