I have a python function that returns multi-dimensional numpy array as output. It's a Monte Carlo simulation with random numbers and I would like to run this function n times with the same input, collect the data and do the average. Is there a simple way to use multiprocessing to achieve this?

For example, calc average with simple square function using 4 processes:

from multiprocessing import Pooldef f(x):return x*xif __name__ == '__main__':pool = Pool(processes=4)n = 10000000inputs = xrange(n)# calc f output using 4 processesout_list = pool.map(f, inputs)# average  print sum(out_list) / float(n)