结合输出多处理python

Question

This question is related to a previous question I asked , and it seems like a simple question, but I have a hard time finding useful information or tutorials about the topic of multiprocessing.

My problem is that I would like to combine the produced data into one big array and then store it in my hdf file.

def Simulation(i, output):
    # make a simulation which outputs it resutlts in A. with shape 4000,3
    A = np.array([4000,3])

    output.put(A)

def handle_output(output):
    hdf = pt.openFile('simulation.h5',mode='w')
    hdf.createGroup('/','data')

    # Here the output should be joined somehow. 
    # I would like to get it in the shape [4000,3,10]

    output.get()
    hdf.createArray('/data','array',A)
    hdf.close()

if __name__ == '__main__':
    output = mp.Queue()    
    jobs = []
    proc = mp.Process(target=handle_output, args=(output, ))
    proc.start()
    for i in range(10):
        p = mp.Process(target=Simulation, args=(i, output))
        jobs.append(p)       
        p.start()
    for p in jobs:
        p.join()
    output.put(None)
    proc.join()

Answer 1

What you really need is a multiprocessing Pool

Just do something like:

def Simulation(i): 
    return output

p = mp.Pool(16)

result = p.map(Simulation,range(10))
result = np.array(result).reshape(...)
p.close()
p.join()