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import g4gen
import multiprocessing
import threading
import numpy as np
import itertools
class G4GeneratorProcess(multiprocessing.Process):
def __init__(self, idnum, material, input_queue, output_queue, seed=None):
multiprocessing.Process.__init__(self)
self.idnum = idnum
self.material = material
self.input_queue = input_queue
self.output_queue = output_queue
self.seed = seed
self.daemon = True
def run(self):
gen = g4gen.G4Generator(self.material, seed=self.seed)
while True:
ev = self.input_queue.get()
ev.photon_start = gen.generate_photons(ev)
self.output_queue.put(ev)
class G4VertexGeneratorProcess(multiprocessing.Process):
def __init__(self, vertex_iterator, queue):
multiprocessing.Process.__init__(self)
self.vertex_iterator = vertex_iterator
self.queue = queue
def run(self):
for ev in self.vertex_iterator:
self.queue.put(ev)
def partition(num, partitions):
'''Generator that returns num//partitions, with the last item including the remainder.
Useful for partitioning a number into mostly equal parts while preserving the sum.
>>> list(partition(800, 3))
[266, 266, 268]
>>> sum(list(partition(800, 3)))
800
'''
step = num // partitions
for i in xrange(partitions):
if i < partitions - 1:
yield step
else:
yield step + (num % partitions)
def queue_iterator(nelements, queue):
for i in xrange(nelements):
yield queue.get()
class G4ParallelGenerator(object):
def __init__(self, nprocesses, material, base_seed=None):
self.material = material
self.vertex_queue = multiprocessing.Queue()
self.photon_queue = multiprocessing.Queue()
self.processes = [ G4GeneratorProcess(i, material, self.vertex_queue, self.photon_queue, seed=base_seed + i)
for i in xrange(nprocesses) ]
for p in self.processes:
p.start()
def generate_events(self, nevents, vertex_iterator):
# Doing this to avoid a deadlock caused by putting to one queue while getting from another
for ev in itertools.islice(vertex_iterator, nevents):
self.vertex_queue.put(ev)
return queue_iterator(nevents, self.photon_queue)
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