我有一个名为run的冗长函数，其中包含一些附加数据的实例。
from multiprocessing import Process
data = []
def run():
global data
...
data.append(trace)
...
if __name__ == '__main__':
jobs = []
gen_count = 0
leaked_count = 0
system_count = 0
N = 100
for i in range(N):
p = Process(target=run)
jobs.append(p)
p.start()
但是，使用多处理时不会附加任何数据。此外，函数run会返回需要添加到gen_count，leaked_count和system_count的多个值，我不知道如何检索这些值。我选择了多处理，因为在run循环中运行for的速度很慢，每次迭代都与其余迭代无关。我想在以后的代码中加入GPU加速，对于那些有任何想法的人。
所以我的问题如下：
trace未被追加到data？run的输出？编辑：
from plotly.offline import init_notebook_mode
import plotly.graph_objs as go
import plotly as py
import time
import Cross_Section_Loading
from multiprocess import Process, Pool, Queue, Manager, cpu_count
from functools import partial
import numpy as np
init_notebook_mode(connected=True)
...
def particle_func(x, y, z):
leaked = 0
nu = 0
# get initial direction
theta = np.random.uniform(0, np.pi, 1)
phi = np.random.uniform(0, 2 * np.pi, 1)
# compute energy via rejection sampling
expfiss = lambda e: 0.453 * np.exp(-1.036 * e / 1.0e6) * np.sinh(np.sqrt(2.29 * e / 1.0e6))
min_eng = np.min(E)
max_eng = np.max(E)
max_prob = np.max(expfiss(E))
rejected = 1
while rejected:
a = np.random.uniform(min_eng, max_eng, 1)
b = np.random.uniform(0, max_prob, 1)
rel_prob = expfiss(a)
if b <= rel_prob:
energy = a
rejected = 0
alive = 1
# vector to keep track of positions
xvec = np.ones(1) * x
yvec = np.ones(1) * y
zvec = np.ones(1) * z
while alive:
# Get real/new cross-sections for corresponding energy
index = energy_lookup(E, energy)
interacted = 0
total_distance = 0
# Interacted may still be alive (scattering)
while interacted == 0:
###################################################
# Determine starting location for sample distance using sigma_total
material_start = material_type(x, y)
if material_start == 1:
sig_tot = sigma_total_fuel(ENRICHMENT_1)[index]
elif material_start == 2:
sig_tot = sigma_total_fuel(ENRICHMENT_2)[index]
elif material_start == 3:
sig_tot = sigma_total_fuel(ENRICHMENT_3)[index]
else:
sig_tot = sigma_total_mod[index]
###################################################
if material_start == 1 or material_start == 2 or material_start == 3: # if in fuel pin
# Get distance to edge of fuel rod (from fuel)
d = distance_to_edge(x, y, phi)
# get sample distance to collision
s = -np.log(1.0 - np.random.random(1)) / sig_tot
# Incidence on interface (denoted by code "no-interface")
if d != 'no-interface':
# Sample distance is greater than interface distance (does not account for material change)
# Must convert between 2D and 3D
if s * np.sin(theta) > d:
total_distance += d / np.sin(theta)
# Sample distance is correct and interaction occurs
else:
total_distance += s
interacted = 1
# Statement may be redundant but idk how to handle return from distance_to_rod
else:
total_distance += s
interacted = 1
else: # if in moderator
# get distance to edge of fuel rod (from moderator)
d = distance_to_edge(x, y, phi)
# get distance to collision
s = -np.log(1.0 - np.random.random(1)) / sig_tot
# Incidence on interface (denoted by code "no-interface")
if d != 'no-interface':
# Sample distance is greater than interface distance (does not account for material change)
# Must convert between 2D and 3D
if s * np.sin(theta) > d:
total_distance += d / np.sin(theta) # <- Right conversion?
# Sample distance is correct and interaction occurs
else:
total_distance += s
interacted = 1
# Statement may be redundant but idk how to handle return from distance_to_rod
else:
total_distance += s
interacted = 1
# move particle
z += total_distance * np.cos(theta)
y += total_distance * np.sin(theta) * np.sin(phi)
x += total_distance * np.sin(theta) * np.cos(phi)
# material_end = material_type(x, y)
#
# if material_start != material_end:
# print("Neutron has crossed material interface(s)")
# Trace/Track particle movement
xvec = np.append(xvec, x)
yvec = np.append(yvec, y)
zvec = np.append(zvec, z)
###################################################
# Leakage
if x > X_BOUNDARY or x < -X_BOUNDARY:
# Still need implementation
leaked = 1
alive = 0
if y > Y_BOUNDARY or y < -Y_BOUNDARY:
# Still need implementation
leaked = 1
alive = 0
if z > HEIGHT or z < 0:
# Still need implementation
leaked = 1
alive = 0
###################################################
# Determine Type of interaction based on energy and corresponding cross-sections
# In fuel
material = material_type(x, y)
if material == 1:
sig_scat_temp = sigma_scatter_fuel(ENRICHMENT_1)[index]
sig_fiss_temp = sigma_fission_fuel(ENRICHMENT_1)[index]
sig_tot_temp = sigma_total_fuel(ENRICHMENT_1)[index]
nu_temp = nu_fuel(ENRICHMENT_1)[index]
# scatter or absorb
if np.random.random(1) < sig_scat_temp / sig_tot_temp:
# scatter, pick new angles & energy
theta = np.random.uniform(0, np.pi, 1)
phi = np.random.uniform(0, 2 * np.pi, 1)
energy = np.random.uniform(alpha_fuel * energy, energy, 1)
elif np.random.random(1) < sig_fiss_temp / sig_tot_temp:
# Determine number of neutrons produced from fission
# round or int or both?
nu = int(round(nu_temp))
alive = 0
else:
# absorbed
alive = 0
#############################
elif material == 2:
sig_scat_temp = sigma_scatter_fuel(ENRICHMENT_2)[index]
sig_fiss_temp = sigma_fission_fuel(ENRICHMENT_2)[index]
sig_tot_temp = sigma_total_fuel(ENRICHMENT_2)[index]
nu_temp = nu_fuel(ENRICHMENT_2)[index]
# scatter or absorb
if np.random.random(1) < sig_scat_temp / sig_tot_temp:
# scatter, pick new angles & energy
theta = np.random.uniform(0, np.pi, 1)
phi = np.random.uniform(0, 2 * np.pi, 1)
energy = np.random.uniform(alpha_fuel * energy, energy, 1)
elif np.random.random(1) < sig_fiss_temp / sig_tot_temp:
# Determine number of neutrons produced from fission
# round or int or both?
nu = int(round(nu_temp))
alive = 0
else:
# absorbed
alive = 0
#############################
if material == 3:
sig_scat_temp = sigma_scatter_fuel(ENRICHMENT_3)[index]
sig_fiss_temp = sigma_fission_fuel(ENRICHMENT_3)[index]
sig_tot_temp = sigma_total_fuel(ENRICHMENT_3)[index]
nu_temp = nu_fuel(ENRICHMENT_3)[index]
# scatter or absorb
if np.random.random(1) < sig_scat_temp / sig_tot_temp:
# scatter, pick new angles & energy
theta = np.random.uniform(0, np.pi, 1)
phi = np.random.uniform(0, 2 * np.pi, 1)
energy = np.random.uniform(alpha_fuel * energy, energy, 1)
elif np.random.random(1) < sig_fiss_temp / sig_tot_temp:
# Determine number of neutrons produced from fission
# round or int or both?
nu = int(round(nu_temp))
alive = 0
else:
# absorbed
alive = 0
#############################
# In water
else:
mod_scat = sigma_scatter_mod[index]
mod_tot = sigma_total_mod[index]
# scatter or absorb
if np.random.random(1) < mod_scat / mod_tot:
# scatter, pick new angles & energy
theta = np.random.uniform(0, np.pi, 1)
phi = np.random.uniform(0, 2 * np.pi, 1)
energy = np.random.uniform(alpha_mod * energy, energy, 1)
else:
# absorbed
alive = 0
###################################################
return xvec, yvec, zvec, nu, leaked
##################################################################
def run(data_test):
###################################################
# Uniformly Dispersed Source (Cylinder)
# x = np.random.uniform(-X_BOUNDARY, X_BOUNDARY, 1)
# y = np.random.uniform(-Y_BOUNDARY, Y_BOUNDARY, 1)
# z = np.random.uniform(-HEIGHT, HEIGHT, 1)
# Uniformly Dispersed FUEL Source (Cylinder)
rejected = 1
while rejected:
x = np.random.uniform(-X_BOUNDARY, X_BOUNDARY, 1)
y = np.random.uniform(-Y_BOUNDARY, Y_BOUNDARY, 1)
z = np.random.uniform(-HEIGHT, HEIGHT, 1)
if material_type(x, y):
rejected = 0
###################################################
# Get normal particle info (trace)
x_vec, y_vec, z_vec, nu, leaked = particle_func(x, y, z)
leaked_count = leaked
gen_count = nu
system_count = (1 + nu - leaked)
# particle_trace = go.Scatter3d(
# x=x_vec,
# y=y_vec,
# z=z_vec,
# mode='lines',
# line=dict(color='rgb(173, 255, 47)')
# )
#
# data_test.append(particle_trace)
data_test.append((x_vec, y_vec, z_vec))
###################################################
nu_vec = [nu]
x_vecs = [x_vec]
y_vecs = [y_vec]
z_vecs = [z_vec]
if nu > 0:
print("{} neutrons generated for neutron {}".format(nu, i))
else:
print("No neutrons generated for neutron {}".format(i + 1))
t = 0
recent_nus = nu_vec
while np.any(recent_nus) != 0:
print(nu_vec[-t:])
tracker = 0
nu_vec_temp = []
x_vecs_temp = []
y_vecs_temp = []
z_vecs_temp = []
for a in range(len(nu_vec[-t:])):
x = x_vecs[-(a + 1)][-1]
y = y_vecs[-(a + 1)][-1]
z = z_vecs[-(a + 1)][-1]
for j in range(nu_vec[-(a + 1)]):
x_vec, y_vec, z_vec, nu, leaked = particle_func(x, y, z)
leaked_count += leaked
print("Particle {} starting coords:".format(j + 1), x_vec[0], y_vec[0], z_vec[0])
print("Particle {} ending coords:".format(j + 1), x_vec[-1], y_vec[-1], z_vec[-1])
print("Particle {} nu value".format(j + 1), nu)
nu_vec_temp.append(nu)
tracker += 1
x_vecs_temp.append(x_vec)
y_vecs_temp.append(y_vec)
z_vecs_temp.append(z_vec)
# time.sleep(1)
# particle_trace = go.Scatter3d(
# x=x_vec,
# y=y_vec,
# z=z_vec,
# mode='lines',
# line=dict(color='rgb(255, 0, 0)')
# )
# data_test.append(particle_trace)
data_test.append((x_vec, y_vec, z_vec))
print()
t = tracker
nu_vec.extend(nu_vec_temp)
x_vecs.extend(x_vecs_temp)
y_vecs.extend(y_vecs_temp)
z_vecs.extend(z_vecs_temp)
recent_nus = nu_vec_temp
print("Continuing fission:", (np.any(recent_nus) != 0))
return leaked_count, gen_count, system_count
##################################################################
if __name__ == '__main__':
jobs = []
manager = Manager()
list_ = manager.list()
for _ in range(cpu_count() - 1):
p = Process(target=run, args=(list_,))
jobs.append(p)
p.start()
p.join()
while True: # stops main thread from completing execution
time.sleep(5) # wait 5 second before checking if processes are terminated
if all([not x.is_alive() for x in jobs]): # check if all processes terminated
break # breaks the loop
# print("\nTotal number of neutrons in system:", system_count)
# print("Total number of neutrons generated from {} neutron source: {}".format(N, gen_count))
# print("System Multiplication factor:", gen_count/N)
# print("Total number of leaked neutrons:", leaked_count)
layout = go.Layout(
title='Monte Carlo Assembly',
autosize=True,
showlegend=False,
height=1000,
width=1000,
scene=dict(zaxis=dict(range=[-1, HEIGHT + 1]),
yaxis=dict(range=[-(Y_DIM * PITCH + 5), (Y_DIM * PITCH + 5)]),
xaxis=dict(range=[-(X_DIM * PITCH + 5), (X_DIM * PITCH + 5)])
),
)
fig = go.Figure(data=data, layout=layout)
py.offline.plot(fig, filename='file.html')
输出＆amp;错误消息：
/Users/sterlingbutters/anaconda/bin/python "/Users/sterlingbutters/PycharmProjects/Monte Carlo Simulation/MC Plotly (Cylindrical Assembly) Reflector.py"
For 17 x 17 assembly, 9 x 9 is needed. Your shape: (9, 9)
No neutrons generated for neutron 9
No neutrons generated for neutron 9
No neutrons generated for neutron 9
No neutrons generated for neutron 9
No neutrons generated for neutron 9
No neutrons generated for neutron 9
No neutrons generated for neutron 9
[(array([ 8.48773757, 9.20971263]), array([-10.08484099, -10.22964405]), array([-6.99776389, -7.45397294])), (array([ 8.48773757, 9.20971263]), array([-10.08484099, -10.22964405]), array([-6.99776389, -7.45397294])), (array([ 8.48773757, 9.20971263]), array([-10.08484099, -10.22964405]), array([-6.99776389, -7.45397294])), (array([ 8.48773757, 9.20971263]), array([-10.08484099, -10.22964405]), array([-6.99776389, -7.45397294])), (array([ 8.48773757, 9.20971263]), array([-10.08484099, -10.22964405]), array([-6.99776389, -7.45397294])), (array([ 8.48773757, 9.20971263]), array([-10.08484099, -10.22964405]), array([-6.99776389, -7.45397294])), (array([ 8.48773757, 9.20971263]), array([-10.08484099, -10.22964405]), array([-6.99776389, -7.45397294]))]
Exception ignored in: <function WeakValueDictionary.__init__.<locals>.remove at 0x114ea8488>
Traceback (most recent call last):
File "/Users/sterlingbutters/anaconda/lib/python3.5/weakref.py", line 117, in remove
TypeError: 'NoneType' object is not callable
Exception ignored in: <function WeakValueDictionary.__init__.<locals>.remove at 0x114ea8488>
Traceback (most recent call last):
File "/Users/sterlingbutters/anaconda/lib/python3.5/weakref.py", line 117, in remove
TypeError: 'NoneType' object is not callable
Exception ignored in: <function WeakValueDictionary.__init__.<locals>.remove at 0x114ea8488>
Traceback (most recent call last):
File "/Users/sterlingbutters/anaconda/lib/python3.5/weakref.py", line 117, in remove
TypeError: 'NoneType' object is not callable
Process finished with exit code 0
答案 0 :(得分：2)
多处理使用它自己的全局变量副本从当前环境生成一个不同的进程。在该过程中进行的变量的所有更改都不会反映在父进程中。您需要在进程之间共享内存，并且可以交换共享内存中的变量。
您可以使用multiprocessing.Manager创建列表或字典之类的共享对象，并操纵该对象。
将进程分配给处理器的不同核心/线程。如果你有一个4核/ 8线程系统，产生最多7个进程以最大限度地提高性能，不仅仅是某些进程会干扰其他进程，并且可能减慢/减少分配给你的操作系统的CPU时间，这可能会导致系统崩溃。它始终是用于稳定处理的cpu核心/ cpu线程-1进程，将至少一个核心留给操作系统来处理其他操作。
您可以像这样修改代码
from multiprocessing import Process, Manager
import time
def run(list_):
list_.append(trace)
if __name__ == "__main__":
jobs = []
gen_count = 0
leaked_count = 0
system_count = 0
with Manager() as manager:
list_ = manager.list()
for _ in range(multiprocessing.cpu_count()-1):
p = Process(target=run,args=(list_))
jobs.append(p)
p.start()
while True: #stops main thread from completing execution
time.sleep(5) #wait 5 second before checking if processes are terminated
if all([not x.is_alive() for x in jobs]): #check if all processes terminated
break #breaks the loop
答案 1 :(得分：0)
多处理的工作方式，每个子任务都在自己的内存空间中运行，并获得自己的任何全局变量的副本。有效拥有共享数据的常见方法是使用multiprocessing.Manager来协调对它的并发访问，并透明地防止同时访问它可能导致的任何问题。
以下是基于示例代码执行此操作的示例。它还使用了一个multiprocessing.Pool()，可以很容易地创建一个固定大小的进程对象集合，每个进程对象可以为每个子任务提供异步结果（或者在检索它们之前等待它们全部完成，就像在这里完成的那样） 。
from functools import partial
import multiprocessing
def run(data, i):
data.append('trace%d' % i)
return 1, 2, 3 # values to add to gen_count, leaked_count, and system_count
if __name__ == '__main__':
N = 10
manager = multiprocessing.Manager() # create SyncManager
data = manager.list() # create a shared list
pool = multiprocessing.Pool()
async_result = pool.map_async(partial(run, data), range(N))
values = tuple(zip(*async_result.get()))
gen_count = sum(values[0])
leaked_count = sum(values[1])
system_count = sum(values[2])
print(data)
print('Totals: gen_count {}, leaked_count {}, system_count {}'.format(
gen_count, leaked_count, system_count))
输出：
['trace0', 'trace1', 'trace2', 'trace4', 'trace3', 'trace5', 'trace8', 'trace6', 'trace7', 'trace9']
Totals: gen_count 10, leaked_count 20, system_count 30