我有一个代码，使用锁定方案为每个“线程”创建进程并使用两个自己的数组进行操作：
if __name__ == "__main__":
geom_file = sys.argv[1]
filename = sys.argv[2]
event = None
resolution = 5814.0
dist = 0.2
N_3D = 501 # num of points
output_array = []
pixm = cg.pixel_maps_from_geometry_file(geom_file) #getting pairs of coordinates in 3D
x_array = pixm.x.flatten()
y_array = pixm.y.flatten()
z_array = np.ones_like(x_array) * dist
with open(filename,'r') as stream:
#reading stream file ang getting the necessary info
lines = stream.readlines()
output_array = get_opt_patterns(lines)
I_xyz_buf = RawArray(ct.c_double, N_3D * N_3D * N_3D)
count_dot_buf = RawArray(ct.c_double, N_3D * N_3D * N_3D)
mask_buf = RawArray(ct.c_int, len(x_array))
result_lock = Lock()
mask_lock = Lock()
pool = Pool(os.cpu_count(),
initializer=init_worker,
initargs=(result_lock, mask_lock,
I_xyz_buf, count_dot_buf, mask_buf,
x_array, y_array, z_array))
pool.map(processing, output_array)
I_xyz = np.frombuffer(I_xyz_buf, dtype=np.double)
count_dot = np.frombuffer(count_dot_buf, dtype=np.double)
运行后，它显示以下错误：
追踪（最近一次呼叫最后一次）：
File "/opt/anaconda/3/lib/python3.5/multiprocessing/process.py", line 254, in _bootstrap self.run() File "/opt/anaconda/3/lib/python3.5/multiprocessing/process.py", line 93, in run self._target(*self._args, **self._kwargs) File "/opt/anaconda/3/lib/python3.5/multiprocessing/pool.py", line 103, in worker initializer(*initargs) File "processing.py", line 340, in init_worker mask_arr = np.frombuffer(mask_buf, dtype=np.int) ValueError: buffer size must be a multiple of element size
创建工人：
def init_worker(res_lck, mask_lck,
I_xyz_buf, count_dot_buf, mask_buf,
x_arr, y_arr, z_arr):
global result_lock
global mask_lock
global I_xyz_arr
global count_dot_arr
global mask_arr
global x_array
global y_array
global z_array
I_xyz_arr = np.frombuffer(I_xyz_buf, dtype=np.double)
count_dot_arr = np.frombuffer(count_dot_buf, dtype=np.double)
mask_arr = np.frombuffer(mask_buf, dtype=np.int)
result_lock = res_lck
mask_lock = mask_lck
x_array = x_arr
y_array = y_arr
z_array = z_arr
负责此获取的功能：
def NEW_sphere_Evald(x_array, y_array, z_array, mask, Int, k):
global resolution
global N_3D
global mask_lock
len_array = len(x_array)
qx = x_array / 2 + N_3D / 5
qy = y_array * 3 - N_3D / 100
qz = z_array / resolution
with mask_lock:
indexes = np.where((qx < N_3D) &
(qy < N_3D) &
(qz < N_3D) &
(mask != MASK_BAD))[0]
coords = np.array((qx, qy, qz), dtype=np.int32)[:, indexes]
coords_intens = Int[indexes]
intensity = np.histogramdd(coords.T,
bins=[np.arange(0, N_3D + 1, 1),
np.arange(0, N_3D + 1, 1),
np.arange(0, N_3D + 1, 1)],
normed=False,
weights=coords_intens)[0]
click_count = np.histogramdd(coords.T,
bins=[np.arange(0, N_3D + 1, 1),
np.arange(0, N_3D + 1, 1),
np.arange(0, N_3D + 1, 1)])[0]
return intensity, click_count
def get_opt_patterns(lines):
....
# metadata = [name_of_file,energy,len_of_camera,[a,b,c,alpha,betta,gamma],[[a1*,a2*,a3*],[b1*,b2*,b3*],[c1*,c2*,c3*]]]
return metadata
def processing(i):
global result_lock
global mask_lock
global I_xyz_arr
global count_dot_arr
global mask_arr
global x_array
global y_array
global z_array
len_array = len(x_array)
name_of_file = i[0]
# print(name_of_file)
f = h5.File(name_of_file, 'r') # h5.File(sys.argv[1],'r')
Int = f['data/data']
Int = np.reshape(Int, len_array)
index = Int >= 0
with mask_lock:
mask_arr[index] = MASK_GOOD
k = i[1] * (1e10) / 12.4
intensity, click_count = NEW_sphere_Evald(x_array, y_array, z_array, mask_arr, Int, k) # higher
with result_lock:
I_xyz_arr += intensity
count_dot_arr += click_count.astype(count_dot_arr.dtype)
我应该注意和修理什么？这是我第一次面对多进程的必要使用。
尝试：
dtype="int32"它解决了一个问题。但看起来是另一个：
line 119, in worker result = (True, func(*args, **kwds)) File "/opt/anaconda/3/lib/python3.5/multiprocessing/pool.py", line 44, in mapstar return list(map(*args)) File "processing.py", line 319, in processing I_xyz_arr += intensity ValueError: operands could not be broadcast together with shapes (125751501,) (501,501,501) (125751501,)