使用python joblib访问和更改全局数组

我正在尝试在python中使用joblib来加快某些数据处理的速度，但是在尝试确定如何将输出分配为所需格式时遇到了问题。我试图生成一个也许过于简单的代码来显示我所遇到的问题：

from joblib import Parallel, delayed
import numpy as np

def main():
    print "Nested loop array assignment:"
    regular()
    print "Parallel nested loop assignment using a single process:"
    par2(1)
    print "Parallel nested loop assignment using multiple process:"
    par2(2)

def regular():
    # Define variables
    a = [0,1,2,3,4]
    b = [0,1,2,3,4]
    # Set array variable to global and define size and shape
    global ab
    ab = np.zeros((2,np.size(a),np.size(b)))

    # Iterate to populate array
    for i in range(0,np.size(a)):
        for j in range(0,np.size(b)):
            func(i,j,a,b)

    # Show array output
    print ab

def par2(process):
    # Define variables
    a2 = [0,1,2,3,4]
    b2 = [0,1,2,3,4]
    # Set array variable to global and define size and shape
    global ab2
    ab2 = np.zeros((2,np.size(a2),np.size(b2)))

    # Parallel process in order to populate array
    Parallel(n_jobs=process)(delayed(func2)(i,j,a2,b2) for i in xrange(0,np.size(a2)) for j in xrange(0,np.size(b2)))

    # Show array output
    print ab2

def func(i,j,a,b):
    # Populate array
    ab[0,i,j] = a[i]+b[j]
    ab[1,i,j] = a[i]*b[j]

def func2(i,j,a2,b2):
    # Populate array
    ab2[0,i,j] = a2[i]+b2[j]
    ab2[1,i,j] = a2[i]*b2[j]

# Run script
main()

其输出如下所示：

Nested loop array assignment:
[[[  0.   1.   2.   3.   4.]
  [  1.   2.   3.   4.   5.]
  [  2.   3.   4.   5.   6.]
  [  3.   4.   5.   6.   7.]
  [  4.   5.   6.   7.   8.]]

 [[  0.   0.   0.   0.   0.]
  [  0.   1.   2.   3.   4.]
  [  0.   2.   4.   6.   8.]
  [  0.   3.   6.   9.  12.]
  [  0.   4.   8.  12.  16.]]]
Parallel nested loop assignment using a single process:
[[[  0.   1.   2.   3.   4.]
  [  1.   2.   3.   4.   5.]
  [  2.   3.   4.   5.   6.]
  [  3.   4.   5.   6.   7.]
  [  4.   5.   6.   7.   8.]]

 [[  0.   0.   0.   0.   0.]
  [  0.   1.   2.   3.   4.]
  [  0.   2.   4.   6.   8.]
  [  0.   3.   6.   9.  12.]
  [  0.   4.   8.  12.  16.]]]
Parallel nested loop assignment using multiple process:
[[[ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]]

 [[ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]
  [ 0.  0.  0.  0.  0.]]]

从Google和StackOverflow搜索功能来看，使用joblib时似乎不会在每个子进程之间共享全局数组。我不确定这是否是joblib的限制，或者是否有解决方法？

实际上，我的脚本周围是其他代码位，这些代码依赖于此全局数组的最终输出为（4，x，x）格式，其中x是可变的（但通常在100到数千之间）。这是我目前考虑并行处理的原因，因为x = 2400 ，整个过程最多可能需要2个小时。

不必使用joblib（但我喜欢命名和简单性），因此可以随意建议简单的替代方法，最好牢记最终数组的要求。我正在使用python 2.7.3和joblib 0.7.1。