如何附加循环中的多处理结果？

Question

我想利用多个处理器来计算两个值列表的函数。在下面的测试用例中，我的想法是我有两个列表：c = [1,2,3] 和 c_shift = [2,3,4]。我想为每个列表中的单个值评估一个函数，并附加两个单独的解决方案数组。

import numpy as np
import multiprocessing as mp

def function(x,a,b,c):

    return a*x**2+b*x+c

def calculate(x,a,b,c):
    
    c_shift = c+1
    
    result = []
    result_shift = []
    
    for i in range(len(c)):
        process0 = mp.Process(target = function, args = (x,a,b,c[i]))
        process1 = mp.Process(target = function, args = (x,a,b,c_shift[i]))
        
        process0.start()
        process1.start()
        
        process0.join()
        process1.join()
        
        # After it finishes, how do I append each list?

    return np.array(result), np.array(result_shift)

if __name__ == '__main__':
    x = np.linspace(-1,1,50)
    a = 1
    b = 1
    c = np.array([1,2,3])
    
    calculate(x,a,b,c)

当每个进程完成并经过 join() 时，如何将 process0 附加到 result = [] 并将 process1 附加到 result_shift = []？

返回结果的结构应具有以下形式：

结果 = [[1 x 50], [1 x 50], [1 x 50] ]

result_shifted = [[1 x 50], [1 x 50], [1 x 50] ]

Answer 1

我不确定你到底想用移位的结果完成什么，但就并发性而言，你应该检查 concurrent.futures to execute parallel tasks. Also, take a look at functools.partial 来创建一个部分对象 - 本质上是一个带有 pre- 的函数填充参数/kwargs。这是一个例子：

import concurrent.futures
from functools import partial

import numpy as np


def map_processes(func, _iterable):
    with concurrent.futures.ProcessPoolExecutor() as executor:
        result = executor.map(func, _iterable)
    return result

def function(x, a, b, c):
    return a * x**2 + b * (x + c)

if __name__ == "__main__":
    base_func = partial(function, np.linspace(-1, 1, 50), 1, 1)
    print(list(map_processes(base_func, np.array([1, 2, 3]))))

Answer 2

方法略有不同，但我认为这就是您想要做的？

import multiprocessing
import numpy as np
from functools import partial


def your_func(c, your_x, a, b):
    results = []
    for c_value in c:
        results.append(a * your_x ** 2 + b * your_x + c_value)
    return results


def get_results(c_values):
    your_x = np.linspace(-1, 1, 50)
    a = 1
    b = 1
    with multiprocessing.Pool() as pool:
        single_arg_function = partial(your_func, your_x=your_x, a=a, b=b)
        out = pool.map(single_arg_function, c_values)
        return out


if __name__ == "__main__":
    c_values = [np.array([1, 2, 3]), np.array([1, 2, 3]) + 1]
    out = get_results(c_values)
    result_one = out[0]
    result_two = out[1]

如何附加循环中的多处理结果？

How to append multiprocessed result that is in a loop?

python

loops

append

multiprocessing