在Python中使用多处理程序编写微分方程输出的问题

Question

实际上，我对并行计算完全陌生，对数值方法而言。我正在尝试使用以下形式的python solve_ivp求解微分方程：

y''(x) + (a^2 + x^2)y(x) = 0
y(0)=1
y'(0)=0
x=(0,100)

我想求解a的范围，并将文件写为a[i] y[i](80)。

原始方程式相当复杂，但实质上其结构与上面定义的相同。我已经使用了for循环，并且要花很多时间进行计算。在网上搜索时，我遇到了一个漂亮的网站，发现此question和相关答案很有价值，可以解决我面临的问题。

我尝试了解决方案中提供的原始代码；但是，产生的输出未正确排序。我的意思是，第二列的顺序不正确。

q1    a1    Y1
q1    a2    Y3
q1    a4    Y4
q1    a3    Y3
q1    a5    Y5
...

我什至尝试过使用一个参数的一个循环，但是仍然存在相同的问题。下面是我的代码，具有相同的多处理方法，但带有solve_ivp

import numpy as np
import scipy.integrate
import multiprocessing as mp
from scipy.integrate import solve_ivp


def fun(t, y):
    # replace this function with whatever function you want to work with
    #    (this one is the example function from the scipy docs for odeint)
    theta, omega = y
    dydt = [omega, -a*omega - q*np.sin(theta)]
    return dydt

#definitions of work thread and write thread functions
tspan = np.linspace(0, 10, 201)


def run_thread(input_queue, output_queue):
    # run threads will pull tasks from the input_queue, push results into output_queue
    while True:
        try:
            queueitem = input_queue.get(block = False)
            if len(queueitem) == 3:
                a, q, t = queueitem
                sol = solve_ivp(fun, [tspan[0], tspan[-1]], [1, 0], method='RK45', t_eval=tspan)
                F = 1 + sol.y[0].T[157]
                output_queue.put((q, a, F))
        except Exception as e:
            print(str(e))
            print("Queue exhausted, terminating")
            break

def write_thread(queue):    
    # write thread will pull results from output_queue, write them to outputfile.txt
    f1 = open("outputfile.txt", "w")
    while True:
        try:
            queueitem = queue.get(block = False)
            if queueitem[0] == "TERMINATE":
                f1.close()
                break
            else:
                q, a, F = queueitem                
                print("{}  {} {} \n".format(q, a, F))            
                f1.write("{}  {} {} \n".format(q, a, F))            
        except:
            # necessary since it will throw an error whenever output_queue is empty
            pass

# define time point sequence            
t = np.linspace(0, 10, 201)

# prepare input and output Queues
mpM = mp.Manager()
input_queue = mpM.Queue()
output_queue = mpM.Queue()

# prepare tasks, collect them in input_queue
for q in np.linspace(0.0, 4.0, 100):
    for a in np.linspace(-2.0, 7.0, 100):
        # Your computations as commented here will now happen in run_threads as defined above and created below
        # print('Solving for q = {}, a = {}'.format(q,a))
        # sol1 = scipy.integrate.odeint(fun, [1, 0], t, args=( a, q))[..., 0]
        # print(t[157])
        # F = 1 + sol1[157]    
        input_tupel = (a, q, t)
        input_queue.put(input_tupel)

# create threads
thread_number = mp.cpu_count()
procs_list = [mp.Process(target = run_thread , args = (input_queue, output_queue)) for i in range(thread_number)]         
write_proc = mp.Process(target = write_thread, args = (output_queue,))

# start threads
for proc in procs_list:
    proc.start()
write_proc.start()

# wait for run_threads to finish
for proc in procs_list:
    proc.join()

# terminate write_thread
output_queue.put(("TERMINATE",))
write_proc.join()

请让我知道多重处理中的错误，以便我可以在此过程中学习一些有关python中多重处理的知识。另外，如果有人让我知道在python中处理这种计算的最优雅/最有效的方法，我将不胜感激。谢谢

Answer 1

您想要的是online sort