Python3中Multiprocessing配合FuncAnimation实时绘图无更新问题求助

以下是代码存在的核心问题及修复方法：

• 共享内存写入逻辑错误：你在run_server函数中直接对shared_data_time、shared_data_signal做赋值操作，本质是把本地变量重新指向了新的numpy数组，完全没有写入多进程共享的内存区域，主进程自然读不到更新的数据，需要改用切片赋值写入共享内存。
• 数据类型不匹配：你从socket接收的数据解析为float64（8字节）类型，但创建共享数组时用的是'f'（对应float32，4字节），类型不匹配会导致数据乱码、长度错误。
• 绘图函数未正确读取共享数据：matplotlib的plot方法不能直接识别multiprocessing.Array对象，需要先转换为numpy数组或普通列表再绘图。

修正后完整代码 #

import socket
import sys
import math
import numpy as np
import struct
import time
import os
import ctypes as c
import multiprocessing
import matplotlib.pyplot as plt
from matplotlib import animation
from matplotlib import style

HOST = '127.0.0.1'
PORT = 6543
receive_size = 4096

def run_server(shared_data_time, shared_data_signal):   
    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as server:  
        server.bind((HOST, PORT))
        server.listen()
        conn, addr = server.accept() 
        with conn:
            print(f"Connected by {addr}")
            while True:
                data = conn.recv(receive_size)
                if len(data) == 4096:                     
                    payload  = np.frombuffer(data, dtype = 'float64')
                    print(payload)
                    print('received data')
                    deinterleaved = [payload[idx::2] for idx in range(2)] 
                    # 改用切片赋值写入共享内存，同时转换类型匹配共享数组
                    shared_data_time[:] = deinterleaved[0].astype('float32')
                    shared_data_signal[:] = deinterleaved[1].astype('float32')
                    print(f'received {len(data)} bytes')  

if __name__ == '__main__':
    HOST = '127.0.0.1'
    PORT = 6543
    receive_size = 4096
    
    shared_data_time = multiprocessing.Array('f', 2048)
    shared_data_signal = multiprocessing.Array('f', 2048)
    process1 = multiprocessing.Process(target = run_server, args =(shared_data_time, shared_data_signal))
    process1.start()

    def animate(i, shared_data_time, shared_data_signal):
        ax1.clear()
        # 将共享数组转换为numpy数组再绘图
        ax1.plot(np.asarray(shared_data_time), np.asarray(shared_data_signal))

    style.use('fivethirtyeight')
    fig = plt.figure()
    ax1 = fig.add_subplot(1,1,1)
    ani = animation.FuncAnimation(fig, animate, fargs = (shared_data_time, shared_data_signal), interval = 100) 
    plt.show() 

内容的提问来源于stack exchange，提问作者Victor Robles Fernández