如何应用于一个基于邻域元素的数值数组特殊函数？

import numpy as np

def sliding_window_average(arr, window_size):
    # 填充数组边界
    pad_width = window_size // 2
    padded_arr = np.pad(arr, pad_width, mode='reflect')
    
    # 计算滑动窗口平均值
    averages = []
    for i in range(len(arr)):
        window = padded_arr[i:i + window_size]
        avg = np.mean(window)
        averages.append(avg)
    
    return averages

# 示例
arr = np.array([1, 2, 3, 4, 5])
window_size = 3
print(sliding_window_average(arr, window_size))  # 输出: [2.0, 3.0, 4.0, 5.0]

import numpy as np
from multiprocessing import Pool

def parallel_sliding_window_average(arr, window_size):
    # 填充数组边界
    pad_width = window_size // 2
    padded_arr = np.pad(arr, pad_width, mode='reflect')
    
    # 定义滑动窗口平均函数
    def window_average(i):
        window = padded_arr[i:i + window_size]
        return np.mean(window)
    
    # 并行计算
    with Pool() as pool:
        averages = pool.map(window_average, range(len(arr)))
    
    return averages

# 示例
arr = np.random.rand(10000)
window_size = 5
print(parallel_sliding_window_average(arr, window_size))