在Python/Numpy中实现变系数简单过滤器的有效方法

import numpy as np

def sliding_window(signal, window_size):
    windows = np.array_split(signal, len(signal) / window_size)
    return windows

def coefficient_of_variation(window):
    std = np.std(window)
    mean = np.mean(window)
    coefficient = std / mean
    return coefficient

def filter_signal(signal, window_size, threshold):
    windows = sliding_window(signal, window_size)
    filtered_signal = []
    for window in windows:
        coefficient = coefficient_of_variation(window)
        if coefficient < threshold:
            filtered_signal.extend(window)
    return np.array(filtered_signal)