一维时序信号非局部均值滤波的Python代码

以下是一维时序信号非局部均值滤波的Python代码：

import numpy as np

def nlmeans_1d(signal, patch_size, search_size, h):
    """
    Non-local means denoising filter for 1D time series signal.
    :param signal: 1D numpy array, the time series signal to be denoised.
    :param patch_size: int, the size of the patch to be compared with the reference patch.
    :param search_size: int, the size of the search window for finding similar patches.
    :param h: float, the filtering parameter.
    :return: 1D numpy array, the denoised signal.
    """
    n = len(signal)
    denoised_signal = np.zeros(n)

    for i in range(n):
        ref_patch_start = max(0, i - patch_size)
        ref_patch_end = min(n - 1, i + patch_size)
        ref_patch = signal[ref_patch_start:ref_patch_end+1]

        weights_sum = 0
        values_sum = 0

        for j in range(n):
            if j == i:
                continue

            search_patch_start = max(0, j - patch_size)
            search_patch_end = min(n - 1, j + patch_size)
            search_patch = signal[search_patch_start:search_patch_end+1]

            distance = np.sum((ref_patch - search_patch) ** 2)
            weight = np.exp(-distance / (h ** 2))

            values_sum += weight * signal[j]
            weights_sum += weight

        denoised_signal[i] = values_sum / weights_sum

    return denoised_signal

其中，`signal`是待去噪的一维时序信号，`patch_size`是比较的局部块大小，`search_size`是寻找相似块的搜索窗口大小，`h`是过滤参数。该函数返回去噪后的一维时序信号。