自定义高斯核

size为一个数表示一维高斯核，两个数的列表表示二维高斯核。

import numpy as np

def gaussian_filter(size, sigma):
    if type(size) == int:
        siz = int((size - 1) / 2)
        x = np.array(range(-siz, siz + 1))
        arg = -x ** 2 / (2 * sigma ** 2)
        h = np.exp(arg)
        sumh = np.sum(h)
        h = h / sumh
    elif type(size) == list:
        siz0 = int((size[0] - 1) / 2)
        siz1 = int((size[1] - 1) / 2)
        x = np.array(range(-siz0, siz0 + 1))
        y = np.array(range(-siz1, siz1 + 1))
        [x, y] = np.meshgrid(x, y)
        arg = -(x ** 2 + y ** 2) / (2 * sigma ** 2)
        h = np.exp(arg)
        sumh = np.sum(h)
        h = h / sumh
    return np.round(h, 4)

对数据进行滤波

f = gaussian_filter(5, 0,6)
data_fed = np.convolve(data, f, mode="same")