如何高效计算移位距离高斯映射numpy

import numpy as np

def shift_distance_gaussian_mapping(image, shift_distance, sigma):
    height, width = image.shape
    y, x = np.mgrid[0:height, 0:width]
    shift_y = y + shift_distance[1]
    shift_x = x + shift_distance[0]
    distance = np.sqrt((x - shift_x) ** 2 + (y - shift_y) ** 2)
    gaussian = np.exp(-distance ** 2 / (2 * sigma ** 2))
    mapped_image = np.zeros_like(image)
    for i in range(height):
        for j in range(width):
            mapped_image[i, j] = image[int(shift_y[i, j]), int(shift_x[i, j])] * gaussian[i, j]
    return mapped_image

# 示例用法
image = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
shift_distance = (1, 1)
sigma = 1.0
mapped_image = shift_distance_gaussian_mapping(image, shift_distance, sigma)
print(mapped_image)