python中对多层for循环的优化

Question

问题遇到的现象和发生背景

这里有一个三层的for循环，运行速度想要优化一下

问题相关代码，请勿粘贴截图

for i in range(len(points_xy)):
    weight_t=1
    x_pos = int((points_xy[i][0] - x_min2) / abs(x_res2))
    y_pos = int((y_max2 - points_xy[i][1]) / abs(x_res2))
    # 先搜索以点为中心正方形区域，再在里面搜索圆形
    y_len_min = (y_pos - radius_pixel_width - 1) if (y_pos - radius_pixel_width - 1) > 0 else 0
    y_len_max = (y_pos + radius_pixel_width + 1) if (y_pos + radius_pixel_width + 1) < row else row

    x_len_min = (x_pos - radius_pixel_width - 1) if (x_pos - radius_pixel_width - 1) > 0 else 0
    x_len_max = (x_pos + radius_pixel_width + 1) if (x_pos + radius_pixel_width + 1) < col else col
    for y in range(y_len_min, y_len_max):
        for x in range(x_len_min, x_len_max):
            distance = float(((x - x_pos) ** 2 + (y - y_pos) ** 2) ** 0.5)
            dis=distance*30
            if (distance < radius_pixel_width and distance > 0):
                value = raster_data[y_pos][x_pos]

                D_value=((radius_pixel_width - distance + 1)/(radius_pixel_width**2))*weight_t

                if (result_data[y][x] != -999.0):
                    result_data[y][x] += D_value
                else:
                    result_data[y][x] = D_value
            elif(distance==0 and result_data[y][x] != -999.0):
                result_data[y][x]+=(1*weight_t)

            elif(distance==0 and result_data[y][x] == -999.0):
                result_data[y][x] = 1*weight_t

运行结果及报错内容

我的解答思路和尝试过的方法

一开始加上jit，但是结果告诉我这里的point_xy是list好像不能用,我又把jit放在for循环内部，结果还是程序一直运行。问问怎么优化

for i in range(len(points_xy)):

    x_pos = int((points_xy[i][0] - x_min) / abs(x_res))
    y_pos = int((y_max - points_xy[i][1]) / abs(x_res))
    # 先搜索以点为中心正方形区域，再在里面搜索圆形
    y_len_min = (y_pos - radius_pixel_width - 1) if (y_pos - radius_pixel_width - 1) > 0 else 0
    y_len_max = (y_pos + radius_pixel_width + 1) if (y_pos + radius_pixel_width + 1) < rows else rows

    x_len_min = (x_pos - radius_pixel_width - 1) if (x_pos - radius_pixel_width - 1) > 0 else 0
    x_len_max = (x_pos + radius_pixel_width + 1) if (x_pos + radius_pixel_width + 1) < cols else cols

    @jit
    def keral_map(y_len_min, y_len_max, x_len_min, x_len_max, x_pos, y_pos, radius_pixel_width, result_data):
        weight_t = 1
        for y in range(y_len_min, y_len_max):
            for x in range(x_len_min, x_len_max):
                distance = float(((x - x_pos) ** 2 + (y - y_pos) ** 2) ** 0.5)
                # 判断在半径内
                if (distance < radius_pixel_width and distance > 0):

                    D_value = ((radius_pixel_width - distance + 1) / (radius_pixel_width ** 2)) * weight_t

                    if (result_data[y][x] != -999.0):
                        result_data[y][x] += D_value
                    else:
                        result_data[y][x] = D_value
                elif (distance == 0 and result_data[y][x] != -999.0):
                    result_data[y][x] += (1 * weight_t)
                elif (distance == 0 and result_data[y][x] == -999.0):
                    result_data[y][x] = 1 * weight_t
        return result_data

    keral_map(y_len_min, y_len_max, x_len_min, x_len_max, x_pos, y_pos, radius_pixel_width, result_data)

我想要达到的结果

目前的速度大概都在25秒左右（6万个点），想能不能快一点