这是我在这里的第一个问题，它是关于在Python中使用numpy库的。我有一个函数，它可以获得带有x，y坐标的三维numpy数组（np.array）。该函数的逻辑-将该数组从较小的坐标重新排序为较大的坐标

import numpy as np
def reorder(points):
    # reshaping array
    points = points.reshape((4, 2))
    # creating empty output array
    points_new = np.zeros((4, 1, 2), np.uint8)
    # summing the values
    add = points.sum(1)
    # find difference
    diff = np.diff(points, axis=1)
    # with the smaller sum will be first, the maximum will be last
    points_new[0] = points[np.argmin(add)]
    points_new[3] = points[np.argmax(add)]
    # the smaller difference will be the second, the max difference - the third
    points_new[1] = points[np.argmin(diff)]
    points_new[2] = points[np.argmax(diff)]
    return points_new

字符串
但是使用这个功能之后

input_data = np.array([[[ 573,  148]], [[  25,  223]], [[ 153, 1023]], [[ 730,  863]]])
output_data = reorder(data)

型
我得到了奇怪的结果

np.array([[[ 25, 223]], [[ 61, 148]], [[153, 255]], [[218,  95]]])

型
如您所见，在新数组output * data中，数据已更改，但应包含与input * data相同的值
我用简单列表重写了这个函数

def reorder_by_lst(points):
    # reshaping array
    points = points.reshape((4, 2))
    # summing the values
    add = points.sum(1)
    # find difference
    diff = np.diff(points, axis=1)
    # with the smaller sum will be first, the maximum will be last
    a = points[np.argmin(add)]
    d = points[np.argmax(add)]
    # the smaller difference will be the second, the max difference - the third
    b = points[np.argmin(diff)]
    c = points[np.argmax(diff)]
    lst = [a, b, c, d]
    return np.array(lst)

型
用过之后

input_data = np.array([[[ 573,  148]], [[  25,  223]], [[ 153, 1023]], [[ 730,  863]]])
output_data = reorder_by_lst(data)

型
我得到了这个结果

np.array([[  25,  223], [ 730,  863], [ 573,  148], [ 153, 1023]])

型
现在的结果是一样的，只有维度应该是固定的。这似乎是一个错误，但也许这是深功能，我不知道。我需要一个专业社区的意见。
P.S. Python版本- 3.10，Numpy版本- 1.23.5