计算中的不一致性-Python&；努比

我尝试运行的代码是：

import numpy as np
x = [np.array([[          0,     0.66111,       0.325,    0.061111,    0.070833]],        dtype=np.float32), np.array([     2.6026], dtype=np.float32), np.array([    -84.806], dtype=np.float32)]
ratio, w, h, pad  = (1.0, 1.0) ,640 ,426 ,(0.0, 107.0)

labels = x.copy()
print('labels before computation', labels[0])
print(ratio[0] * w * (x[0][:, 1] + x[0][:, 3] / 2) + pad[0])
print(ratio[1] * h * (x[0][:, 2] + x[0][:, 4] / 2) + pad[1])
labels[0][:, 1] = ratio[0] * w * (x[0][:, 1] - x[0][:, 3] / 2) + pad[0]  
labels[0][:, 2] = ratio[1] * h * (x[0][:, 2] - x[0][:, 4] / 2) + pad[1]  
labels[0][:, 3] = ratio[0] * w * (x[0][:, 1] + x[0][:, 3] / 2) + pad[0]
labels[0][:, 4] = ratio[1] * h * (x[0][:, 2] + x[0][:, 4] / 2) + pad[1]
print('labels after computation', labels[0])

输出为：

labels before computation [[0.       0.66111  0.325    0.061111 0.070833]]
[442.6659]
[260.5374]
labels after computation [[0.0000000e+00 4.0355487e+02 2.3036258e+02 2.5829467e+05 9.8256547e+04]]

第2条和第3条语句打印的值是正确的。但是，当我试图将同一计算输出的值分别分配给标签[0][：，3]和标签[0][：，4]时，会分配一些垃圾值

如果我删除第9行和第10行中的赋值操作并运行以下代码，则输出正常

import numpy as np

x = [np.array([[          0,     0.66111,       0.325,    0.061111,    0.070833]], dtype=np.float32), np.array([     2.6026], dtype=np.float32), np.array([    -84.806], dtype=np.float32)]
ratio, w, h, pad  = (1.0, 1.0) ,640 ,426 ,(0.0, 107.0)

labels = x.copy()
print('labels before computation', labels[0])
print(ratio[0] * w * (x[0][:, 1] + x[0][:, 3] / 2) + pad[0])
print(ratio[1] * h * (x[0][:, 2] + x[0][:, 4] / 2) + pad[1])
labels[0][:, 3] = ratio[0] * w * (x[0][:, 1] + x[0][:, 3] / 2) + pad[0]
labels[0][:, 4] = ratio[1] * h * (x[0][:, 2] + x[0][:, 4] / 2) + pad[1]
print('labels after computation', labels[0])

输出：

labels before computation [[0.       0.66111  0.325    0.061111 0.070833]]
[442.6659]
[260.5374]
labels after computation [[0.000000e+00 6.611100e-01 3.250000e-01 4.426659e+02 2.605374e+02]]

labels before computation [[0.       0.66111  0.325    0.061111 0.070833]]
[442.66592]
[260.537429]
labels after computation [[  0.       403.55488  230.362571 442.66592  260.537429]]

有人能解释不一致背后的原因吗

我的环境：
Python版本：3.6.9
Numpy版本：1.19.4

谢谢

labels = x.copy()

您只需创建

x

的浅层副本，该副本的元素为数组，因此更改

标签[0][：，1]

和

标签[0][：，2]

会更改

x

中的相同字段

同时检查

复制功能的功能：

请注意，np.copy是一个浅复制，不会复制数组中的对象元素。这对于包含Python对象的数组非常重要。新数组将包含相同的对象，如果该对象可以修改（是可变的），则可能会导致意外：

解决方案是：

要确保复制对象数组中的所有元素，请使用copy.deepcopy：

就你而言：

import numpy as np
x = [np.array([[          0,     0.66111,       0.325,    0.061111,    0.070833]],        dtype=np.float32), np.array([     2.6026], dtype=np.float32), np.array([    -84.806], dtype=np.float32)]
ratio, w, h, pad  = (1.0, 1.0) ,640 ,426 ,(0.0, 107.0)
import copy
labels = copy.deepcopy(x)
print('labels before computation', labels[0])
print(ratio[0] * w * (x[0][:, 1] + x[0][:, 3] / 2) + pad[0])
print(ratio[1] * h * (x[0][:, 2] + x[0][:, 4] / 2) + pad[1])
labels[0][:, 1] = ratio[0] * w * (x[0][:, 1] - x[0][:, 3] / 2) + pad[0]
labels[0][:, 2] = ratio[1] * h * (x[0][:, 2] - x[0][:, 4] / 2) + pad[1]
labels[0][:, 3] = ratio[0] * w * (x[0][:, 1] + x[0][:, 3] / 2) + pad[0]
labels[0][:, 4] = ratio[1] * h * (x[0][:, 2] + x[0][:, 4] / 2) + pad[1]
print('labels after computation', labels[0])

输出：

labels before computation [[0.       0.66111  0.325    0.061111 0.070833]]
[442.6659]
[260.5374]
labels after computation [[0.000000e+00 6.611100e-01 3.250000e-01 4.426659e+02 2.605374e+02]]

labels before computation [[0.       0.66111  0.325    0.061111 0.070833]]
[442.66592]
[260.537429]
labels after computation [[  0.       403.55488  230.362571 442.66592  260.537429]]