我正在尝试使用 NumPy 制作 Python 程序，但遇到了问题:
I'm trying to make a Python program with NumPy, but I ran into a problem:
width, height, pngData, metaData = png.Reader(file).asDirect()
planeCount = metaData['planes']
print('Bildgroesse: ' + str(width) + 'x' + str(height) + ' Pixel')
image_2d = np.vstack(list(map(np.uint8, pngData)))
imageOriginal_3d = np.reshape(image_2d, (width, height, planeCount))
imageEdited_3d = imageOriginal_3d
这是我的代码，用于读取 PNG 图像.现在我想编辑 imageEdited_3d 而不是 imageOriginal_3d，像这样:
This is my code, to read in a PNG image. Now I want to edit imageEdited_3d but NOT imageOriginal_3d, like this:
imageEdited_3d[x,y,0] = 255
但是 imareOriginal_3d 变量的值与 imageEdited_3d 相同...
But then the imareOriginal_3d variable has the same values as the imageEdited_3d one...
有谁知道，我该如何解决这个问题?所以它不仅创建了一个引用，而且创建了一个真实的副本?:/
Does anyone know, how I can fix this? So it doesn't only creates a reference, but it creates a real copy? :/
你需要创建对象的副本.您可以使用 numpy.copy() 因为你有 numpy 对象.因此，您的初始化应该是这样的:
You need to create the copy of the object. You may do it using numpy.copy() since you are having numpy object. Hence, your initialisation should be like:
imageEdited_3d = imageOriginal_3d.copy()
还有 copy 模块用于创建深拷贝或浅拷贝.这与对象类型无关.例如，您使用 copy 的代码应为:
Also there is copy module for creating the deep copy OR, shallow copy. This works independent of object type. For example, your code using copy should be as:
from copy import copy, deepcopy
# Creates shallow copy of object
imageEdited_3d = copy(imageOriginal_3d)
# Creates deep copy of object
imageEdited_3d = deepcopy(imageOriginal_3d)
说明:
浅拷贝构造一个新的复合对象，然后(到尽可能)将引用插入其中找到的对象原件.
A shallow copy constructs a new compound object and then (to the extent possible) inserts references into it to the objects found in the original.
深拷贝构造一个新的复合对象，然后递归地，将原始对象中的对象的副本插入其中.
A deep copy constructs a new compound object and then, recursively, inserts copies into it of the objects found in the original.
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