Python 带副本的 Numpy 数组赋值
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Numpy array assignment with copy
提问by mrgloom
For example, if we have a numpyarray A, and we want a numpyarray Bwith the same elements.
例如，如果我们有一个numpy数组A，并且我们想要一个具有相同元素的numpy数组B。
What is the difference between the following (see below) methods? When is additional memory allocated, and when is it not?
以下（见下文）方法之间有什么区别？什么时候分配额外的内存，什么时候不分配？
B = AB[:] = A(same asB[:]=A[:]?)numpy.copy(B, A)
B = AB[:] = A（一样B[:]=A[:]？）numpy.copy(B, A)
采纳答案by Blckknght
All three versions do different things:
所有三个版本都做不同的事情：
B = AThis binds a new name
Bto the existing object already namedA. Afterwards they refer to the same object, so if you modify one in place, you'll see the change through the other one too.B[:] = A(same asB[:]=A[:]?)This copies the values from
Ainto an existing arrayB. The two arrays must have the same shape for this to work.B[:] = A[:]does the same thing (butB = A[:]would do something more like 1).numpy.copy(B, A)This is not legal syntax. You probably meant
B = numpy.copy(A). This is almost the same as 2, but it creates a new array, rather than reusing theBarray. If there were no other references to the previousBvalue, the end result would be the same as 2, but it will use more memory temporarily during the copy.Or maybe you meant
numpy.copyto(B, A), which is legal, and is equivalent to 2?
B = A这会将新名称绑定
B到已命名的现有对象A。之后它们会引用同一个对象，因此如果您就地修改一个对象，您也会通过另一个对象看到更改。B[:] = A（一样B[:]=A[:]？）这会将值复制
A到现有数组中B。这两个数组必须具有相同的形状才能工作。B[:] = A[:]做同样的事情（但B = A[:]会做更像 1 的事情）。numpy.copy(B, A)这不是合法的语法。你可能的意思是
B = numpy.copy(A). 这与 2 几乎相同，但它创建了一个新数组，而不是重用该B数组。如果没有其他对前一个B值的引用，则最终结果将与 2 相同，但在复制期间会临时使用更多内存。或者你的意思是
numpy.copyto(B, A)，这是合法的，相当于 2？
回答by Mailerdaimon
B=Acreates a referenceB[:]=Amakes a copynumpy.copy(B,A)makes a copy
B=A创建参考B[:]=A复印numpy.copy(B,A)复印
the last two need additional memory.
最后两个需要额外的内存。
To make a deep copy you need to use B = copy.deepcopy(A)
要制作深拷贝，您需要使用 B = copy.deepcopy(A)
回答by Woeitg
This is the only working answer for me:
这是对我来说唯一有效的答案：
B=numpy.array(A)
