[英]Values of variables inside a for-loop
I have an array a
defined outside a for-loop. 我有一个数组
a
for循环以外定义。 b
is a variable assigned to be equal to a
inside the loop. b
是分配为等于变量a
循环内。 I change the values of b
inside the loop which also alters a
. 我在循环内更改
b
的值,这也会更改a
。 Why/How does this happen? 为什么/如何发生?
>>> import numpy as np
>>> a = np.asarray(range(10))
>>> for i in range(5,7):
b = a #assign b to be equal to a
b[b<i]=0 #alter b
b[b>=i]=1
print a
Output: 输出:
[0 0 0 0 0 1 1 1 1 1] #Unexpected!!
[0 0 0 0 0 0 0 0 0 0]
Why is a
altered when I don't explicitly do so? 为什么是
a
改变的时候,我不明确为什么这么做?
Because when you do b = a
only the reference gets copied. 因为当您执行
b = a
仅引用被复制。 Both a
and b
point to the same object. a
和b
指向同一个对象。
If you really want to create a copy of a
you need to do for example: 如果你真的想创建的副本
a
你需要,例如做:
import copy
...
b = copy.deepcopy(a)
numpy.asarray
is mutable so, a
and b
pointed one location. numpy.asarray
是可变的,因此a
和b
指向一个位置。
>>> a = [1,2,3]
>>> b = a
>>> id(a)
140435835060736
>>> id(b)
140435835060736
You can fix like this b = a[:]
or b = copy.deepcopy(a)
您可以像这样修复
b = a[:]
或b = copy.deepcopy(a)
Use the slice operator to make a copy. 使用切片运算符进行复制。
=
just gives it another name as it copies references. =
只是在复制引用时给它另一个名称。
b = a[:]
Will work fine. 将正常工作。
According to @AshwiniChaudhary's comment, this won't work for Numpy arrays, the solution in this case is to 根据@AshwiniChaudhary的评论,这不适用于Numpy数组,这种情况下的解决方案是
b = copy.deepcopy(a)
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