问题描述
我一直令人头大我的脑子出3个小时了，但我还是不明白这一点，所以我问在这里。 （我在标题中写道Python的，但是这可能是pretty太多任何语言）
I have been wracking my brains out for 3 hours straight, but I still don't get it, so I am asking here. (I wrote Python in the title, but this could be for pretty much any language)
让我们假设我有一组位（但它也可以是在一个确定的范围内的整数）的固定长度为n的，让我们说5
Let's assume I have an array of bits (but it may also be integers in a defined range) of fixed length n, let's say 5.
array=[0,1,1,0,0]
现在，我怎么产生的所有阵列，这在数量范围是可能的（以比特的情况下，2）。
Now, how do I generate ALL arrays, which are possible in the number range (in the case of bits, 2).
所以：
[0,0,0,0,0], [0,0,0,0,1], [0,0,0,1,0], [0,0,0,1,1] ...
我试图寻找这里的解决方案，但我总能找到的东西是相似的，但并不完全解决我的问题。
I have tried searching for a solution here, but I always find something which is similar, but which doesn't quite solve my problem.
要解决这个问题，我已经试过各种循环，但我总是最后要么得到一个可能不止一次（不应发生），或者没有得到所有可能的。
To solve this, I have tried various loops, but I always end up either getting one possibility more than once (should not happen), or not getting all possible ones.
我可以管理与if语句（检查组合已经存在），要做到这一点，但似乎很不成熟。
I can manage to do this with if statements (to check if a combination already exists), but that seems very unsophisticated.
有没有一种简单的方法，只使用循环，获得所有的可能性？
Is there a simple method, using only loops, to obtain all possibilities?
感谢您
编辑：由于这是下面提到的，不，这不是功课。这对于研究，以实现二进制状态的贝叶斯网络。 （开/关）。
Since this was mentioned below, no, this is not homework. This is for research in order to implement a Bayesian network of binary states. (on/off).
推荐答案
在Python中，使用和itertools 像这样的东西。
In Python, use itertools for stuff like this
from itertools import product
for i in product([0,1], repeat=5):
print i
收益率：
(0, 0, 0, 0, 0)
(0, 0, 0, 0, 1)
(0, 0, 0, 1, 0)
(0, 0, 0, 1, 1)
(0, 0, 1, 0, 0)
etc...
这篇关于我该如何计算的数字/位的阵列中所有的可能性（在python，或任何与此有关的语言）的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！