以有效的方式查找 PowerSet 的特定子集

发布于 2024-12-06 03:06:40 字数 697 浏览 0 评论 0原文

我正在尝试找到一种有效的方法来获取 PowerSet 的一组子集。

例如,当集合大小很小时,这可以工作:

Set<Integer> set = new HashSet<Integer>();
set.add(1);
set.add(2);
set.add(3);

Set<Integer> set2 = new HashSet<Integer>();
set2.add(3);


Set<Set<Integer>> sets = MyUtils.powerSet(set); //size - 8 SubSets
Set<Set<Integer>> badSets = MyUtils.powerSet(set2); //size - 2 SubSets

//my set of subsets of the powerset
sets.removeAll(badSets) //size - 6 SubSets

但是,当将更多元素添加到这些集合中时,这就不实用了。还有其他方法可以做到这一点吗?

友情提醒一下 PowerSet 是什么:

{a,b,c} 的 PowerSet:

P(S) = { {}, {a}, {b}, {c}, {a, b}, {a, c }, {b, c}, {a, b, c} }

I'm trying to find an efficient way to grab a Set of Subsets of a PowerSet.

For example, this works when the set sizes are small:

Set<Integer> set = new HashSet<Integer>();
set.add(1);
set.add(2);
set.add(3);

Set<Integer> set2 = new HashSet<Integer>();
set2.add(3);


Set<Set<Integer>> sets = MyUtils.powerSet(set); //size - 8 SubSets
Set<Set<Integer>> badSets = MyUtils.powerSet(set2); //size - 2 SubSets

//my set of subsets of the powerset
sets.removeAll(badSets) //size - 6 SubSets

However when more elements are added to these sets this does not become practical. Is there another way to do this?

Just friendly reminder of what a PowerSet is:

PowerSet of {a,b,c}:

P(S) = { {}, {a}, {b}, {c}, {a, b}, {a, c}, {b, c}, {a, b, c} }

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评论(4

迷离° 2024-12-13 03:06:41

尝试另一种方法:

let call set3 = set - set2;

然后 Powerset(set) - Poserset(set2) = Powerset(set3) x (Powerset(set)- {});

其中 x 是 2 集的笛卡尔倍数。

如果set3有x元素,set2有y元素,那么使用这种方法,复杂度约为2^(x+y),而如果尝试直接删除它,复杂度约为2^(x + 2Y)。

哈。

Try another way:

let call set3 = set - set2;

Then Powerset(set) - Poserset(set2) = Powerset(set3) x (Powerset(set)- {});

where x here is Descartes multiple of 2 set.

if set3 has x element, set2 has y element, then with this approach, it's complexity around 2^(x+y), while if try to remove it directly, the complexity is around 2^(x + 2Y).

Hth.

梦明 2024-12-13 03:06:41

听起来像是零抑制决策图的工作。它们支持集合减法,并且在 ZDD 中创建一系列数字的幂集是微不足道的(事实上,生成的 ZDD 具有很少的节点)。这意味着非对称差异也会运行得很快,因为它是在两个小的 ZDD 上,并且它仅取决于节点中 ZDD 的大小,而不取决于它们包含的集合数量的大小。我不知道接下来要做什么,但无论它是什么,您总是可以枚举 ZDD 中的所有集合并将它们放入其他数据结构中。

Sounds like a job for zero suppressed decision diagrams. They support set-subtraction and creating a powerset of a range of numbers is trivial in ZDD's (and in fact the resulting ZDD has very few nodes). That means that the asymmetric difference will also run fast, because it's on two small ZDD's and it depends only on the size of the ZDD's in nodes, not the size in number of sets they contain. I don't know what you're going to do with it next, but whatever it is, you could always enumerate all sets in the ZDD and put them in an other datastructure.

酸甜透明夹心 2024-12-13 03:06:41

为了从一个幂集减去另一个幂集,扣除的幂集计算是多余的。方法如下:

public static <T>void removePowerSet(
        Collection <? extends Collection <T>> powerSet,
        Collection <T> removedComponents){
    Iterator <? extends Collection <T>> powerSetIter = powerSet.iterator();
    while (powerSetIter.hasNext()) {
        Collection <T> powerSetSubset = powerSetIter.next();
        if (removedComponents.containsAll(powerSetSubset)) {
            powerSetIter.remove();
        }
    }
}

对于 HashSet,该算法的执行时间为多项式时间 - O(n2)

现在您可以调用 removePowerSet(sets, set2)removePowerSet(sets, Arrays.asList(3)) 以获取示例中的结果。

For subtracting one power set from another, deducted power set computataion is redundant. Here is the way to go:

public static <T>void removePowerSet(
        Collection <? extends Collection <T>> powerSet,
        Collection <T> removedComponents){
    Iterator <? extends Collection <T>> powerSetIter = powerSet.iterator();
    while (powerSetIter.hasNext()) {
        Collection <T> powerSetSubset = powerSetIter.next();
        if (removedComponents.containsAll(powerSetSubset)) {
            powerSetIter.remove();
        }
    }
}

This algorithm performs in a polynomial time - O(n2) for a HashSet

Now you can call removePowerSet(sets, set2) or removePowerSet(sets, Arrays.asList(3)) to get the result in your example.

蝶舞 2024-12-13 03:06:40

如果从 P(A) 中删除 P(B) 后,一组是另一组的子集(A、B 大小为 m、n),则有 2n - 2m 元素,如果 B 不是 A 的子集,您也可以假设 B'=A 与 B 的交集,我们也有类似的关系,所以数字总体上很大。

例如假设 AB 有一个元素 |P(A)-P(B)| = 2n - 2(n-1) = 2(n-1),例如,对于 n = 40,您无法迭代超过所有项目。

无论如何,一种方法如下:

有一个以 2 为基数、大小为 n 的计数器,首先将 m+1 位设置为 1,将所有其他位设置为 0,然后打印结果,然后每次增加计数器(加一)并打印结果最多为 2n - 1。其时间复杂度为 O(2n - 2m)。

If one set is subset of another one (A,B sizes m,n) after removing P(B) from P(A) you have 2n - 2m element, also if B is not a subset of A, again you can assume B'=A intersection with B and again we have similar relation, so numbers are big in all.

for example assume A-B has one element, |P(A)-P(B)| = 2n - 2(n-1) = 2(n-1), for example for n = 40 you can't iterate over all items.

anyway, one way is as bellow:

have a counter of size n in base 2, first set m+1 bit as 1 and all others as 0 then print result, and each time increase counter (by one) and print result upto rich to 2n - 1. which is O(2n - 2m).

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