在Python中，利用递归的优势和所有事情都是通过引用完成的事实。对于非常大的集合，这将占用大量内存，但其优点是初始集合可以是一个复杂的对象。它只会找到唯一的组合。

import copy

def find_combinations( length, set, combinations = None, candidate = None ):
    # recursive function to calculate all unique combinations of unique values
    # from [set], given combinations of [length].  The result is populated
    # into the 'combinations' list.
    #
    if combinations == None:
        combinations = []
    if candidate == None:
        candidate = []

    for item in set:
        if item in candidate:
            # this item already appears in the current combination somewhere.
            # skip it
            continue

        attempt = copy.deepcopy(candidate)
        attempt.append(item)
        # sorting the subset is what gives us completely unique combinations,
        # so that [1, 2, 3] and [1, 3, 2] will be treated as equals
        attempt.sort()

        if len(attempt) < length:
            # the current attempt at finding a new combination is still too
            # short, so add another item to the end of the set
            # yay recursion!
            find_combinations( length, set, combinations, attempt )
        else:
            # the current combination attempt is the right length.  If it
            # already appears in the list of found combinations then we'll
            # skip it.
            if attempt in combinations:
                continue
            else:
                # otherwise, we append it to the list of found combinations
                # and move on.
                combinations.append(attempt)
                continue
    return len(combinations)

你可以这样使用它。传递'result'是可选的，所以你可以用它来获取可能组合的数量…尽管这样做效率很低(最好通过计算来完成)。

size = 3
set = [1, 2, 3, 4, 5]
result = []

num = find_combinations( size, set, result ) 
print "size %d results in %d sets" % (size, num)
print "result: %s" % (result,)

您应该从测试数据中得到以下输出:

size 3 results in 10 sets
result: [[1, 2, 3], [1, 2, 4], [1, 2, 5], [1, 3, 4], [1, 3, 5], [1, 4, 5], [2, 3, 4], [2, 3, 5], [2, 4, 5], [3, 4, 5]]

如果你的集合是这样的，它也会工作得很好:

set = [
    [ 'vanilla', 'cupcake' ],
    [ 'chocolate', 'pudding' ],
    [ 'vanilla', 'pudding' ],
    [ 'chocolate', 'cookie' ],
    [ 'mint', 'cookie' ]
]

Python中的简短示例:

def comb(sofar, rest, n):
    if n == 0:
        print sofar
    else:
        for i in range(len(rest)):
            comb(sofar + rest[i], rest[i+1:], n-1)

>>> comb("", "abcde", 3)
abc
abd
abe
acd
ace
ade
bcd
bce
bde
cde

为了解释，递归方法用下面的例子描述:

示例:A B C D E 3的所有组合是:

A与其余2的所有组合(B C D E) B与其余2的所有组合(C D E) C与其余2的所有组合(D E)

c#简单算法。 (我发布它是因为我试图使用你们上传的那个，但由于某种原因我无法编译它——扩展一个类?所以我自己写了一个，以防别人遇到和我一样的问题)。 顺便说一下，除了基本的编程，我对c#没什么兴趣，但是这个工作得很好。

public static List<List<int>> GetSubsetsOfSizeK(List<int> lInputSet, int k)
        {
            List<List<int>> lSubsets = new List<List<int>>();
            GetSubsetsOfSizeK_rec(lInputSet, k, 0, new List<int>(), lSubsets);
            return lSubsets;
        }

public static void GetSubsetsOfSizeK_rec(List<int> lInputSet, int k, int i, List<int> lCurrSet, List<List<int>> lSubsets)
        {
            if (lCurrSet.Count == k)
            {
                lSubsets.Add(lCurrSet);
                return;
            }

            if (i >= lInputSet.Count)
                return;

            List<int> lWith = new List<int>(lCurrSet);
            List<int> lWithout = new List<int>(lCurrSet);
            lWith.Add(lInputSet[i++]);

            GetSubsetsOfSizeK_rec(lInputSet, k, i, lWith, lSubsets);
            GetSubsetsOfSizeK_rec(lInputSet, k, i, lWithout, lSubsets);
        }

GetSubsetsOfSizeK(set of type List<int>， integer k)

您可以修改它以遍历您正在处理的任何内容。

好运！

作为迭代器对象实现的MetaTrader MQL4非常快速的组合。

代码很容易理解。

我对很多算法进行了基准测试，这个算法真的非常快——大约比大多数next_combination()函数快3倍。

class CombinationsIterator { private: int input_array[]; // 1 2 3 4 5 int index_array[]; // i j k int m_elements; // N int m_indices; // K public: CombinationsIterator(int &src_data[], int k) { m_indices = k; m_elements = ArraySize(src_data); ArrayCopy(input_array, src_data); ArrayResize(index_array, m_indices); // create initial combination (0..k-1) for (int i = 0; i < m_indices; i++) { index_array[i] = i; } } // https://stackoverflow.com/questions/5076695 // bool next_combination(int &item[], int k, int N) bool advance() { int N = m_elements; for (int i = m_indices - 1; i >= 0; --i) { if (index_array[i] < --N) { ++index_array[i]; for (int j = i + 1; j < m_indices; ++j) { index_array[j] = index_array[j - 1] + 1; } return true; } } return false; } void getItems(int &items[]) { // fill items[] from input array for (int i = 0; i < m_indices; i++) { items[i] = input_array[index_array[i]]; } } };

测试上述迭代器类的驱动程序:

//+------------------------------------------------------------------+ //| | //+------------------------------------------------------------------+ // driver program to test above class #define N 5 #define K 3 void OnStart() { int myset[N] = {1, 2, 3, 4, 5}; int items[K]; CombinationsIterator comboIt(myset, K); do { comboIt.getItems(items); printf("%s", ArrayToString(items)); } while (comboIt.advance()); }

输出: 1 2 3 1 2 4 1 2 5 1 3 4 1 3 5 1 4 5 2 3 4 2 3 5 2 4 5 3 4 5

下面是一个简单易懂的递归c++解决方案:

#include<vector>
using namespace std;

template<typename T>
void ksubsets(const vector<T>& arr, unsigned left, unsigned idx,
    vector<T>& lst, vector<vector<T>>& res)
{
    if (left < 1) {
        res.push_back(lst);
        return;
    }
    for (unsigned i = idx; i < arr.size(); i++) {
        lst.push_back(arr[i]);
        ksubsets(arr, left - 1, i + 1, lst, res);
        lst.pop_back();
    }
}

int main()
{
    vector<int> arr = { 1, 2, 3, 4, 5 };
    unsigned left = 3;
    vector<int> lst;
    vector<vector<int>> res;
    ksubsets<int>(arr, left, 0, lst, res);
    // now res has all the combinations
}

也许我错过了重点(你需要的是算法，而不是现成的解决方案)，但看起来scala已经开箱即用了(现在):

def combis(str:String, k:Int):Array[String] = {
  str.combinations(k).toArray 
}

使用这样的方法:

  println(combis("abcd",2).toList)

会产生:

  List(ab, ac, ad, bc, bd, cd)