Array.prototype.combs = function(num) {

    var str = this,
        length = str.length,
        of = Math.pow(2, length) - 1,
        out, combinations = [];

    while(of) {

        out = [];

        for(var i = 0, y; i < length; i++) {

            y = (1 << i);

            if(y & of && (y !== of))
                out.push(str[i]);

        }

        if (out.length >= num) {
           combinations.push(out);
        }

        of--;
    }

    return combinations;
}

下面是一个方法，它从一个随机长度的字符串中给出指定大小的所有组合。类似于昆玛斯的解，但适用于不同的输入和k。

代码可以更改为换行，即'dab'从输入'abcd' w k=3。

public void run(String data, int howMany){
    choose(data, howMany, new StringBuffer(), 0);
}


//n choose k
private void choose(String data, int k, StringBuffer result, int startIndex){
    if (result.length()==k){
        System.out.println(result.toString());
        return;
    }

    for (int i=startIndex; i<data.length(); i++){
        result.append(data.charAt(i));
        choose(data,k,result, i+1);
        result.setLength(result.length()-1);
    }
}

"abcde"的输出:

ABC abd ace ade BCD bce bde cde

这是一个简单的JS解决方案:

function getAllCombinations(n, k, f1) { indexes = Array(k); for (let i =0; i< k; i++) { indexes[i] = i; } var total = 1; f1(indexes); while (indexes[0] !== n-k) { total++; getNext(n, indexes); f1(indexes); } return {total}; } function getNext(n, vec) { const k = vec.length; vec[k-1]++; for (var i=0; i<k; i++) { var currentIndex = k-i-1; if (vec[currentIndex] === n - i) { var nextIndex = k-i-2; vec[nextIndex]++; vec[currentIndex] = vec[nextIndex] + 1; } } for (var i=1; i<k; i++) { if (vec[i] === n - (k-i - 1)) { vec[i] = vec[i-1] + 1; } } return vec; } let start = new Date(); let result = getAllCombinations(10, 3, indexes => console.log(indexes)); let runTime = new Date() - start; console.log({ result, runTime });

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' ]
]

遵循Haskell代码同时计算组合数和组合，由于Haskell的惰性，您可以得到其中的一部分而无需计算另一部分。

import Data.Semigroup
import Data.Monoid

data Comb = MkComb {count :: Int, combinations :: [[Int]]} deriving (Show, Eq, Ord)

instance Semigroup Comb where
    (MkComb c1 cs1) <> (MkComb c2 cs2) = MkComb (c1 + c2) (cs1 ++ cs2)

instance Monoid Comb where
    mempty = MkComb 0 []

addElem :: Comb -> Int -> Comb
addElem (MkComb c cs) x = MkComb c (map (x :) cs)

comb :: Int -> Int -> Comb
comb n k | n < 0 || k < 0 = error "error in `comb n k`, n and k should be natural number"
comb n k | k == 0 || k == n = MkComb 1 [(take k [k-1,k-2..0])]
comb n k | n < k = mempty
comb n k = comb (n-1) k <> (comb (n-1) (k-1) `addElem` (n-1))

它是这样工作的:

*Main> comb 0 1
MkComb {count = 0, combinations = []}

*Main> comb 0 0
MkComb {count = 1, combinations = [[]]}

*Main> comb 1 1
MkComb {count = 1, combinations = [[0]]}

*Main> comb 4 2
MkComb {count = 6, combinations = [[1,0],[2,0],[2,1],[3,0],[3,1],[3,2]]}

*Main> count (comb 10 5)
252

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)