最近在IronScripter网站上有一个PowerShell挑战，需要一个n- choice -k的解决方案。我在那里发布了一个解决方案，但这里有一个更通用的版本。

AllK开关用于控制输出是长度为ChooseK的组合，还是长度为1到ChooseK的组合。 Prefix参数实际上是输出字符串的累加器，但其效果是为初始调用传递的值实际上会为每一行输出添加前缀。

function Get-NChooseK
{

    [CmdletBinding()]

    Param
    (

        [String[]]
        $ArrayN

    ,   [Int]
        $ChooseK

    ,   [Switch]
        $AllK

    ,   [String]
        $Prefix = ''

    )

    PROCESS
    {
        # Validate the inputs
        $ArrayN = $ArrayN | Sort-Object -Unique

        If ($ChooseK -gt $ArrayN.Length)
        {
            Write-Error "Can't choose $ChooseK items when only $($ArrayN.Length) are available." -ErrorAction Stop
        }

        # Control the output
        $firstK = If ($AllK) { 1 } Else { $ChooseK }

        # Get combinations
        $firstK..$ChooseK | ForEach-Object {

            $thisK = $_

            $ArrayN[0..($ArrayN.Length-($thisK--))] | ForEach-Object {
                If ($thisK -eq 0)
                {
                    Write-Output ($Prefix+$_)
                }
                Else
                {
                    Get-NChooseK -Array ($ArrayN[($ArrayN.IndexOf($_)+1)..($ArrayN.Length-1)]) -Choose $thisK -AllK:$false -Prefix ($Prefix+$_)
                }
            }

        }
    }

}

例如:

PS C:\>$ArrayN  = 'E','B','C','A','D'
PS C:\>$ChooseK = 3
PS C:\>Get-NChooseK -ArrayN $ArrayN -ChooseK $ChooseK
ABC
ABD
ABE
ACD
ACE
ADE
BCD
BCE
BDE
CDE

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' ]
]

像Andrea Ambu一样用Python写的，但不是硬编码来选择三个。

def combinations(list, k):
    """Choose combinations of list, choosing k elements(no repeats)"""
    if len(list) < k:
        return []
    else:
        seq = [i for i in range(k)]
        while seq:
            print [list[index] for index in seq]
            seq = get_next_combination(len(list), k, seq)

def get_next_combination(num_elements, k, seq):
        index_to_move = find_index_to_move(num_elements, seq)
        if index_to_move == None:
            return None
        else:
            seq[index_to_move] += 1

            #for every element past this sequence, move it down
            for i, elem in enumerate(seq[(index_to_move+1):]):
                seq[i + 1 + index_to_move] = seq[index_to_move] + i + 1

            return seq

def find_index_to_move(num_elements, seq):
        """Tells which index should be moved"""
        for rev_index, elem in enumerate(reversed(seq)):
            if elem < (num_elements - rev_index - 1):
                return len(seq) - rev_index - 1
        return None   

我有一个用于project euler的排列算法，用python编写:

def missing(miss,src):
    "Returns the list of items in src not present in miss"
    return [i for i in src if i not in miss]


def permutation_gen(n,l):
    "Generates all the permutations of n items of the l list"
    for i in l:
        if n<=1: yield [i]
        r = [i]
        for j in permutation_gen(n-1,missing([i],l)):  yield r+j

If

n<len(l) 

你应该有所有你需要的组合，没有重复，你需要吗?

它是一个生成器，所以你可以这样使用它:

for comb in permutation_gen(3,list("ABCDEFGH")):
    print comb 

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)

不需要进行集合操作。这个问题几乎和循环K个嵌套循环一样，但你必须小心索引和边界(忽略Java和OOP的东西):

 public class CombinationsGen {
    private final int n;
    private final int k;
    private int[] buf;

    public CombinationsGen(int n, int k) {
        this.n = n;
        this.k = k;
    }

    public void combine(Consumer<int[]> consumer) {
        buf = new int[k];
        rec(0, 0, consumer);
    }

    private void rec(int index, int next, Consumer<int[]> consumer) {
        int max = n - index;

        if (index == k - 1) {
            for (int i = 0; i < max && next < n; i++) {
                buf[index] = next;
                next++;
                consumer.accept(buf);
            }
        } else {
            for (int i = 0; i < max && next + index < n; i++) {
                buf[index] = next;
                next++;
                rec(index + 1, next, consumer);
            }
        }
    }
}

像这样使用:

 CombinationsGen gen = new CombinationsGen(5, 2);

 AtomicInteger total = new AtomicInteger();
 gen.combine(arr -> {
     System.out.println(Arrays.toString(arr));
     total.incrementAndGet();
 });
 System.out.println(total);

获得预期的结果:

[0, 1]
[0, 2]
[0, 3]
[0, 4]
[1, 2]
[1, 3]
[1, 4]
[2, 3]
[2, 4]
[3, 4]
10

最后，将索引映射到您可能拥有的任何数据集。