我想写一个函数,它以一个字母数组作为参数,并从中选择一些字母。

假设您提供了一个包含8个字母的数组,并希望从中选择3个字母。那么你应该得到:

8! / ((8 - 3)! * 3!) = 56

数组(或单词),每个数组由3个字母组成。


当前回答

简短快速的c#实现

public static IEnumerable<IEnumerable<T>> Combinations<T>(IEnumerable<T> elements, int k)
{
    return Combinations(elements.Count(), k).Select(p => p.Select(q => elements.ElementAt(q)));                
}      

public static List<int[]> Combinations(int setLenght, int subSetLenght) //5, 3
{
    var result = new List<int[]>();

    var lastIndex = subSetLenght - 1;
    var dif = setLenght - subSetLenght;
    var prevSubSet = new int[subSetLenght];
    var lastSubSet = new int[subSetLenght];
    for (int i = 0; i < subSetLenght; i++)
    {
        prevSubSet[i] = i;
        lastSubSet[i] = i + dif;
    }

    while(true)
    {
        //add subSet ad result set
        var n = new int[subSetLenght];
        for (int i = 0; i < subSetLenght; i++)
            n[i] = prevSubSet[i];

        result.Add(n);

        if (prevSubSet[0] >= lastSubSet[0])
            break;

        //start at index 1 because index 0 is checked and breaking in the current loop
        int j = 1;
        for (; j < subSetLenght; j++)
        {
            if (prevSubSet[j] >= lastSubSet[j])
            {
                prevSubSet[j - 1]++;

                for (int p = j; p < subSetLenght; p++)
                    prevSubSet[p] = prevSubSet[p - 1] + 1;

                break;
            }
        }

        if (j > lastIndex)
            prevSubSet[lastIndex]++;
    }

    return result;
}

其他回答

下面是一个使用宏的Lisp方法。这适用于Common Lisp,也适用于其他Lisp方言。

下面的代码创建了'n'个嵌套循环,并为列表lst中的'n'个元素的每个组合执行任意代码块(存储在body变量中)。变量var指向一个包含用于循环的变量的列表。

(defmacro do-combinations ((var lst num) &body body)
  (loop with syms = (loop repeat num collect (gensym))
        for i on syms
        for k = `(loop for ,(car i) on (cdr ,(cadr i))
                         do (let ((,var (list ,@(reverse syms)))) (progn ,@body)))
                then `(loop for ,(car i) on ,(if (cadr i) `(cdr ,(cadr i)) lst) do ,k)
        finally (return k)))

让我们看看…

(macroexpand-1 '(do-combinations (p '(1 2 3 4 5 6 7) 4) (pprint (mapcar #'car p))))

(LOOP FOR #:G3217 ON '(1 2 3 4 5 6 7) DO
 (LOOP FOR #:G3216 ON (CDR #:G3217) DO
  (LOOP FOR #:G3215 ON (CDR #:G3216) DO
   (LOOP FOR #:G3214 ON (CDR #:G3215) DO
    (LET ((P (LIST #:G3217 #:G3216 #:G3215 #:G3214)))
     (PROGN (PPRINT (MAPCAR #'CAR P))))))))

(do-combinations (p '(1 2 3 4 5 6 7) 4) (pprint (mapcar #'car p)))

(1 2 3 4)
(1 2 3 5)
(1 2 3 6)
...

由于默认情况下不存储组合,因此存储空间保持在最小值。选择主体代码而不是存储所有结果的可能性也提供了更大的灵活性。

这是我用c++写的命题

我尽可能少地限制迭代器类型,所以这个解决方案假设只有前向迭代器,它可以是const_iterator。这应该适用于任何标准容器。在参数没有意义的情况下,它抛出std:: invalid_argument

#include <vector>
#include <stdexcept>

template <typename Fci> // Fci - forward const iterator
std::vector<std::vector<Fci> >
enumerate_combinations(Fci begin, Fci end, unsigned int combination_size)
{
    if(begin == end && combination_size > 0u)
        throw std::invalid_argument("empty set and positive combination size!");
    std::vector<std::vector<Fci> > result; // empty set of combinations
    if(combination_size == 0u) return result; // there is exactly one combination of
                                              // size 0 - emty set
    std::vector<Fci> current_combination;
    current_combination.reserve(combination_size + 1u); // I reserve one aditional slot
                                                        // in my vector to store
                                                        // the end sentinel there.
                                                        // The code is cleaner thanks to that
    for(unsigned int i = 0u; i < combination_size && begin != end; ++i, ++begin)
    {
        current_combination.push_back(begin); // Construction of the first combination
    }
    // Since I assume the itarators support only incrementing, I have to iterate over
    // the set to get its size, which is expensive. Here I had to itrate anyway to  
    // produce the first cobination, so I use the loop to also check the size.
    if(current_combination.size() < combination_size)
        throw std::invalid_argument("combination size > set size!");
    result.push_back(current_combination); // Store the first combination in the results set
    current_combination.push_back(end); // Here I add mentioned earlier sentinel to
                                        // simplyfy rest of the code. If I did it 
                                        // earlier, previous statement would get ugly.
    while(true)
    {
        unsigned int i = combination_size;
        Fci tmp;                            // Thanks to the sentinel I can find first
        do                                  // iterator to change, simply by scaning
        {                                   // from right to left and looking for the
            tmp = current_combination[--i]; // first "bubble". The fact, that it's 
            ++tmp;                          // a forward iterator makes it ugly but I
        }                                   // can't help it.
        while(i > 0u && tmp == current_combination[i + 1u]);

        // Here is probably my most obfuscated expression.
        // Loop above looks for a "bubble". If there is no "bubble", that means, that
        // current_combination is the last combination, Expression in the if statement
        // below evaluates to true and the function exits returning result.
        // If the "bubble" is found however, the ststement below has a sideeffect of 
        // incrementing the first iterator to the left of the "bubble".
        if(++current_combination[i] == current_combination[i + 1u])
            return result;
        // Rest of the code sets posiotons of the rest of the iterstors
        // (if there are any), that are to the right of the incremented one,
        // to form next combination

        while(++i < combination_size)
        {
            current_combination[i] = current_combination[i - 1u];
            ++current_combination[i];
        }
        // Below is the ugly side of using the sentinel. Well it had to haave some 
        // disadvantage. Try without it.
        result.push_back(std::vector<Fci>(current_combination.begin(),
                                          current_combination.end() - 1));
    }
}

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' ]
]

这是一个优雅的Scala通用实现,如99个Scala问题所述。

object P26 {
  def flatMapSublists[A,B](ls: List[A])(f: (List[A]) => List[B]): List[B] = 
    ls match {
      case Nil => Nil
      case sublist@(_ :: tail) => f(sublist) ::: flatMapSublists(tail)(f)
    }

  def combinations[A](n: Int, ls: List[A]): List[List[A]] =
    if (n == 0) List(Nil)
    else flatMapSublists(ls) { sl =>
      combinations(n - 1, sl.tail) map {sl.head :: _}
    }
}

在VB。Net,该算法从一组数字(PoolArray)中收集n个数字的所有组合。例如,从“8,10,20,33,41,44,47”中选择5个选项的所有组合。

Sub CreateAllCombinationsOfPicksFromPool(ByVal PicksArray() As UInteger, ByVal PicksIndex As UInteger, ByVal PoolArray() As UInteger, ByVal PoolIndex As UInteger)
    If PicksIndex < PicksArray.Length Then
        For i As Integer = PoolIndex To PoolArray.Length - PicksArray.Length + PicksIndex
            PicksArray(PicksIndex) = PoolArray(i)
            CreateAllCombinationsOfPicksFromPool(PicksArray, PicksIndex + 1, PoolArray, i + 1)
        Next
    Else
        ' completed combination. build your collections using PicksArray.
    End If
End Sub

        Dim PoolArray() As UInteger = Array.ConvertAll("8,10,20,33,41,44,47".Split(","), Function(u) UInteger.Parse(u))
        Dim nPicks as UInteger = 5
        Dim Picks(nPicks - 1) As UInteger
        CreateAllCombinationsOfPicksFromPool(Picks, 0, PoolArray, 0)