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

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));
    }
}

其他回答

下面是我最近用Java写的一段代码,它计算并返回从“outOf”元素中“num”元素的所有组合。

// author: Sourabh Bhat (heySourabh@gmail.com)

public class Testing
{
    public static void main(String[] args)
    {

// Test case num = 5, outOf = 8.

        int num = 5;
        int outOf = 8;
        int[][] combinations = getCombinations(num, outOf);
        for (int i = 0; i < combinations.length; i++)
        {
            for (int j = 0; j < combinations[i].length; j++)
            {
                System.out.print(combinations[i][j] + " ");
            }
            System.out.println();
        }
    }

    private static int[][] getCombinations(int num, int outOf)
    {
        int possibilities = get_nCr(outOf, num);
        int[][] combinations = new int[possibilities][num];
        int arrayPointer = 0;

        int[] counter = new int[num];

        for (int i = 0; i < num; i++)
        {
            counter[i] = i;
        }
        breakLoop: while (true)
        {
            // Initializing part
            for (int i = 1; i < num; i++)
            {
                if (counter[i] >= outOf - (num - 1 - i))
                    counter[i] = counter[i - 1] + 1;
            }

            // Testing part
            for (int i = 0; i < num; i++)
            {
                if (counter[i] < outOf)
                {
                    continue;
                } else
                {
                    break breakLoop;
                }
            }

            // Innermost part
            combinations[arrayPointer] = counter.clone();
            arrayPointer++;

            // Incrementing part
            counter[num - 1]++;
            for (int i = num - 1; i >= 1; i--)
            {
                if (counter[i] >= outOf - (num - 1 - i))
                    counter[i - 1]++;
            }
        }

        return combinations;
    }

    private static int get_nCr(int n, int r)
    {
        if(r > n)
        {
            throw new ArithmeticException("r is greater then n");
        }
        long numerator = 1;
        long denominator = 1;
        for (int i = n; i >= r + 1; i--)
        {
            numerator *= i;
        }
        for (int i = 2; i <= n - r; i++)
        {
            denominator *= i;
        }

        return (int) (numerator / denominator);
    }
}

下面的递归算法从有序集中选取所有k元素组合:

选择组合中的第一个元素I 将I与从大于I的元素集中递归选择的k-1个元素的组合组合。

对集合中的每一个i进行上述迭代。

为了避免重复,您必须选择比i大的其余元素。这样[3,5]将只被选中一次,即[3]与[5]结合,而不是两次(该条件消除了[5]+[3])。没有这个条件,你得到的是变化而不是组合。

Lisp宏为所有值r(每次取)生成代码

(defmacro txaat (some-list taken-at-a-time)
  (let* ((vars (reverse (truncate-list '(a b c d e f g h i j) taken-at-a-time))))
    `(
      ,@(loop for i below taken-at-a-time 
           for j in vars 
           with nested = nil 
           finally (return nested) 
           do
             (setf 
              nested 
              `(loop for ,j from
                    ,(if (< i (1- (length vars)))
                         `(1+ ,(nth (1+ i) vars))
                         0)
                  below (- (length ,some-list) ,i)
                    ,@(if (equal i 0) 
                          `(collect 
                               (list
                                ,@(loop for k from (1- taken-at-a-time) downto 0
                                     append `((nth ,(nth k vars) ,some-list)))))
                          `(append ,nested))))))))

So,

CL-USER> (macroexpand-1 '(txaat '(a b c d) 1))
(LOOP FOR A FROM 0 TO (- (LENGTH '(A B C D)) 1)
    COLLECT (LIST (NTH A '(A B C D))))
T
CL-USER> (macroexpand-1 '(txaat '(a b c d) 2))
(LOOP FOR A FROM 0 TO (- (LENGTH '(A B C D)) 2)
      APPEND (LOOP FOR B FROM (1+ A) TO (- (LENGTH '(A B C D)) 1)
                   COLLECT (LIST (NTH A '(A B C D)) (NTH B '(A B C D)))))
T
CL-USER> (macroexpand-1 '(txaat '(a b c d) 3))
(LOOP FOR A FROM 0 TO (- (LENGTH '(A B C D)) 3)
      APPEND (LOOP FOR B FROM (1+ A) TO (- (LENGTH '(A B C D)) 2)
                   APPEND (LOOP FOR C FROM (1+ B) TO (- (LENGTH '(A B C D)) 1)
                                COLLECT (LIST (NTH A '(A B C D))
                                              (NTH B '(A B C D))
                                              (NTH C '(A B C D))))))
T

CL-USER> 

And,

CL-USER> (txaat '(a b c d) 1)
((A) (B) (C) (D))
CL-USER> (txaat '(a b c d) 2)
((A B) (A C) (A D) (B C) (B D) (C D))
CL-USER> (txaat '(a b c d) 3)
((A B C) (A B D) (A C D) (B C D))
CL-USER> (txaat '(a b c d) 4)
((A B C D))
CL-USER> (txaat '(a b c d) 5)
NIL
CL-USER> (txaat '(a b c d) 0)
NIL
CL-USER> 

简短的python代码,产生索引位置

def yield_combos(n,k):
    # n is set size, k is combo size

    i = 0
    a = [0]*k

    while i > -1:
        for j in range(i+1, k):
            a[j] = a[j-1]+1
        i=j
        yield a
        while a[i] == i + n - k:
            i -= 1
        a[i] += 1

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