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

《计算机编程艺术，卷4A:组合算法，第1部分》第7.2.1.3节中算法L(字典组合)的C代码:

#include <stdio.h>
#include <stdlib.h>

void visit(int* c, int t) 
{
  // for (int j = 1; j <= t; j++)
  for (int j = t; j > 0; j--)
    printf("%d ", c[j]);
  printf("\n");
}

int* initialize(int n, int t) 
{
  // c[0] not used
  int *c = (int*) malloc((t + 3) * sizeof(int));

  for (int j = 1; j <= t; j++)
    c[j] = j - 1;
  c[t+1] = n;
  c[t+2] = 0;
  return c;
}

void comb(int n, int t) 
{
  int *c = initialize(n, t);
  int j;

  for (;;) {
    visit(c, t);
    j = 1;
    while (c[j]+1 == c[j+1]) {
      c[j] = j - 1;
      ++j;
    }
    if (j > t) 
      return;
    ++c[j];
  }
  free(c);
}

int main(int argc, char *argv[])
{
  comb(5, 3);
  return 0;
}

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   

https://gist.github.com/3118596

JavaScript有一个实现。它有函数来获得k组合和任意对象数组的所有组合。例子:

k_combinations([1,2,3], 2)
-> [[1,2], [1,3], [2,3]]

combinations([1,2,3])
-> [[1],[2],[3],[1,2],[1,3],[2,3],[1,2,3]]

void combine(char a[], int N, int M, int m, int start, char result[]) {
    if (0 == m) {
        for (int i = M - 1; i >= 0; i--)
            std::cout << result[i];
        std::cout << std::endl;
        return;
    }
    for (int i = start; i < (N - m + 1); i++) {
        result[m - 1] = a[i];
        combine(a, N, M, m-1, i+1, result);
    }
}

void combine(char a[], int N, int M) {
    char *result = new char[M];
    combine(a, N, M, M, 0, result);
    delete[] result;
}

在第一个函数中，m表示还需要选择多少个，start表示必须从数组中的哪个位置开始选择。