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

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

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。

说了这么多,做了这么多,这就是奥卡姆的代码。 算法是显而易见的代码..

let combi n lst =
    let rec comb l c =
        if( List.length c = n) then [c] else
        match l with
        [] -> []
        | (h::t) -> (combi t (h::c))@(combi t c)
    in
        combi lst []
;;

赶时髦,发布另一个解决方案。这是一个通用的Java实现。输入:(int k)是要选择的元素数量,(List<T> List)是要选择的列表。返回一个组合列表(list < list <T>>)。

public static <T> List<List<T>> getCombinations(int k, List<T> list) {
    List<List<T>> combinations = new ArrayList<List<T>>();
    if (k == 0) {
        combinations.add(new ArrayList<T>());
        return combinations;
    }
    for (int i = 0; i < list.size(); i++) {
        T element = list.get(i);
        List<T> rest = getSublist(list, i+1);
        for (List<T> previous : getCombinations(k-1, rest)) {
            previous.add(element);
            combinations.add(previous);
        }
    }
    return combinations;
}

public static <T> List<T> getSublist(List<T> list, int i) {
    List<T> sublist = new ArrayList<T>();
    for (int j = i; j < list.size(); j++) {
        sublist.add(list.get(j));
    }
    return sublist;
}

用c#的另一个解决方案:

 static List<List<T>> GetCombinations<T>(List<T> originalItems, int combinationLength)
    {
        if (combinationLength < 1)
        {
            return null;
        }

        return CreateCombinations<T>(new List<T>(), 0, combinationLength, originalItems);
    }

 static List<List<T>> CreateCombinations<T>(List<T> initialCombination, int startIndex, int length, List<T> originalItems)
    {
        List<List<T>> combinations = new List<List<T>>();
        for (int i = startIndex; i < originalItems.Count - length + 1; i++)
        {
            List<T> newCombination = new List<T>(initialCombination);
            newCombination.Add(originalItems[i]);
            if (length > 1)
            {
                List<List<T>> newCombinations = CreateCombinations(newCombination, i + 1, length - 1, originalItems);
                combinations.AddRange(newCombinations);
            }
            else
            {
                combinations.Add(newCombination);
            }
        }

        return combinations;
    }

用法示例:

   List<char> initialArray = new List<char>() { 'a','b','c','d'};
   int combinationLength = 3;
   List<List<char>> combinations = GetCombinations(initialArray, combinationLength);

我知道这个问题已经有很多答案了,但我想在JavaScript中添加我自己的贡献,它由两个函数组成——一个生成原始n元素集的所有可能不同的k子集,另一个使用第一个函数生成原始n元素集的幂集。

下面是这两个函数的代码:

//Generate combination subsets from a base set of elements (passed as an array). This function should generate an
//array containing nCr elements, where nCr = n!/[r! (n-r)!].

//Arguments:

//[1] baseSet :     The base set to create the subsets from (e.g., ["a", "b", "c", "d", "e", "f"])
//[2] cnt :         The number of elements each subset is to contain (e.g., 3)

function MakeCombinationSubsets(baseSet, cnt)
{
    var bLen = baseSet.length;
    var indices = [];
    var subSet = [];
    var done = false;
    var result = [];        //Contains all the combination subsets generated
    var done = false;
    var i = 0;
    var idx = 0;
    var tmpIdx = 0;
    var incr = 0;
    var test = 0;
    var newIndex = 0;
    var inBounds = false;
    var tmpIndices = [];
    var checkBounds = false;

    //First, generate an array whose elements are indices into the base set ...

    for (i=0; i<cnt; i++)

        indices.push(i);

    //Now create a clone of this array, to be used in the loop itself ...

        tmpIndices = [];

        tmpIndices = tmpIndices.concat(indices);

    //Now initialise the loop ...

    idx = cnt - 1;      //point to the last element of the indices array
    incr = 0;
    done = false;
    while (!done)
    {
    //Create the current subset ...

        subSet = [];    //Make sure we begin with a completely empty subset before continuing ...

        for (i=0; i<cnt; i++)

            subSet.push(baseSet[tmpIndices[i]]);    //Create the current subset, using items selected from the
                                                    //base set, using the indices array (which will change as we
                                                    //continue scanning) ...

    //Add the subset thus created to the result set ...

        result.push(subSet);

    //Now update the indices used to select the elements of the subset. At the start, idx will point to the
    //rightmost index in the indices array, but the moment that index moves out of bounds with respect to the
    //base set, attention will be shifted to the next left index.

        test = tmpIndices[idx] + 1;

        if (test >= bLen)
        {
        //Here, we're about to move out of bounds with respect to the base set. We therefore need to scan back,
        //and update indices to the left of the current one. Find the leftmost index in the indices array that
        //isn't going to  move out of bounds with respect to the base set ...

            tmpIdx = idx - 1;
            incr = 1;

            inBounds = false;       //Assume at start that the index we're checking in the loop below is out of bounds
            checkBounds = true;

            while (checkBounds)
            {
                if (tmpIdx < 0)
                {
                    checkBounds = false;    //Exit immediately at this point
                }
                else
                {
                    newIndex = tmpIndices[tmpIdx] + 1;
                    test = newIndex + incr;

                    if (test >= bLen)
                    {
                    //Here, incrementing the current selected index will take that index out of bounds, so
                    //we move on to the next index to the left ...

                        tmpIdx--;
                        incr++;
                    }
                    else
                    {
                    //Here, the index will remain in bounds if we increment it, so we
                    //exit the loop and signal that we're in bounds ...

                        inBounds = true;
                        checkBounds = false;

                    //End if/else
                    }

                //End if 
                }               
            //End while
            }
    //At this point, if we'er still in bounds, then we continue generating subsets, but if not, we abort immediately.

            if (!inBounds)
                done = true;
            else
            {
            //Here, we're still in bounds. We need to update the indices accordingly. NOTE: at this point, although a
            //left positioned index in the indices array may still be in bounds, incrementing it to generate indices to
            //the right may take those indices out of bounds. We therefore need to check this as we perform the index
            //updating of the indices array.

                tmpIndices[tmpIdx] = newIndex;

                inBounds = true;
                checking = true;
                i = tmpIdx + 1;

                while (checking)
                {
                    test = tmpIndices[i - 1] + 1;   //Find out if incrementing the left adjacent index takes it out of bounds

                    if (test >= bLen)
                    {
                        inBounds = false;           //If we move out of bounds, exit NOW ...
                        checking = false;
                    }
                    else
                    {
                        tmpIndices[i] = test;       //Otherwise, update the indices array ...

                        i++;                        //Now move on to the next index to the right in the indices array ...

                        checking = (i < cnt);       //And continue until we've exhausted all the indices array elements ...
                    //End if/else
                    }
                //End while
                }
                //At this point, if the above updating of the indices array has moved any of its elements out of bounds,
                //we abort subset construction from this point ...
                if (!inBounds)
                    done = true;
            //End if/else
            }
        }
        else
        {
        //Here, the rightmost index under consideration isn't moving out of bounds with respect to the base set when
        //we increment it, so we simply increment and continue the loop ...
            tmpIndices[idx] = test;
        //End if
        }
    //End while
    }
    return(result);
//End function
}


function MakePowerSet(baseSet)
{
    var bLen = baseSet.length;
    var result = [];
    var i = 0;
    var partialSet = [];

    result.push([]);    //add the empty set to the power set

    for (i=1; i<bLen; i++)
    {
        partialSet = MakeCombinationSubsets(baseSet, i);
        result = result.concat(partialSet);
    //End i loop
    }
    //Now, finally, add the base set itself to the power set to make it complete ...

    partialSet = [];
    partialSet.push(baseSet);
    result = result.concat(partialSet);

    return(result);
    //End function
}

我用集合["a", "b", "c", "d", "e", "f"]作为基本集进行了测试,并运行代码以产生以下幂集:

[]
["a"]
["b"]
["c"]
["d"]
["e"]
["f"]
["a","b"]
["a","c"]
["a","d"]
["a","e"]
["a","f"]
["b","c"]
["b","d"]
["b","e"]
["b","f"]
["c","d"]
["c","e"]
["c","f"]
["d","e"]
["d","f"]
["e","f"]
["a","b","c"]
["a","b","d"]
["a","b","e"]
["a","b","f"]
["a","c","d"]
["a","c","e"]
["a","c","f"]
["a","d","e"]
["a","d","f"]
["a","e","f"]
["b","c","d"]
["b","c","e"]
["b","c","f"]
["b","d","e"]
["b","d","f"]
["b","e","f"]
["c","d","e"]
["c","d","f"]
["c","e","f"]
["d","e","f"]
["a","b","c","d"]
["a","b","c","e"]
["a","b","c","f"]
["a","b","d","e"]
["a","b","d","f"]
["a","b","e","f"]
["a","c","d","e"]
["a","c","d","f"]
["a","c","e","f"]
["a","d","e","f"]
["b","c","d","e"]
["b","c","d","f"]
["b","c","e","f"]
["b","d","e","f"]
["c","d","e","f"]
["a","b","c","d","e"]
["a","b","c","d","f"]
["a","b","c","e","f"]
["a","b","d","e","f"]
["a","c","d","e","f"]
["b","c","d","e","f"]
["a","b","c","d","e","f"]

只要复制粘贴这两个函数“原样”,你就有了提取n元素集的不同k子集所需的基本知识,并生成该n元素集的幂集(如果你愿意的话)。

我并不是说这很优雅,只是说它在经过大量的测试(并在调试阶段将空气变为蓝色:)之后可以工作。