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。
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
也许我错过了重点(你需要的是算法,而不是现成的解决方案),但看起来scala已经开箱即用了(现在):
def combis(str:String, k:Int):Array[String] = {
str.combinations(k).toArray
}
使用这样的方法:
println(combis("abcd",2).toList)
会产生:
List(ab, ac, ad, bc, bd, cd)
其他回答
我已经编写了一个类来处理处理二项式系数的常见函数,这是您的问题属于的问题类型。它执行以下任务:
Outputs all the K-indexes in a nice format for any N choose K to a file. The K-indexes can be substituted with more descriptive strings or letters. This method makes solving this type of problem quite trivial. Converts the K-indexes to the proper index of an entry in the sorted binomial coefficient table. This technique is much faster than older published techniques that rely on iteration. It does this by using a mathematical property inherent in Pascal's Triangle. My paper talks about this. I believe I am the first to discover and publish this technique, but I could be wrong. Converts the index in a sorted binomial coefficient table to the corresponding K-indexes. Uses Mark Dominus method to calculate the binomial coefficient, which is much less likely to overflow and works with larger numbers. The class is written in .NET C# and provides a way to manage the objects related to the problem (if any) by using a generic list. The constructor of this class takes a bool value called InitTable that when true will create a generic list to hold the objects to be managed. If this value is false, then it will not create the table. The table does not need to be created in order to perform the 4 above methods. Accessor methods are provided to access the table. There is an associated test class which shows how to use the class and its methods. It has been extensively tested with 2 cases and there are no known bugs.
要了解这个类并下载代码,请参见将二项式系数表化。
将这个类转换为c++应该不难。
简短javascript版本(es5)
令combine = (list, n) => N == 0 ? [[]]: 列表。flatMap((e, i) => 结合( 列表。切片(i + 1) N - 1 ).Map (c => [e].concat(c)) ); Let res = combine([1,2,3,4], 3); res.forEach(e => console.log(e.join()));
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
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
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