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
你可以使用Asif算法来生成所有可能的组合。这可能是最简单和最有效的方法。你可以在这里查看媒体文章。
让我们看看JavaScript中的实现。
function Combinations( arr, r ) {
// To avoid object referencing, cloning the array.
arr = arr && arr.slice() || [];
var len = arr.length;
if( !len || r > len || !r )
return [ [] ];
else if( r === len )
return [ arr ];
if( r === len ) return arr.reduce( ( x, v ) => {
x.push( [ v ] );
return x;
}, [] );
var head = arr.shift();
return Combinations( arr, r - 1 ).map( x => {
x.unshift( head );
return x;
} ).concat( Combinations( arr, r ) );
}
// Now do your stuff.
console.log( Combinations( [ 'a', 'b', 'c', 'd', 'e' ], 3 ) );
其他回答
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));
}
}
我可以给出这个问题的递归Python解决方案吗?
def choose_iter(elements, length):
for i in xrange(len(elements)):
if length == 1:
yield (elements[i],)
else:
for next in choose_iter(elements[i+1:], length-1):
yield (elements[i],) + next
def choose(l, k):
return list(choose_iter(l, k))
使用示例:
>>> len(list(choose_iter("abcdefgh",3)))
56
我喜欢它的简洁。
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 :: _}
}
}
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;
}
简单但缓慢的c++回溯算法。
#include <iostream>
void backtrack(int* numbers, int n, int k, int i, int s)
{
if (i == k)
{
for (int j = 0; j < k; ++j)
{
std::cout << numbers[j];
}
std::cout << std::endl;
return;
}
if (s > n)
{
return;
}
numbers[i] = s;
backtrack(numbers, n, k, i + 1, s + 1);
backtrack(numbers, n, k, i, s + 1);
}
int main(int argc, char* argv[])
{
int n = 5;
int k = 3;
int* numbers = new int[k];
backtrack(numbers, n, k, 0, 1);
delete[] numbers;
return 0;
}