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
不需要进行集合操作。这个问题几乎和循环K个嵌套循环一样,但你必须小心索引和边界(忽略Java和OOP的东西):
public class CombinationsGen {
private final int n;
private final int k;
private int[] buf;
public CombinationsGen(int n, int k) {
this.n = n;
this.k = k;
}
public void combine(Consumer<int[]> consumer) {
buf = new int[k];
rec(0, 0, consumer);
}
private void rec(int index, int next, Consumer<int[]> consumer) {
int max = n - index;
if (index == k - 1) {
for (int i = 0; i < max && next < n; i++) {
buf[index] = next;
next++;
consumer.accept(buf);
}
} else {
for (int i = 0; i < max && next + index < n; i++) {
buf[index] = next;
next++;
rec(index + 1, next, consumer);
}
}
}
}
像这样使用:
CombinationsGen gen = new CombinationsGen(5, 2);
AtomicInteger total = new AtomicInteger();
gen.combine(arr -> {
System.out.println(Arrays.toString(arr));
total.incrementAndGet();
});
System.out.println(total);
获得预期的结果:
[0, 1]
[0, 2]
[0, 3]
[0, 4]
[1, 2]
[1, 3]
[1, 4]
[2, 3]
[2, 4]
[3, 4]
10
最后,将索引映射到您可能拥有的任何数据集。
其他回答
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
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。
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)
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' ]
]
下面是c++中的迭代算法,它不使用STL,也不使用递归,也不使用条件嵌套循环。这样更快,它不执行任何元素交换,也不会给堆栈带来递归负担,还可以通过分别用mallloc()、free()和printf()替换new、delete和std::cout轻松地移植到ANSI C。
如果你想用不同或更长的字母显示元素,那么改变*字母参数以指向不同于"abcdefg"的字符串。
void OutputArrayChar(unsigned int* ka, size_t n, const char *alphabet) {
for (int i = 0; i < n; i++)
std::cout << alphabet[ka[i]] << ",";
std::cout << endl;
}
void GenCombinations(const unsigned int N, const unsigned int K, const char *alphabet) {
unsigned int *ka = new unsigned int [K]; //dynamically allocate an array of UINTs
unsigned int ki = K-1; //Point ki to the last elemet of the array
ka[ki] = N-1; //Prime the last elemet of the array.
while (true) {
unsigned int tmp = ka[ki]; //Optimization to prevent reading ka[ki] repeatedly
while (ki) //Fill to the left with consecutive descending values (blue squares)
ka[--ki] = --tmp;
OutputArrayChar(ka, K, alphabet);
while (--ka[ki] == ki) { //Decrement and check if the resulting value equals the index (bright green squares)
OutputArrayChar(ka, K, alphabet);
if (++ki == K) { //Exit condition (all of the values in the array are flush to the left)
delete[] ka;
return;
}
}
}
}
int main(int argc, char *argv[])
{
GenCombinations(7, 4, "abcdefg");
return 0;
}
重要提示:字母参数*必须指向至少N个字符的字符串。你也可以传递一个在其他地方定义的字符串地址。
组合:从“7选4”中选择。