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
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。
其他回答
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。
Lisp宏为所有值r(每次取)生成代码
(defmacro txaat (some-list taken-at-a-time)
(let* ((vars (reverse (truncate-list '(a b c d e f g h i j) taken-at-a-time))))
`(
,@(loop for i below taken-at-a-time
for j in vars
with nested = nil
finally (return nested)
do
(setf
nested
`(loop for ,j from
,(if (< i (1- (length vars)))
`(1+ ,(nth (1+ i) vars))
0)
below (- (length ,some-list) ,i)
,@(if (equal i 0)
`(collect
(list
,@(loop for k from (1- taken-at-a-time) downto 0
append `((nth ,(nth k vars) ,some-list)))))
`(append ,nested))))))))
So,
CL-USER> (macroexpand-1 '(txaat '(a b c d) 1))
(LOOP FOR A FROM 0 TO (- (LENGTH '(A B C D)) 1)
COLLECT (LIST (NTH A '(A B C D))))
T
CL-USER> (macroexpand-1 '(txaat '(a b c d) 2))
(LOOP FOR A FROM 0 TO (- (LENGTH '(A B C D)) 2)
APPEND (LOOP FOR B FROM (1+ A) TO (- (LENGTH '(A B C D)) 1)
COLLECT (LIST (NTH A '(A B C D)) (NTH B '(A B C D)))))
T
CL-USER> (macroexpand-1 '(txaat '(a b c d) 3))
(LOOP FOR A FROM 0 TO (- (LENGTH '(A B C D)) 3)
APPEND (LOOP FOR B FROM (1+ A) TO (- (LENGTH '(A B C D)) 2)
APPEND (LOOP FOR C FROM (1+ B) TO (- (LENGTH '(A B C D)) 1)
COLLECT (LIST (NTH A '(A B C D))
(NTH B '(A B C D))
(NTH C '(A B C D))))))
T
CL-USER>
And,
CL-USER> (txaat '(a b c d) 1)
((A) (B) (C) (D))
CL-USER> (txaat '(a b c d) 2)
((A B) (A C) (A D) (B C) (B D) (C D))
CL-USER> (txaat '(a b c d) 3)
((A B C) (A B D) (A C D) (B C D))
CL-USER> (txaat '(a b c d) 4)
((A B C D))
CL-USER> (txaat '(a b c d) 5)
NIL
CL-USER> (txaat '(a b c d) 0)
NIL
CL-USER>
这里你有一个用c#编写的该算法的惰性评估版本:
static bool nextCombination(int[] num, int n, int k)
{
bool finished, changed;
changed = finished = false;
if (k > 0)
{
for (int i = k - 1; !finished && !changed; i--)
{
if (num[i] < (n - 1) - (k - 1) + i)
{
num[i]++;
if (i < k - 1)
{
for (int j = i + 1; j < k; j++)
{
num[j] = num[j - 1] + 1;
}
}
changed = true;
}
finished = (i == 0);
}
}
return changed;
}
static IEnumerable Combinations<T>(IEnumerable<T> elements, int k)
{
T[] elem = elements.ToArray();
int size = elem.Length;
if (k <= size)
{
int[] numbers = new int[k];
for (int i = 0; i < k; i++)
{
numbers[i] = i;
}
do
{
yield return numbers.Select(n => elem[n]);
}
while (nextCombination(numbers, size, k));
}
}
及测试部分:
static void Main(string[] args)
{
int k = 3;
var t = new[] { "dog", "cat", "mouse", "zebra"};
foreach (IEnumerable<string> i in Combinations(t, k))
{
Console.WriteLine(string.Join(",", i));
}
}
希望这对你有帮助!
另一种版本,迫使所有前k个组合首先出现,然后是所有前k+1个组合,然后是所有前k+2个组合,等等。这意味着如果你对数组进行排序,最重要的在最上面,它会把它们逐渐扩展到下一个——只有在必须这样做的时候。
private static bool NextCombinationFirstsAlwaysFirst(int[] num, int n, int k)
{
if (k > 1 && NextCombinationFirstsAlwaysFirst(num, num[k - 1], k - 1))
return true;
if (num[k - 1] + 1 == n)
return false;
++num[k - 1];
for (int i = 0; i < k - 1; ++i)
num[i] = i;
return true;
}
例如,如果你在k=3, n=5上运行第一个方法("nextCombination"),你会得到:
0 1 2
0 1 3
0 1 4
0 2 3
0 2 4
0 3 4
1 2 3
1 2 4
1 3 4
2 3 4
但如果你跑
int[] nums = new int[k];
for (int i = 0; i < k; ++i)
nums[i] = i;
do
{
Console.WriteLine(string.Join(" ", nums));
}
while (NextCombinationFirstsAlwaysFirst(nums, n, k));
你会得到这个(为了清晰起见,我添加了空行):
0 1 2
0 1 3
0 2 3
1 2 3
0 1 4
0 2 4
1 2 4
0 3 4
1 3 4
2 3 4
它只在必须添加时才添加“4”,而且在添加“4”之后,它只在必须添加时再添加“3”(在执行01、02、12之后)。
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' ]
]
下面是一个coffeescript实现
combinations: (list, n) ->
permuations = Math.pow(2, list.length) - 1
out = []
combinations = []
while permuations
out = []
for i in [0..list.length]
y = ( 1 << i )
if( y & permuations and (y isnt permuations))
out.push(list[i])
if out.length <= n and out.length > 0
combinations.push(out)
permuations--
return combinations