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
简短的python代码,产生索引位置
def yield_combos(n,k):
# n is set size, k is combo size
i = 0
a = [0]*k
while i > -1:
for j in range(i+1, k):
a[j] = a[j-1]+1
i=j
yield a
while a[i] == i + n - k:
i -= 1
a[i] += 1
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));
}
}
现在又出现了祖辈COBOL,一种饱受诟病的语言。
让我们假设一个包含34个元素的数组,每个元素8个字节(完全是任意选择)。其思想是枚举所有可能的4元素组合,并将它们加载到一个数组中。
我们使用4个指标,每个指标代表4个组中的每个位置
数组是这样处理的:
idx1 = 1
idx2 = 2
idx3 = 3
idx4 = 4
我们把idx4从4变到最后。对于每个idx4,我们得到一个唯一的组合 四人一组。当idx4到达数组的末尾时,我们将idx3增加1,并将idx4设置为idx3+1。然后再次运行idx4到最后。我们以这种方式继续,分别增加idx3、idx2和idx1,直到idx1的位置距离数组末端小于4。算法就完成了。
1 --- pos.1
2 --- pos 2
3 --- pos 3
4 --- pos 4
5
6
7
etc.
第一次迭代:
1234
1235
1236
1237
1245
1246
1247
1256
1257
1267
etc.
一个COBOL的例子:
01 DATA_ARAY.
05 FILLER PIC X(8) VALUE "VALUE_01".
05 FILLER PIC X(8) VALUE "VALUE_02".
etc.
01 ARAY_DATA OCCURS 34.
05 ARAY_ITEM PIC X(8).
01 OUTPUT_ARAY OCCURS 50000 PIC X(32).
01 MAX_NUM PIC 99 COMP VALUE 34.
01 INDEXXES COMP.
05 IDX1 PIC 99.
05 IDX2 PIC 99.
05 IDX3 PIC 99.
05 IDX4 PIC 99.
05 OUT_IDX PIC 9(9).
01 WHERE_TO_STOP_SEARCH PIC 99 COMP.
* Stop the search when IDX1 is on the third last array element:
COMPUTE WHERE_TO_STOP_SEARCH = MAX_VALUE - 3
MOVE 1 TO IDX1
PERFORM UNTIL IDX1 > WHERE_TO_STOP_SEARCH
COMPUTE IDX2 = IDX1 + 1
PERFORM UNTIL IDX2 > MAX_NUM
COMPUTE IDX3 = IDX2 + 1
PERFORM UNTIL IDX3 > MAX_NUM
COMPUTE IDX4 = IDX3 + 1
PERFORM UNTIL IDX4 > MAX_NUM
ADD 1 TO OUT_IDX
STRING ARAY_ITEM(IDX1)
ARAY_ITEM(IDX2)
ARAY_ITEM(IDX3)
ARAY_ITEM(IDX4)
INTO OUTPUT_ARAY(OUT_IDX)
ADD 1 TO IDX4
END-PERFORM
ADD 1 TO IDX3
END-PERFORM
ADD 1 TO IDX2
END_PERFORM
ADD 1 TO IDX1
END-PERFORM.
下面是我最近用Java写的一段代码,它计算并返回从“outOf”元素中“num”元素的所有组合。
// author: Sourabh Bhat (heySourabh@gmail.com)
public class Testing
{
public static void main(String[] args)
{
// Test case num = 5, outOf = 8.
int num = 5;
int outOf = 8;
int[][] combinations = getCombinations(num, outOf);
for (int i = 0; i < combinations.length; i++)
{
for (int j = 0; j < combinations[i].length; j++)
{
System.out.print(combinations[i][j] + " ");
}
System.out.println();
}
}
private static int[][] getCombinations(int num, int outOf)
{
int possibilities = get_nCr(outOf, num);
int[][] combinations = new int[possibilities][num];
int arrayPointer = 0;
int[] counter = new int[num];
for (int i = 0; i < num; i++)
{
counter[i] = i;
}
breakLoop: while (true)
{
// Initializing part
for (int i = 1; i < num; i++)
{
if (counter[i] >= outOf - (num - 1 - i))
counter[i] = counter[i - 1] + 1;
}
// Testing part
for (int i = 0; i < num; i++)
{
if (counter[i] < outOf)
{
continue;
} else
{
break breakLoop;
}
}
// Innermost part
combinations[arrayPointer] = counter.clone();
arrayPointer++;
// Incrementing part
counter[num - 1]++;
for (int i = num - 1; i >= 1; i--)
{
if (counter[i] >= outOf - (num - 1 - i))
counter[i - 1]++;
}
}
return combinations;
}
private static int get_nCr(int n, int r)
{
if(r > n)
{
throw new ArithmeticException("r is greater then n");
}
long numerator = 1;
long denominator = 1;
for (int i = n; i >= r + 1; i--)
{
numerator *= i;
}
for (int i = 2; i <= n - r; i++)
{
denominator *= i;
}
return (int) (numerator / denominator);
}
}
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;
}
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。