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
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)。
其他回答
我们可以用比特的概念来做这个。假设我们有一个字符串“abc”,我们想要所有长度为2的元素的组合(即“ab”,“ac”,“bc”)。
我们可以在1到2^n(排他性)的数字中找到集合位。这里是1到7,只要我们设置了bits = 2,我们就可以从string中输出相应的值。
例如:
1 - 001 二零零一 3011 ->印刷ab (str[0], str[1]) 四到一百。 5 - 101 ->打印ac (str[0], str[2]) 6 - 110 ->印刷ab (str[1], str[2]) 7 - 111。
代码示例:
public class StringCombinationK {
static void combk(String s , int k){
int n = s.length();
int num = 1<<n;
int j=0;
int count=0;
for(int i=0;i<num;i++){
if (countSet(i)==k){
setBits(i,j,s);
count++;
System.out.println();
}
}
System.out.println(count);
}
static void setBits(int i,int j,String s){ // print the corresponding string value,j represent the index of set bit
if(i==0){
return;
}
if(i%2==1){
System.out.print(s.charAt(j));
}
setBits(i/2,j+1,s);
}
static int countSet(int i){ //count number of set bits
if( i==0){
return 0;
}
return (i%2==0? 0:1) + countSet(i/2);
}
public static void main(String[] arhs){
String s = "abcdefgh";
int k=3;
combk(s,k);
}
}
Array.prototype.combs = function(num) {
var str = this,
length = str.length,
of = Math.pow(2, length) - 1,
out, combinations = [];
while(of) {
out = [];
for(var i = 0, y; i < length; i++) {
y = (1 << i);
if(y & of && (y !== of))
out.push(str[i]);
}
if (out.length >= num) {
combinations.push(out);
}
of--;
}
return combinations;
}
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' ]
]
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.
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)。