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
假设你的字母数组是这样的:"ABCDEFGH"。你有三个下标(i, j, k)来表示你要用哪个字母来表示当前单词。
A B C D E F G H ^ ^ ^ i j k
首先你改变k,所以下一步看起来像这样:
A B C D E F G H ^ ^ ^ i j k
如果你到达终点,你继续改变j和k。
A B C D E F G H ^ ^ ^ i j k A B C D E F G H ^ ^ ^ i j k
一旦j达到G, i也开始变化。
A B C D E F G H ^ ^ ^ i j k A B C D E F G H ^ ^ ^ i j k ...
function initializePointers($cnt) {
$pointers = [];
for($i=0; $i<$cnt; $i++) {
$pointers[] = $i;
}
return $pointers;
}
function incrementPointers(&$pointers, &$arrLength) {
for($i=0; $i<count($pointers); $i++) {
$currentPointerIndex = count($pointers) - $i - 1;
$currentPointer = $pointers[$currentPointerIndex];
if($currentPointer < $arrLength - $i - 1) {
++$pointers[$currentPointerIndex];
for($j=1; ($currentPointerIndex+$j)<count($pointers); $j++) {
$pointers[$currentPointerIndex+$j] = $pointers[$currentPointerIndex]+$j;
}
return true;
}
}
return false;
}
function getDataByPointers(&$arr, &$pointers) {
$data = [];
for($i=0; $i<count($pointers); $i++) {
$data[] = $arr[$pointers[$i]];
}
return $data;
}
function getCombinations($arr, $cnt)
{
$len = count($arr);
$result = [];
$pointers = initializePointers($cnt);
do {
$result[] = getDataByPointers($arr, $pointers);
} while(incrementPointers($pointers, count($arr)));
return $result;
}
$result = getCombinations([0, 1, 2, 3, 4, 5], 3);
print_r($result);
基于https://stackoverflow.com/a/127898/2628125,但更抽象,适用于任何大小的指针。
其他回答
递归,一个很简单的答案,combo,在Free Pascal中。
procedure combinata (n, k :integer; producer :oneintproc);
procedure combo (ndx, nbr, len, lnd :integer);
begin
for nbr := nbr to len do begin
productarray[ndx] := nbr;
if len < lnd then
combo(ndx+1,nbr+1,len+1,lnd)
else
producer(k);
end;
end;
begin
combo (0, 0, n-k, n-1);
end;
“producer”处理为每个组合生成的产品数组。
还有另一个递归解决方案(你应该能够使用字母而不是数字)使用堆栈,虽然比大多数更短:
stack = []
def choose(n,x):
r(0,0,n+1,x)
def r(p, c, n,x):
if x-c == 0:
print stack
return
for i in range(p, n-(x-1)+c):
stack.append(i)
r(i+1,c+1,n,x)
stack.pop()
4选3或者我想要从0到4的所有3种数字组合
choose(4,3)
[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]
下面的递归算法从有序集中选取所有k元素组合:
选择组合中的第一个元素I 将I与从大于I的元素集中递归选择的k-1个元素的组合组合。
对集合中的每一个i进行上述迭代。
为了避免重复,您必须选择比i大的其余元素。这样[3,5]将只被选中一次,即[3]与[5]结合,而不是两次(该条件消除了[5]+[3])。没有这个条件,你得到的是变化而不是组合。
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);
}
}
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' ]
]