I want to write a function that takes an array of letters as an argument and a number of those letters to select.
Say you provide an array of 8 letters and want to select 3 letters from that. Then you should get:
8! / ((8 - 3)! * 3!) = 56
Arrays (or words) in return consisting of 3 letters each.
Art of Computer Programming Volume 4: Fascicle 3 has a ton of these that might fit your particular situation better than how I describe.
An issue that you will come across is of course memory and pretty quickly, you'll have problems by 20 elements in your set -- 20C3 = 1140. And if you want to iterate over the set it's best to use a modified gray code algorithm so you aren't holding all of them in memory. These generate the next combination from the previous and avoid repetitions. There are many of these for different uses. Do we want to maximize the differences between successive combinations? minimize? et cetera.
Some of the original papers describing gray codes:
Here are some other papers covering the topic:
Phillip J Chase, `Algorithm 382: Combinations of M out of N Objects' (1970)
You can also reference a combination by its index (in lexicographical order). Realizing that the index should be some amount of change from right to left based on the index we can construct something that should recover a combination.
So, we have a set {1,2,3,4,5,6}... and we want three elements. Let's say {1,2,3} we can say that the difference between the elements is one and in order and minimal. {1,2,4} has one change and is lexicographically number 2. So the number of 'changes' in the last place accounts for one change in the lexicographical ordering. The second place, with one change {1,3,4} has one change but accounts for more change since it's in the second place (proportional to the number of elements in the original set).
The method I've described is a deconstruction, as it seems, from set to the index, we need to do the reverse – which is much trickier. This is how Buckles solves the problem. I wrote some C to compute them, with minor changes – I used the index of the sets rather than a number range to represent the set, so we are always working from 0...n. Note:
There is another way:, its concept is easier to grasp and program but it's without the optimizations of Buckles. Fortunately, it also does not produce duplicate combinations:
The set 
that maximizes 
, where 
.
For an example: 27 = C(6,4) + C(5,3) + C(2,2) + C(1,1). So, the 27th lexicographical combination of four things is: {1,2,5,6}, those are the indexes of whatever set you want to look at. Example below (OCaml), requires choose function, left to reader:
(* this will find the [x] combination of a [set] list when taking [k] elements *)
let combination_maccaffery set k x =
(* maximize function -- maximize a that is aCb *)
(* return largest c where c < i and choose(c,i) <= z *)
let rec maximize a b x =
if (choose a b ) <= x then a else maximize (a-1) b x
in
let rec iterate n x i = match i with
| 0 -> []
| i ->
let max = maximize n i x in
max :: iterate n (x - (choose max i)) (i-1)
in
if x < 0 then failwith "errors" else
let idxs = iterate (List.length set) x k in
List.map (List.nth set) (List.sort (-) idxs)
The following two algorithms are provided for didactic purposes. They implement an iterator and (a more general) folder overall combinations.
They are as fast as possible, having the complexity O(nCk). The memory consumption is bound by k.
We will start with the iterator, which will call a user provided function for each combination
let iter_combs n k f =
let rec iter v s j =
if j = k then f v
else for i = s to n - 1 do iter (i::v) (i+1) (j+1) done in
iter [] 0 0
A more general version will call the user provided function along with the state variable, starting from the initial state. Since we need to pass the state between different states we won't use the for-loop, but instead, use recursion,
let fold_combs n k f x =
let rec loop i s c x =
if i < n then
loop (i+1) s c @@
let c = i::c and s = s + 1 and i = i + 1 in
if s < k then loop i s c x else f c x
else x in
loop 0 0 [] x
In C#:
public static IEnumerable<IEnumerable<T>> Combinations<T>(this IEnumerable<T> elements, int k)
{
return k == 0 ? new[] { new T[0] } :
elements.SelectMany((e, i) =>
elements.Skip(i + 1).Combinations(k - 1).Select(c => (new[] {e}).Concat(c)));
}
Usage:
var result = Combinations(new[] { 1, 2, 3, 4, 5 }, 3);
Result:
123
124
125
134
135
145
234
235
245
345
Lets say your array of letters looks like this: "ABCDEFGH". You have three indices (i, j, k) indicating which letters you are going to use for the current word, You start with:
A B C D E F G H ^ ^ ^ i j k
First you vary k, so the next step looks like that:
A B C D E F G H ^ ^ ^ i j k
If you reached the end you go on and vary j and then k again.
A B C D E F G H ^ ^ ^ i j k A B C D E F G H ^ ^ ^ i j k
Once you j reached G you start also to vary i.
A B C D E F G H ^ ^ ^ i j k A B C D E F G H ^ ^ ^ i j k ...
Written in code this look something like that
void print_combinations(const char *string)
{
int i, j, k;
int len = strlen(string);
for (i = 0; i < len - 2; i++)
{
for (j = i + 1; j < len - 1; j++)
{
for (k = j + 1; k < len; k++)
printf("%c%c%c\n", string[i], string[j], string[k]);
}
}
}
The following recursive algorithm picks all of the k-element combinations from an ordered set:
i of your combinationi with each of the combinations of k-1 elements chosen recursively from the set of elements larger than i.Iterate the above for each i in the set.
It is essential that you pick the rest of the elements as larger than i, to avoid repetition. This way [3,5] will be picked only once, as [3] combined with [5], instead of twice (the condition eliminates [5] + [3]). Without this condition you get variations instead of combinations.
static IEnumerable<string> Combinations(List<string> characters, int length)
{
for (int i = 0; i < characters.Count; i++)
{
// only want 1 character, just return this one
if (length == 1)
yield return characters[i];
// want more than one character, return this one plus all combinations one shorter
// only use characters after the current one for the rest of the combinations
else
foreach (string next in Combinations(characters.GetRange(i + 1, characters.Count - (i + 1)), length - 1))
yield return characters[i] + next;
}
}
If you can use SQL syntax - say, if you're using LINQ to access fields of an structure or array, or directly accessing a database that has a table called "Alphabet" with just one char field "Letter", you can adapt following code:
SELECT A.Letter, B.Letter, C.Letter
FROM Alphabet AS A, Alphabet AS B, Alphabet AS C
WHERE A.Letter<>B.Letter AND A.Letter<>C.Letter AND B.Letter<>C.Letter
AND A.Letter<B.Letter AND B.Letter<C.Letter
This will return all combinations of 3 letters, notwithstanding how many letters you have in table "Alphabet" (it can be 3, 8, 10, 27, etc.).
If what you want is all permutations, rather than combinations (i.e. you want "ACB" and "ABC" to count as different, rather than appear just once) just delete the last line (the AND one) and it's done.
Post-Edit: After re-reading the question, I realise what's needed is the general algorithm, not just a specific one for the case of selecting 3 items. Adam Hughes' answer is the complete one, unfortunately I cannot vote it up (yet). This answer's simple but works only for when you want exactly 3 items.
I had a permutation algorithm I used for project euler, in python:
def missing(miss,src):
"Returns the list of items in src not present in miss"
return [i for i in src if i not in miss]
def permutation_gen(n,l):
"Generates all the permutations of n items of the l list"
for i in l:
if n<=1: yield [i]
r = [i]
for j in permutation_gen(n-1,missing([i],l)): yield r+j
If
n<len(l)
you should have all combination you need without repetition, do you need it?
It is a generator, so you use it in something like this:
for comb in permutation_gen(3,list("ABCDEFGH")):
print comb
Here you have a lazy evaluated version of that algorithm coded in C#:
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));
}
}
And test part:
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));
}
}
Hope this help you!
Short javascript version (ES 5)
let combine = (list, n) =>
n == 0 ?
[[]] :
list.flatMap((e, i) =>
combine(
list.slice(i + 1),
n - 1
).map(c => [e].concat(c))
);
let res = combine([1,2,3,4], 3);
res.forEach(e => console.log(e.join()));Here is my proposition in C++
I tried to impose as little restriction on the iterator type as i could so this solution assumes just forward iterator, and it can be a const_iterator. This should work with any standard container. In cases where arguments don't make sense it throws std::invalid_argumnent
#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));
}
}
I created a solution in SQL Server 2005 for this, and posted it on my website: http://www.jessemclain.com/downloads/code/sql/fn_GetMChooseNCombos.sql.htm
Here is an example to show usage:
SELECT * FROM dbo.fn_GetMChooseNCombos('ABCD', 2, '')
results:
Word
----
AB
AC
AD
BC
BD
CD
(6 row(s) affected)
Here is a code I recently wrote in Java, which calculates and returns all the combination of "num" elements from "outOf" elements.
// 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);
}
}
JavaScript, generator-based, recursive approach:
function *nCk(n,k){
for(var i=n-1;i>=k-1;--i)
if(k===1)
yield [i];
else
for(var temp of nCk(i,k-1)){
temp.unshift(i);
yield temp;
}
}
function test(){
try{
var n=parseInt(ninp.value);
var k=parseInt(kinp.value);
log.innerText="";
var stop=Date.now()+1000;
if(k>=1)
for(var res of nCk(n,k))
if(Date.now()<stop)
log.innerText+=JSON.stringify(res)+" ";
else{
log.innerText+="1 second passed, stopping here.";
break;
}
}catch(ex){}
}n:<input id="ninp" oninput="test()">
>= k:<input id="kinp" oninput="test()"> >= 1
<div id="log"></div>This way (decreasing i and unshift()) it produces combinations and elements inside combinations in decreasing order, somewhat pleasing the eye.
Test stops after 1 second, so entering weird numbers is relatively safe.
Another python recusive solution.
def combination_indicies(n, k, j = 0, stack = []):
if len(stack) == k:
yield list(stack)
return
for i in range(j, n):
stack.append(i)
for x in combination_indicies(n, k, i + 1, stack):
yield x
stack.pop()
list(combination_indicies(5, 3))
Output:
[[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]]
Since programming language is not mentioned I am assuming that lists are OK too. So here's an OCaml version suitable for short lists (non tail-recursive). Given a list l of elements of any type and an integer n it will return a list of all possible lists containing n elements of l if we assume that the order of the elements in the outcome lists is ignored, i.e. list ['a';'b'] is the same as ['b';'a'] and will reported once. So size of resultant list will be ((List.length l) Choose n).
The intuition of the recursion is the following: you take the head of the list and then make two recursive calls:
to combine the recursive results, list-multiply (please bear the odd name) the head of the list with the results of RC1 and then append (@) the results of RC2. List-multiply is the following operation lmul:
a lmul [ l1 ; l2 ; l3] = [a::l1 ; a::l2 ; a::l3]
lmul is implemented in the code below as
List.map (fun x -> h::x)
Recursion is terminated when the size of the list equals the number of elements you want to choose, in which case you just return the list itself.
So here's a four-liner in OCaml that implements the above algorithm:
let rec choose l n = match l, (List.length l) with
| _, lsize when n==lsize -> [l]
| h::t, _ -> (List.map (fun x-> h::x) (choose t (n-1))) @ (choose t n)
| [], _ -> []
Here is a Lisp approach using a macro. This works in Common Lisp and should work in other Lisp dialects.
The code below creates 'n' nested loops and executes an arbitrary chunk of code (stored in the body variable) for each combination of 'n' elements from the list lst. The variable var points to a list containing the variables used for the loops.
(defmacro do-combinations ((var lst num) &body body)
(loop with syms = (loop repeat num collect (gensym))
for i on syms
for k = `(loop for ,(car i) on (cdr ,(cadr i))
do (let ((,var (list ,@(reverse syms)))) (progn ,@body)))
then `(loop for ,(car i) on ,(if (cadr i) `(cdr ,(cadr i)) lst) do ,k)
finally (return k)))
Let's see...
(macroexpand-1 '(do-combinations (p '(1 2 3 4 5 6 7) 4) (pprint (mapcar #'car p))))
(LOOP FOR #:G3217 ON '(1 2 3 4 5 6 7) DO
(LOOP FOR #:G3216 ON (CDR #:G3217) DO
(LOOP FOR #:G3215 ON (CDR #:G3216) DO
(LOOP FOR #:G3214 ON (CDR #:G3215) DO
(LET ((P (LIST #:G3217 #:G3216 #:G3215 #:G3214)))
(PROGN (PPRINT (MAPCAR #'CAR P))))))))
(do-combinations (p '(1 2 3 4 5 6 7) 4) (pprint (mapcar #'car p)))
(1 2 3 4)
(1 2 3 5)
(1 2 3 6)
...
Since combinations are not stored by default, storage is kept to a minimum. The possibility of choosing the body code instead of storing all results also affords more flexibility.
Following Haskell code calculate the combination number and combinations at the same time, and thanks to Haskell's laziness, you can get one part of them without calculating the other.
import Data.Semigroup
import Data.Monoid
data Comb = MkComb {count :: Int, combinations :: [[Int]]} deriving (Show, Eq, Ord)
instance Semigroup Comb where
(MkComb c1 cs1) <> (MkComb c2 cs2) = MkComb (c1 + c2) (cs1 ++ cs2)
instance Monoid Comb where
mempty = MkComb 0 []
addElem :: Comb -> Int -> Comb
addElem (MkComb c cs) x = MkComb c (map (x :) cs)
comb :: Int -> Int -> Comb
comb n k | n < 0 || k < 0 = error "error in `comb n k`, n and k should be natural number"
comb n k | k == 0 || k == n = MkComb 1 [(take k [k-1,k-2..0])]
comb n k | n < k = mempty
comb n k = comb (n-1) k <> (comb (n-1) (k-1) `addElem` (n-1))
It works like:
*Main> comb 0 1
MkComb {count = 0, combinations = []}
*Main> comb 0 0
MkComb {count = 1, combinations = [[]]}
*Main> comb 1 1
MkComb {count = 1, combinations = [[0]]}
*Main> comb 4 2
MkComb {count = 6, combinations = [[1,0],[2,0],[2,1],[3,0],[3,1],[3,2]]}
*Main> count (comb 10 5)
252
In Python like Andrea Ambu, but not hardcoded for choosing three.
def combinations(list, k):
"""Choose combinations of list, choosing k elements(no repeats)"""
if len(list) < k:
return []
else:
seq = [i for i in range(k)]
while seq:
print [list[index] for index in seq]
seq = get_next_combination(len(list), k, seq)
def get_next_combination(num_elements, k, seq):
index_to_move = find_index_to_move(num_elements, seq)
if index_to_move == None:
return None
else:
seq[index_to_move] += 1
#for every element past this sequence, move it down
for i, elem in enumerate(seq[(index_to_move+1):]):
seq[i + 1 + index_to_move] = seq[index_to_move] + i + 1
return seq
def find_index_to_move(num_elements, seq):
"""Tells which index should be moved"""
for rev_index, elem in enumerate(reversed(seq)):
if elem < (num_elements - rev_index - 1):
return len(seq) - rev_index - 1
return None
Here is a simple JS solution:
function getAllCombinations(n, k, f1) {
indexes = Array(k);
for (let i =0; i< k; i++) {
indexes[i] = i;
}
var total = 1;
f1(indexes);
while (indexes[0] !== n-k) {
total++;
getNext(n, indexes);
f1(indexes);
}
return {total};
}
function getNext(n, vec) {
const k = vec.length;
vec[k-1]++;
for (var i=0; i<k; i++) {
var currentIndex = k-i-1;
if (vec[currentIndex] === n - i) {
var nextIndex = k-i-2;
vec[nextIndex]++;
vec[currentIndex] = vec[nextIndex] + 1;
}
}
for (var i=1; i<k; i++) {
if (vec[i] === n - (k-i - 1)) {
vec[i] = vec[i-1] + 1;
}
}
return vec;
}
let start = new Date();
let result = getAllCombinations(10, 3, indexes => console.log(indexes));
let runTime = new Date() - start;
console.log({
result, runTime
});I'm aware that there are a LOT of answers to this already, but I thought I'd add my own individual contribution in JavaScript, which consists of two functions - one to generate all the possible distinct k-subsets of an original n-element set, and one to use that first function to generate the power set of the original n-element set.
Here is the code for the two functions:
//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
}
I tested this with the set ["a", "b", "c", "d", "e", "f"] as the base set, and ran the code to produce the following power set:
[]
["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"]
Just copy and paste those two functions "as is", and you'll have the basics needed to extract the distinct k-subsets of an n-element set, and generate the power set of that n-element set if you wish.
I don't claim this to be elegant, merely that it works after a lot of testing (and turning the air blue during the debugging phase :) ).
Below is an iterative algorithm in C++ that does not use the STL nor recursion nor conditional nested loops. It is faster that way, it does not perform any element swaps and it does not burden the stack with recursion and it can also be easily ported to ANSI C by substituting mallloc(), free() and printf() for new, delete and std::cout, respectively.
If you want to display the elements with a different or longer alphabet then change the *alphabet parameter to point to a different string than "abcdefg".
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;
}
IMPORTANT: The *alphabet parameter must point to a string with at least N characters. You can also pass an address of a string which is defined somewhere else.
Combinations: Out of "7 Choose 4".
Here is a simple und understandable recursive C++ solution:
#include<vector>
using namespace std;
template<typename T>
void ksubsets(const vector<T>& arr, unsigned left, unsigned idx,
vector<T>& lst, vector<vector<T>>& res)
{
if (left < 1) {
res.push_back(lst);
return;
}
for (unsigned i = idx; i < arr.size(); i++) {
lst.push_back(arr[i]);
ksubsets(arr, left - 1, i + 1, lst, res);
lst.pop_back();
}
}
int main()
{
vector<int> arr = { 1, 2, 3, 4, 5 };
unsigned left = 3;
vector<int> lst;
vector<vector<int>> res;
ksubsets<int>(arr, left, 0, lst, res);
// now res has all the combinations
}
There was recently a PowerShell challenge on the IronScripter website that needed an n-choose-k solution. I posted a solution there, but here is a more generic version.
function Get-NChooseK
{
[CmdletBinding()]
Param
(
[String[]]
$ArrayN
, [Int]
$ChooseK
, [Switch]
$AllK
, [String]
$Prefix = ''
)
PROCESS
{
# Validate the inputs
$ArrayN = $ArrayN | Sort-Object -Unique
If ($ChooseK -gt $ArrayN.Length)
{
Write-Error "Can't choose $ChooseK items when only $($ArrayN.Length) are available." -ErrorAction Stop
}
# Control the output
$firstK = If ($AllK) { 1 } Else { $ChooseK }
# Get combinations
$firstK..$ChooseK | ForEach-Object {
$thisK = $_
$ArrayN[0..($ArrayN.Length-($thisK--))] | ForEach-Object {
If ($thisK -eq 0)
{
Write-Output ($Prefix+$_)
}
Else
{
Get-NChooseK -Array ($ArrayN[($ArrayN.IndexOf($_)+1)..($ArrayN.Length-1)]) -Choose $thisK -AllK:$false -Prefix ($Prefix+$_)
}
}
}
}
}
E.g.:
PS C:\>$ArrayN = 'E','B','C','A','D'
PS C:\>$ChooseK = 3
PS C:\>Get-NChooseK -ArrayN $ArrayN -ChooseK $ChooseK
ABC
ABD
ABE
ACD
ACE
ADE
BCD
BCE
BDE
CDE
You can use the Asif's algorithm to generate all the possible combinations. It's probably the easiest and most efficient one. You can check out the medium article here.
Let's take a look in the implementation in JavaScript.
function Combinations( arr, r ) {
// To avoid object referencing, cloning the array.
arr = arr && arr.slice() || [];
var len = arr.length;
if( !len || r > len || !r )
return [ [] ];
else if( r === len )
return [ arr ];
if( r === len ) return arr.reduce( ( x, v ) => {
x.push( [ v ] );
return x;
}, [] );
var head = arr.shift();
return Combinations( arr, r - 1 ).map( x => {
x.unshift( head );
return x;
} ).concat( Combinations( arr, r ) );
}
// Now do your stuff.
console.log( Combinations( [ 'a', 'b', 'c', 'd', 'e' ], 3 ) );
A PowerShell solution:
function Get-NChooseK
{
<#
.SYNOPSIS
Returns all the possible combinations by choosing K items at a time from N possible items.
.DESCRIPTION
Returns all the possible combinations by choosing K items at a time from N possible items.
The combinations returned do not consider the order of items as important i.e. 123 is considered to be the same combination as 231, etc.
.PARAMETER ArrayN
The array of items to choose from.
.PARAMETER ChooseK
The number of items to choose.
.PARAMETER AllK
Includes combinations for all lesser values of K above zero i.e. 1 to K.
.PARAMETER Prefix
String that will prefix each line of the output.
.EXAMPLE
PS C:\> Get-NChooseK -ArrayN '1','2','3' -ChooseK 3
123
.EXAMPLE
PS C:\> Get-NChooseK -ArrayN '1','2','3' -ChooseK 3 -AllK
1
2
3
12
13
23
123
.EXAMPLE
PS C:\> Get-NChooseK -ArrayN '1','2','3' -ChooseK 2 -Prefix 'Combo: '
Combo: 12
Combo: 13
Combo: 23
.NOTES
Author : nmbell
#>
# Use cmdlet binding
[CmdletBinding()]
# Declare parameters
Param
(
[String[]]
$ArrayN
, [Int]
$ChooseK
, [Switch]
$AllK
, [String]
$Prefix = ''
)
BEGIN
{
}
PROCESS
{
# Validate the inputs
$ArrayN = $ArrayN | Sort-Object -Unique
If ($ChooseK -gt $ArrayN.Length)
{
Write-Error "Can't choose $ChooseK items when only $($ArrayN.Length) are available." -ErrorAction Stop
}
# Control the output
$firstK = If ($AllK) { 1 } Else { $ChooseK }
# Get combinations
$firstK..$ChooseK | ForEach-Object {
$thisK = $_
$ArrayN[0..($ArrayN.Length-($thisK--))] | ForEach-Object {
If ($thisK -eq 0)
{
Write-Output ($Prefix+$_)
}
Else
{
Get-NChooseK -Array ($ArrayN[($ArrayN.IndexOf($_)+1)..($ArrayN.Length-1)]) -Choose $thisK -AllK:$false -Prefix ($Prefix+$_)
}
}
}
}
END
{
}
}
E.g.:
PS C:\>Get-NChooseK -ArrayN 'A','B','C','D','E' -ChooseK 3
ABC
ABD
ABE
ACD
ACE
ADE
BCD
BCE
BDE
CDE
There was a challenge posted recently on the IronScripter website similar to this question, where you can find links to mine and some other solutions.