I wanted to ask how to check if a group of numbers could be split into subgroups (every subgroup has to have 3 members) that every sum of subgroups' members would be equal. How to check so many combinations?
Example:
int numbers[] = {1, 2, 5, 6, 8, 3, 2, 4, 5};
can be divided into
{1, 5, 6}, {2, 8, 2}, {3, 4, 5}
A recursive approach can be followed, where one keeps two arrays:
An array with the sums of every subgroup.
A boolean array to check whether an element is already taken into
some subgroup or not.
You asked for 3 subgroups, i.e. K = 3 in the rest of this post, but keep in mind that when dealing with recursion, bases cases should be taken into account. In this case we will focus on two base cases:
If K is 1, then we already have our answer, complete array is only
subset with same sum.
If N < K, then it is not possible to divide array into subsets with
equal sum, because we can’t divide the array into more than N parts.
If the sum of group is not divisible by K, then it is not possible to divide it. We will only proceed if k divides sum. Our goal reduces to divide the group into K subgroups where sum of each subgroup should be the sum of the group divided by K.
In the code below a recursive method is written which tries to add array element into some subset. If sum of this subset reaches required sum, we iterate for next part recursively, otherwise we backtrack for different set of elements. If number of subsets whose sum reaches the required sum is (K-1), we flag that it is possible to partition array into K parts with equal sum, because remaining elements already have a sum equal to required sum.
Quoted from here, while in your case you would set K = 3, as in the example code.
// C++ program to check whether an array can be
// subsetitioned into K subsets of equal sum
#include <bits/stdc++.h>
using namespace std;
// Recursive Utility method to check K equal sum
// subsetition of array
/**
array - given input array
subsetSum array - sum to store each subset of the array
taken - boolean array to check whether element
is taken into sum subsetition or not
K - number of subsetitions needed
N - total number of element in array
curIdx - current subsetSum index
limitIdx - lastIdx from where array element should
be taken */
bool isKPartitionPossibleRec(int arr[], int subsetSum[], bool taken[],
int subset, int K, int N, int curIdx, int limitIdx)
{
if (subsetSum[curIdx] == subset)
{
/* current index (K - 2) represents (K - 1) subsets of equal
sum last subsetition will already remain with sum 'subset'*/
if (curIdx == K - 2)
return true;
// recursive call for next subsetition
return isKPartitionPossibleRec(arr, subsetSum, taken, subset,
K, N, curIdx + 1, N - 1);
}
// start from limitIdx and include elements into current subsetition
for (int i = limitIdx; i >= 0; i--)
{
// if already taken, continue
if (taken[i])
continue;
int tmp = subsetSum[curIdx] + arr[i];
// if temp is less than subset then only include the element
// and call recursively
if (tmp <= subset)
{
// mark the element and include into current subsetition sum
taken[i] = true;
subsetSum[curIdx] += arr[i];
bool nxt = isKPartitionPossibleRec(arr, subsetSum, taken,
subset, K, N, curIdx, i - 1);
// after recursive call unmark the element and remove from
// subsetition sum
taken[i] = false;
subsetSum[curIdx] -= arr[i];
if (nxt)
return true;
}
}
return false;
}
// Method returns true if arr can be subsetitioned into K subsets
// with equal sum
bool isKPartitionPossible(int arr[], int N, int K)
{
// If K is 1, then complete array will be our answer
if (K == 1)
return true;
// If total number of subsetitions are more than N, then
// division is not possible
if (N < K)
return false;
// if array sum is not divisible by K then we can't divide
// array into K subsetitions
int sum = 0;
for (int i = 0; i < N; i++)
sum += arr[i];
if (sum % K != 0)
return false;
// the sum of each subset should be subset (= sum / K)
int subset = sum / K;
int subsetSum[K];
bool taken[N];
// Initialize sum of each subset from 0
for (int i = 0; i < K; i++)
subsetSum[i] = 0;
// mark all elements as not taken
for (int i = 0; i < N; i++)
taken[i] = false;
// initialize first subsubset sum as last element of
// array and mark that as taken
subsetSum[0] = arr[N - 1];
taken[N - 1] = true;
if (subset < subsetSum[0])
return false;
// call recursive method to check K-subsetition condition
return isKPartitionPossibleRec(arr, subsetSum, taken,
subset, K, N, 0, N - 1);
}
// Driver code to test above methods
int main()
{
int arr[] = {2, 1, 4, 5, 3, 3};
int N = sizeof(arr) / sizeof(arr[0]);
int K = 3;
if (isKPartitionPossible(arr, N, K))
cout << "Partitions into equal sum is possible.\n";
else
cout << "Partitions into equal sum is not possible.\n";
}
Output:
Partitions into equal sum is possible.
Relevant links: 2 and 3.
You could just do something like that in this particular case (3x3):
const int COUNT = 9;
bool test(int const (&array)[COUNT], std::vector<std::vector<int>>* result) {
for(int _1=0; _1<COUNT-2; ++_1) {
for(int _2=1; _2<COUNT-1; ++_2) {
if(_2 == _1)
continue;
for(int _3=2; _3<COUNT; ++_3) {
if(_3 == _2 || _3 == _1)
continue;
std::vector<int> chosen1 {array[_1], array[_2], array[_3]};
std::vector<int> rest;
for(int _x = 0; _x < COUNT; ++_x) {
if(_x != _1 && _x != _2 && _x != _3) {
rest.push_back(array[_x]);
}
}
for (int _4 = 0; _4 < COUNT-5; ++_4) {
for (int _5 = 1; _5 < COUNT-4; ++_5) {
if(_5 == _4)
continue;
for (int _6 = 2; _6 < COUNT-3; ++_6) {
if(_6 == _5 || _6 == _4)
continue;
std::vector<int> chosen2 = {rest[_4], rest[_5], rest[_6]};
std::vector<int> chosen3;
for(int _x = 0; _x < COUNT-3; ++_x) {
if(_x != _4 && _x != _5 && _x != _6) {
chosen3.push_back(rest[_x]);
}
}
int total = std::accumulate(chosen1.begin(), chosen1.end(), 0);
if((std::accumulate(chosen2.begin(), chosen2.end(), 0) == total) &&
(std::accumulate(chosen3.begin(), chosen3.end(), 0) == total)) {
*result = {chosen1, chosen2, chosen3};
return true;
}
}
}
}
}
}
}
return false;
}
int main() {
int values[] = {1, 2, 5, 6, 8, 3, 2, 4, 5};
std::vector<std::vector<int>> result;
if(test(values, &result)) {
for(auto& x : result) {
std::cout << "{";
for(auto& y : x) {
std::cout << y << ",";
}
std::cout << "}";
}
std::cout << std::endl;
} else {
std::cout << "not found";
}
}
If you had longer array (3+ * 3) then you could use recurrence (you could use it in my example too), but that would be still very slow.
Related
Given a number S ( int > 0 ) and n (int > 0), print all the different subsets of len n which sum to S.
For S = 7 and n = 3, the output is the following, the output must be descending order:
5 + 1 + 1
4 + 2 + 1
3 + 3 + 1
3 + 2 + 2
Here is what I've tried so far:
vector<vector<int> > partitions(int X, int Y)
{
vector<vector<int> > v;
if (X <= 1 && X <= X - Y + 1)
{
v.resize(1);
v[0].push_back(X);
return v;
}
for (int y = min(X - 1, Y); y >= 1; y--)
{
vector<vector<int> > w = partitions(X - y, y);
for (int i = 0; i<w.size(); i++)
{
w[i].push_back(y);
v.push_back(w[i]);
}
}
return v;
}
int main()
{
vector<vector<int> > v = partitions(7, 3);
int i;
for (i = 0; i<v.size(); i++)
{
int x;
for (x = 0; x<v[i].size(); x++)
printf("%d ", v[i][x]);
printf("\n");
}
}
the first element in the matrix is s- n + 1 and full of 1 till the sum is reached, or if the s-n+1 is equal to s, then n is 1, so only s will be the solution.
p.s.: I don t know if this problem has a particular name
This may not be the best solution for your problem, since it's not a dynamic programming based solution. In this case, I'm using recursion to fill an array until I reduce the desired number to 0. In this solution, every combination will be stored in the increasing order of the elements so we prevent permutations of a already calculated solution.
#include <iostream>
void findCombinationGivenSize(int numbersArray[], int index, int num, int reducedNum, int maxNum){
if (reducedNum < 0)
return; // this is our base case
if (reducedNum == 0 && index == maxNum){ // both criteria were attended:
//the sum is up to num, and the subset contain maxNum numbers
for (int i = index - 1; i>=0; i--)
std::cout<< numbersArray[i] << " + ";
// here we will have a problem with an extra '+' on the end, but you can figure out easily how to remove it :)
std::cout<<std::endl;
return;
}
// Find the previous number stored in arrayNumber[]
int prev;
if(index == 0)
prev = 1;
else
prev = numbersArray[index-1];
for (int k = prev; k <= num; k++){
// next element of array is k
numbersArray[index] = k;
// call recursively with reduced number
findCombinationGivenSize(numbersArray, index + 1, num,reducedNum - k, maxNum);
}
}
void findCombinations(int number, int maxSubset){
int arrayNumbers[number];
findCombinationGivenSize(arrayNumbers, 0, number, number, maxSubset);
}
int main(){
int number = 7;
int maxPartitions = 3;
findCombinations(number, maxPartitions);
return 0;
}
Given : A two dimensional array , values K and M
Problem : Find the maximum possible sum less than or equal K using all the rows (i.e there should be an element form each row) using exactly M elements.
This is a snippet of a program, I am having trouble implementing the conditions for each row and M.
for (int i = 0 ; i<n ; i++)
for (int s=0; s<M; s++)
for (int j=K;j>=0;j--)
if (dp[s][j] && A[i] + j < K)
dp[s + 1][j + A[i]] = true;
EDIT 1: Rows = M , i.e one element from each row has to be selected.
EDIT 2 : Dynamic Programming Solution, Thanks to #6502
ill ret(V(ill) col[101],ill prec[][101],ill s,ill row,ill m,ill k)
{
if(prec[s][row])
return prec[s][row];
else
{
if(row==m+1)
return s;
ill best=-1;
int j=row;
for(int i=0;i<col[j].size();i++)
{
if(s+col[j][i] <= k)
{
ill x = ret (col,prec,s+col[j][i],row+1,m,k);
if ((best==-1)||(x>best))
best=x;
}
}
prec[s][row]=best;
return best;
}
}
The problem can be solved using dynamic programming by choosing as state the pair (s, row) where s is the current sum and row is the next row we need to include.
The maximal principle is valid because no matter on which choices we made in previous rows the result depends only on the current sum and the current row index.
In code (Python)
cache = {}
data = [[2, 3, 4],
[2, 3, 4],
[2, 3, 4]]
M = 3
K = 10
def msum(s, row):
try:
return cache[s, row]
except KeyError:
if row == M:
return s
best = None
for v in data[row]:
if s+v <= K:
x = msum(s+v, row+1)
if best is None or x > best:
best = x
cache[s, row] = best
return best
print msum(0, 0)
The function returns None if no solution exists (i.e. if even taking the smallest value from each row we end up exceeding K).
A brute force approach:
bool increase(const std::vector<std::vector<int>>& v, std::vector<std::size_t>& it)
{
for (std::size_t i = 0, size = it.size(); i != size; ++i) {
const std::size_t index = size - 1 - i;
++it[index];
if (it[index] > v[index].size()) {
it[index] = 0;
} else {
return true;
}
}
return false;
}
int sum(const std::vector<std::vector<int>>& v, const std::vector<std::size_t>& it)
{
int res = 0;
for (std::size_t i = 0; i != it.size(); ++i) {
res += v[i][it[i]];
}
return res;
}
int maximum_sum_less_or_equal_to_K(const std::vector<std::vector<int>>& v, int K)
{
std::vector<std::size_t> it(v.size());
int res = K + 1;
do {
int current_sum = sum(v, it);
if (current_sum <= K) {
if (res == K + 1 || res < current_sum) {
res = current_sum;
}
}
} while (increase(v, it));
if (res == K + 1) {
// Handle no solution
}
return res;
}
it has the current selection of each row.
This can be solved using boolean 2D table. The value of dp[r][s] is set to true, if its possible to generate sum 's' , using exactly 'r' rows (i.e exactly one element from each of the [0 to r-1] rows). Using this dp table, we can compute next state as
dp[r+1][s] |= dp[r][s-A[r+1][c]] ; 0 < c < N, 0 < s <= K
where N is number of columns(0-based indexing). Finally return the value of max index set in M-1 row of dp table
Following is a bottom-up implementation
// Assuming input matrix is M*N
int maxSum() {
memset(dp, false, sizeof(dp));
//Initialise base row
for (int c = 0; c < N; ++c)
dp[0][A[0][c]] = true;
for ( int r = 1; r < M; ++r ) {
for ( int c = 0; c < N; ++c) {
// For each A[r][c], check for all possible values of sum upto K
for (int sum = 0; sum <= K; ++sum) {
if ( sum-A[r][c] >= 0 && dp[r-1][sum-A[r][c]] )
dp[r][sum] = true;
}
}
}
// Return max possible value <= K
for (int sum = K; sum >= 0; --sum) {
if ( dp[M-1][sum] )
return sum;
}
return 0;
}
Note that dp table values for current row depend only on previous row, as such space optimization trick can be used to solve it using 1-D table
Suppose the array is 1 2 3 4 5
Here N = 5 and we have to select 3 elements and we cannot select more than 2 consecutive elements, so P = 3 and k = 2. So the output here will be 1 + 2 + 4 = 7.
I came up with a recursive solution, but it has an exponential time complexity. Here is the code.
#include<iostream>
using namespace std;
void mincost_hoarding (int *arr, int max_size, int P, int k, int iter, int& min_val, int sum_sofar, int orig_k)
{
if (P == 0)
{
if (sum_sofar < min_val)
min_val = sum_sofar;
return;
}
if (iter == max_size)
return;
if (k!=0)
{
mincost_hoarding (arr, max_size, P - 1, k - 1, iter + 1, min_val, sum_sofar + arr[iter], orig_k);
mincost_hoarding (arr, max_size, P, orig_k, iter + 1, min_val, sum_sofar, orig_k);
}
else
{
mincost_hoarding (arr, max_size, P, orig_k, iter + 1, min_val, sum_sofar, orig_k);
}
}
int main()
{
int a[] = {10, 5, 13, 8, 2, 11, 6, 4};
int N = sizeof(a)/sizeof(a[0]);
int P = 2;
int k = 1;
int min_val = INT_MAX;
mincost_hoarding (a, N, P, k, 0, min_val, 0, k);
cout<<min_val;
}
Also, if supposedly P elements cannot be selected following the constraint, then we return INT_MAX.
I was asked this question in an interview. After proposing this solution, the interviewer was expecting something faster. Maybe, a DP approach towards the problem. Can someone propose a DP algorithm if there exists one, or a faster algorithm.
I have tried various tests cases and got correct answers. If you find some test cases that are giving incorrect response, please point that out too.
Below is a Java Dynamic Programming algorithm.
(the C++ version should look very similar)
It basically works as follows:
Have a 3D array of [pos][consecutive length][length]
Here length index = actual length - 1), so [0] would be length 1, similarly for consecutive length. This was done since there's no point to having length 0 anywhere.
At every position:
If at length 0 and consecutive length 0, just use the value at pos.
Otherwise, if consecutive length 0, look around for the minimum in all the previous positions (except pos - 1) with length - 1 and use that plus the value at pos.
For everything else, if pos > 0 && consecutive length > 0 && length > 0,
use [pos-1][consecutive length-1][length-1] plus the value at pos.
If one of those are 0, initialize it to an invalid value.
Initially it felt like one only needs 2 dimensions for this problem, however, as soon as I tried to figure it out, I realized I needed a 3rd.
Code:
int[] arr = {1, 2, 3, 4, 5};
int k = 2, P = 3;
int[][][] A = new int[arr.length][P][k];
for (int pos = 0; pos < arr.length; pos++)
for (int len = 0; len < P; len++)
{
int min = 1000000;
if (len > 0)
{
for (int pos2 = 0; pos2 < pos-1; pos2++)
for (int con = 0; con < k; con++)
min = Math.min(min, A[pos2][len-1][con]);
A[pos][len][0] = min + arr[pos];
}
else
A[pos][0][0] = arr[pos];
for (int con = 1; con < k; con++)
if (pos > 0 && len > 0)
A[pos][len][con] = A[pos-1][len-1][con-1] + arr[pos];
else
A[pos][len][con] = 1000000;
}
// Determine the minimum sum
int min = 100000;
for (int pos = 0; pos < arr.length; pos++)
for (int con = 0; con < k; con++)
min = Math.min(A[pos][P-1][con], min);
System.out.println(min);
Here we get 7 as output, as expected.
Running time: O(N2k + NPk)
I want to solve this CodeChef challenge:
Suppose We are given an array A of N(of range 100,000) elements. We are to find the count of all pairs of 3 such elements 1<=Ai,Aj,Ak<=30,000 such that
Aj-Ai = Ak- Aj and i < j < k
In other words Ai,Aj,Ak are in Arithmetic Progression. For instance for Array :
9 4 2 3 6 10 3 3 10
so The AP are:
{2,6,10},{9,6,3},{9,6,3},{3,3,3},{2,6,10}
So the required answer is 5.
My Approach
What I tried is take 30,000 long arrays named past and right. Initially right contains the count of each 1-30,000 element.
If we are at ith position past stores the count of array value before i and right stores the count of array after i. I simply loop for all possible common difference in the array. Here is the code :
right[arr[1]]--;
for(i=2;i<=n-1;i++)
{
past[arr[i-1]]++;
right[arr[i]]--;
k=30000 - arr[i];
if(arr[i] <= 15000)
k=arr[i];
for(d=1;d<=k;d++)
{
ans+= right[arr[i] + d]*past[arr[i]-d] + past[arr[i] + d]*right[arr[i]-d];
}
ans+=past[arr[i]]*right[arr[i]];
}
But this gets me Time Limit Exceeded. Please help with a better algorithm.
You can greatly cut execution time if you make a first pass over the list and only extract number pairs that it is possible to have an 3 term AP between (difference is 0 mod 2). And then iterating between such pairs.
Pseudo C++-y code:
// Contains information about each beginning point
struct BeginNode {
int value;
size_t offset;
SortedList<EndNode> ends; //sorted by EndNode.value
};
// Contains information about each class of end point
struct EndNode {
int value;
List<size_t> offsets; // will be sorted without effort due to how we collect offsets
};
struct Result {
size_t begin;
size_t middle;
size_t end;
};
SortedList<BeginNode> nodeList;
foreach (auto i : baseList) {
BeginNode begin;
node.value = i;
node.offset = i's offset; //you'll need to use old school for (i=0;etc;i++) with this
// baseList is the list between begin and end-2 (inclusive)
foreach (auto j : restList) {
// restList is the list between iterator i+2 and end (inclusive)
// we do not need to consider i+1, because not enough space for AP
if ((i-j)%2 == 0) { //if it's possible to have a 3 term AP between these two nodes
size_t listOffset = binarySearch(begin.ends);
if (listOffset is valid) {
begin.ends[listOffset].offsets.push_back(offsets);
} else {
EndNode end;
end.value = j;
end.offsets.push_back(j's offset);
begin.ends.sorted_insert(end);
}
}
}
if (begin has shit in it) {
nodeList.sorted_insert(begin);
}
}
// Collection done, now iterate over collection
List<Result> res;
foreach (auto node : nodeList) {
foreach (auto endNode : node.ends) {
foreach (value : sublist from node.offset until endNode.offsets.last()) {
if (value == average(node.value, endNode.value)) {
// binary_search here to determine how many offsets in "endNode.offsets" "value's offset" is less than.
do this that many times:
res.push_back({node.value, value, endNode.value});
}
}
}
}
return res;
Here's a simple C version of the solution that takes advantage of the Ai + Ak must be even test:
#include <stdio.h>
static int arr[] = {9, 4, 2, 3, 6, 10, 3, 3, 10};
int main ()
{
int i, j, k;
int sz = sizeof(arr)/sizeof(arr[0]);
int count = 0;
for (i = 0; i < sz - 2; i++)
{
for (k = i + 2; k < sz; k++)
{
int ik = arr[i] + arr[k];
int ikdb2 = ik / 2;
if ((ikdb2 * 2) == ik) // if ik is even
{
for (j = i + 1; j < k; j++)
{
if (arr[j] == ikdb2)
{
count += 1;
printf("{%d, %d, %d}\n", arr[i], arr[j], arr[k]);
}
}
}
}
}
printf("Count is: %d\n", count);
}
and the console dribble:
tmp e$ cc -o triples triples.c
tmp e$ ./triples
{9, 6, 3}
{9, 6, 3}
{2, 6, 10}
{2, 6, 10}
{3, 3, 3}
Count is: 5
tmp e$
This more complicated version keeps a list of Aj indexed by value to go from n-cubed to n-squared (kinda).
#include <stdio.h>
#include <stdint.h>
static uint32_t arr[] = {9, 4, 2, 3, 6, 10, 3, 3, 10};
#define MAX_VALUE 100000u
#define MAX_ASIZE 30000u
static uint16_t index[MAX_VALUE+1];
static uint16_t list[MAX_ASIZE+1];
static inline void remove_from_index (int subscript)
{
list[subscript] = 0u; // it is guaranteed to be the last element
uint32_t value = arr[subscript];
if (value <= MAX_VALUE && subscript == index[value])
{
index[value] = 0u; // list now empty
}
}
static inline void add_to_index (int subscript)
{
uint32_t value = arr[subscript];
if (value <= MAX_VALUE)
{
list[subscript] = index[value]; // cons
index[value] = subscript;
}
}
int main ()
{
int i, k;
int sz = sizeof(arr)/sizeof(arr[0]);
int count = 0;
for (i = 0; i < sz - 2; i++)
{
for (k = i; k < sz; k++) remove_from_index(k);
for (k = i + 2; k < sz; k++)
{
uint32_t ik = arr[i] + arr[k];
uint32_t ikdb2 = ik / 2;
add_to_index(k-1); // A(k-1) is now a legal middle value
if ((ikdb2 * 2) == ik) // if ik is even
{
uint16_t rover = index[ikdb2];
while (rover != 0u)
{
count += 1;
printf("{%d, %d, %d}\n", arr[i], arr[rover], arr[k]);
rover = list[rover];
}
}
}
}
printf("Count is: %d\n", count);
}
and the dribble:
tmp e$ cc -o triples triples.c
tmp e$ ./triples
{9, 6, 3}
{9, 6, 3}
{2, 6, 10}
{2, 6, 10}
{3, 3, 3}
Count is: 5
tmp e$
Suppose I am given:
A range of integers iRange (i.e. from 1 up to iRange) and
A desired number of combinations
I want to find the number of all possible combinations and print out all these combinations.
For example:
Given: iRange = 5 and n = 3
Then the number of combinations is iRange! / ((iRange!-n!)*n!) = 5! / (5-3)! * 3! = 10 combinations, and the output is:
123 - 124 - 125 - 134 - 135 - 145 - 234 - 235 - 245 - 345
Another example:
Given: iRange = 4 and n = 2
Then the number of combinations is iRange! / ((iRange!-n!)*n!) = 4! / (4-2)! * 2! = 6 combinations, and the output is:
12 - 13 - 14 - 23 - 24 - 34
My attempt so far is:
#include <iostream>
using namespace std;
int iRange= 0;
int iN=0;
int fact(int n)
{
if ( n<1)
return 1;
else
return fact(n-1)*n;
}
void print_combinations(int n, int iMxM)
{
int iBigSetFact=fact(iMxM);
int iDiffFact=fact(iMxM-n);
int iSmallSetFact=fact(n);
int iNoTotComb = (iBigSetFact/(iDiffFact*iSmallSetFact));
cout<<"The number of possible combinations is: "<<iNoTotComb<<endl;
cout<<" and these combinations are the following: "<<endl;
int i, j, k;
for (i = 0; i < iMxM - 1; i++)
{
for (j = i + 1; j < iMxM ; j++)
{
//for (k = j + 1; k < iMxM; k++)
cout<<i+1<<j+1<<endl;
}
}
}
int main()
{
cout<<"Please give the range (max) within which the combinations are to be found: "<<endl;
cin>>iRange;
cout<<"Please give the desired number of combinations: "<<endl;
cin>>iN;
print_combinations(iN,iRange);
return 0;
}
My problem:
The part of my code related to the printing of the combinations works only for n = 2, iRange = 4 and I can't make it work in general, i.e., for any n and iRange.
Your solution will only ever work for n=2. Think about using an array (combs) with n ints, then the loop will tick up the last item in the array. When that item reaches max update then comb[n-2] item and set the last item to the previous value +1.
Basically working like a clock but you need logic to find what to uptick and what the next minimum value is.
Looks like a good problem for recursion.
Define a function f(prefix, iMin, iMax, n), that prints all combinations of n digits in the range [iMin, iMax] and returns the total number of combinations. For n = 1, it should print every digit from iMin to iMax and return iMax - iMin + 1.
For your iRange = 5 and n = 3 case, you call f("", 1, 5, 3). The output should be 123 - 124 - 125 - 134 - 135 - 145 - 234 - 235 - 245 - 345.
Notice that the first group of outputs are simply 1 prefixed onto the outputs of f("", 2, 5, 2), i.e. f("1", 2, 5, 2), followed by f("2", 3, 5, 2) and f("3", 4, 5, 2). See how you would do that with a loop. Between this, the case for n = 1 above, and traps for bad inputs (best if they print nothing and return 0, it should simplify your loop), you should be able to write f().
I'm stopping short because this looks like a homework assignment. Is this enough to get you started?
EDIT: Just for giggles, I wrote a Python version. Python has an easier time throwing around sets and lists of things and staying legible.
#!/usr/bin/env python
def Combos(items, n):
if n <= 0 or len(items) == 0:
return []
if n == 1:
return [[x] for x in items]
result = []
for k in range(len(items) - n + 1):
for s in Combos(items[k+1:], n - 1):
result.append([items[k]] + s)
return result
comb = Combos([str(x) for x in range(1, 6)], 3)
print len(comb), " - ".join(["".join(c) for c in comb])
Note that Combos() doesn't care about the types of the items in the items list.
Here is your code edited :D :D with a recursive solution:
#include <iostream>
int iRange=0;
int iN=0; //Number of items taken from iRange, for which u want to print out the combinations
int iTotalCombs=0;
int* pTheRange;
int* pTempRange;
int find_factorial(int n)
{
if ( n<1)
return 1;
else
return find_factorial(n-1)*n;
}
//--->Here is another solution:
void print_out_combinations(int *P, int K, int n_i)
{
if (K == 0)
{
for (int j =iN;j>0;j--)
std::cout<<P[j]<<" ";
std::cout<<std::endl;
}
else
for (int i = n_i; i < iRange; i++)
{
P[K] = pTheRange[i];
print_out_combinations(P, K-1, i+1);
}
}
//Here ends the solution...
int main()
{
std::cout<<"Give the set of items -iRange- = ";
std::cin>>iRange;
std::cout<<"Give the items # -iN- of iRange for which the combinations will be created = ";
std::cin>>iN;
pTheRange = new int[iRange];
for (int i = 0;i<iRange;i++)
{
pTheRange[i]=i+1;
}
pTempRange = new int[iN];
iTotalCombs = (find_factorial(iRange)/(find_factorial(iRange-iN)*find_factorial(iN)));
std::cout<<"The number of possible combinations is: "<<iTotalCombs<<std::endl;
std::cout<<"i.e.the combinations of "<<iN<<" elements drawn from a set of size "<<iRange<<" are: "<<std::endl;
print_out_combinations(pTempRange, iN, 0);
return 0;
}
Here's an example of a plain recursive solution. I believe there exists a more optimal implementation if you replace recursion with cycles. It could be your homework :)
#include <stdio.h>
const int iRange = 9;
const int n = 4;
// A more efficient way to calculate binomial coefficient, in my opinion
int Cnm(int n, int m)
{
int i;
int result = 1;
for (i = m + 1; i <= n; ++i)
result *= i;
for (i = n - m; i > 1; --i)
result /= i;
return result;
}
print_digits(int *digits)
{
int i;
for (i = 0; i < n; ++i) {
printf("%d", digits[i]);
}
printf("\n");
}
void plus_one(int *digits, int index)
{
int i;
// Increment current digit
++digits[index];
// If it is the leftmost digit, run to the right, setup all the others
if (index == 0) {
for (i = 1; i < n; ++i)
digits[i] = digits[i-1] + 1;
}
// step back by one digit recursively
else if (digits[index] > iRange) {
plus_one(digits, index - 1);
}
// otherwise run to the right, setting up other digits, and break the recursion once a digit exceeds iRange
else {
for (i = index + 1; i < n; ++i) {
digits[i] = digits[i-1] + 1;
if (digits[i] > iRange) {
plus_one(digits, i - 1);
break;
}
}
}
}
int main()
{
int i;
int digits[n];
for (i = 0; i < n; ++i) {
digits[i] = i + 1;
}
printf("%d\n\n", Cnm(iRange, n));
// *** This loop has been updated ***
while (digits[0] <= iRange - n + 1) {
print_digits(digits);
plus_one(digits, n - 1);
}
return 0;
}
This is my C++ function with different interface (based on sts::set) but performing the same task:
typedef std::set<int> NumbersSet;
typedef std::set<NumbersSet> CombinationsSet;
CombinationsSet MakeCombinations(const NumbersSet& numbers, int count)
{
CombinationsSet result;
if (!count) throw std::exception();
if (count == numbers.size())
{
result.insert(NumbersSet(numbers.begin(), numbers.end()));
return result;
}
// combinations with 1 element
if (!(count - 1) || (numbers.size() <= 1))
{
for (auto number = numbers.begin(); number != numbers.end(); ++number)
{
NumbersSet single_combination;
single_combination.insert(*number);
result.insert(single_combination);
}
return result;
}
// Combinations with (count - 1) without current number
int first_num = *numbers.begin();
NumbersSet truncated_numbers = numbers;
truncated_numbers.erase(first_num);
CombinationsSet subcombinations = MakeCombinations(truncated_numbers, count - 1);
for (auto subcombination = subcombinations.begin(); subcombination != subcombinations.end(); ++subcombination)
{
NumbersSet cmb = *subcombination;
// Add current number
cmb.insert(first_num);
result.insert(cmb);
}
// Combinations with (count) without current number
subcombinations = MakeCombinations(truncated_numbers, count);
result.insert(subcombinations.begin(), subcombinations.end());
return result;
}
I created a next_combination() function similar to next_permutation(), but valid input is required to make it work
//nums should always be in ascending order
vector <int> next_combination(vector<int>nums, int max){
int size = nums.size();
if(nums[size-1]+1<=max){
nums[size-1]++;
return nums;
}else{
if(nums[0] == max - (size -1)){
nums[0] = -1;
return nums;
}
int pos;
int negate = -1;
for(int i = size-2; i>=0; i--){
if(nums[i]+1 <= max + negate){
pos = i;
break;
}
negate --;
}
nums[pos]++;
pos++;
while(pos<size){
nums[pos] = nums[pos-1]+1;
pos++;
}
}
return nums;
}