We Keep Coding

Find all combinations of an array and get top k sum elements

I have an array of numbers say [1,2,3,1,1000] , now I want to get all possible combinations of this array and calculate its sum. Combinations are valid such that two combinations have different subset of elements. Then order all the sum values in descending order and get the top k elements.
Example:
[1,2,3,1,1000]
Combinations:
Duplicates of earlier ones are striked out, for example (3,1) matches the earlier (1,3).
(), (1), (2), (3), (1), (1000), (1,2), (1,3), (1,1), (1,1000), (2,3), (2,1), (2,1000), (3,1), (3,1000), (1,1000), (1,2,3), (1,2,1), (1,2,1000), (1,3,1), (1,3,1000), (1,1,1000), (2,3,1), (2,3,1000), (2,1,1000), (3,1,1000), (1,2,3,1), (1,2,3,1000), (1,2,1,1000), (1,3,1,1000), (2,3,1,1000), (1,2,3,1,1000)
And the corresponding sums:
0, 1, 2, 3, 1, 1000, 3, 4, 2, 1001, 5, 3, 1002, 4, 1003, 1001, 6, 4, 1003, 5, 1004, 1002, 6, 1005, 1003, 1004, 7, 1006, 1004, 1005, 1006, 1007
Getting top k=3, sums = 1007, 1006, 1005
So output is [1007, 1006, 1005].
Constraints:
Array size n = 1 to 105
Array elements -109 to 109
k ranges from 1 to 2000
This is my code, reference taken from here:
static List<Long> printDistSum(int arr[]) {
List<Long> list = new ArrayList<>();
int n = arr.length;
// There are totoal 2^n subsets
long total = (long) Math.pow(2, n);
// Consider all numbers from 0 to 2^n - 1
for (int i = 0; i < total; i++) {
long sum = 0;
// Consider binary representation of
// current i to decide which elements
// to pick.
for (int j = 0; j < n; j++)
if ((i & (1 << j)) != 0)
sum += arr[j];
// Print sum of picked elements.
list.add(sum);
}
return list;
}
This code works for small range of inputs but times out for large range of inputs. How to solve this program.

I probably have solution that should be good enough. It has time complexity O(n * k * log(k)).
First we need to calculate max sum - sum of all positive values.
Next we need to iterate over positive values, from smallest to largest. For each of these values we calculate sums of new combinations (at the start we have one combination with max sum).
New combinations will not contains given value so we need to substract it from sum.
At the end we need to iterate over negative values. These values are not belongs to combinations from previous step so we need to add these values to sums.
In every iteration are needed only k maximum sums. I used the PriorityQueue to store these sums. That class use heap data structure so adding/removing values has logarithmic time.
Code:
private static long[] findSums(int[] array, int k) {
long maxSum = Arrays.stream(array).filter(it -> it >= 0).sum();
int[] positives = Arrays.stream(array).filter(it -> it >= 0).sorted().toArray();
int[] negatives = Arrays.stream(array).filter(it -> it < 0).sorted().toArray();
// sort time complexity is O(n*log(n))
PriorityQueue<Long> sums = new PriorityQueue<>(k); // priority queue is implemented using heap so adding element has time complexity O(log(n))
sums.add(maxSum); // we start with max sum - combination of all positive elements
int previous = Integer.MIN_VALUE;
Long[] previousAddedSums = {};
Long[] sumsToIterate;
// iterate over positive values
for (int i = 0; i < positives.length; i++) {
if (positives[i] == previous) {
sumsToIterate = previousAddedSums;
} else {
sumsToIterate = sums.toArray(new Long[sums.size()]);
}
previousAddedSums = new Long[sumsToIterate.length];
for (int j = 0; j < sumsToIterate.length; j++) {
long newSum = sumsToIterate[j] - positives[i];
// new sum is calculated - value positives[i] is removed from combination (subtracted from sum of that combination)
sums.add(newSum);
previousAddedSums[j] = newSum;
if (sums.size() > k) {
sums.poll(); // only first k maximum sums are needed at the moment
}
}
previous = positives[i];
}
previous = Integer.MAX_VALUE;
// iterate over negative values in reverse order
for (int i = negatives.length - 1; i >= 0; i--) {
if (negatives[i] == previous) {
sumsToIterate = previousAddedSums;
} else {
sumsToIterate = sums.toArray(new Long[sums.size()]);
}
previousAddedSums = new Long[sumsToIterate.length];
for (int j = 0; j < sumsToIterate.length; j++) {
long newSum = sumsToIterate[j] + negatives[i]; // value negatives[i] is added to combination (added to sum of that combination)
sums.add(newSum);
previousAddedSums[j] = newSum;
if (sums.size() > k) {
sums.poll();
}
}
previous = negatives[i];
}
long[] result = new long[sums.size()];
for (int i = sums.size() - 1; i >=0 ; i--) {
result[i] = sums.poll();
}
// get sums from priority queue in proper order
return result;
// this whole method has time complexity O(n * k * log(k))
// k is less than or equal 2000 so it should be good enough ;)
}
Demo: https://ideone.com/yf6POI
Edit: I have fixed my solution. Instead of iterating over distinct values I check if current value is same like previous. In that case I use combinations (sums) created in previous step. This prevents from creating duplicates of combinations.
I'm sorry if I didn't explain this well enough. I don't have experience in describing algorithmic / mathematical things in english.

Pls ignore all previous posts cuz they are all wrong.
Intuitively, we gotta use backtrack to find all desired combos, but it's impossible to backtrack on 10^5 elements.
Constraint 1 <= n <= 10^5 alludes that our algorithm bottlenecked by O(nlogn) sorting
Constraint 1 <= k <= min(2000,2^n) alludes that we can backtrack on k elements since k is less than 11. 2^11=2024/log(2000)=11 -- actually this "2^n" gives away solution :)
My algorithm (nlog(n) + 2^k)
sort the array
Record the highest score combo which is the sum of all positive integers
Find a window in the sorted array of math.min(log(k)--which is less than 11,n) elements -- worst case, this window consists of the
lowest 11 absolute values in the sorted array. Several approaches to
achieve that, since the candidates must be inside 22 elements
window(11 smallest positive values + 11 biggest negative values), we
can use PriorityQueue of size 11 scanning over these 22 elements. or
we can use two pointers to find the sliding window of size 11.
backtrack on this 11 absolute value elements window, find sum of each combo and put them into a size k/k-1 PriorityQueue. (k is for
the case that there's no positive elements)
result is the sum of all positive integers plus (sum deducted by each of k-1 elements in PriorityQueue).

I was also asked the same question yesterday but sadly I was not able to solve it yesterday. I have tried solving it today and think I have the answer today.
First of all I don't think that different subsets mean different costs in a set i.e in array of [1,2,3,1] both subsets are valid => [1,2,3] and [2,3,1] as they both use different 1's. Now here is my solution keeping this in mind. But if you really want to keep distinct elements in set then you can simply remove the multiple elements and do partial_sort then.
Logic
Store sum of all +ve nos. in a variable, say maxsum.
Convert the negative nos. to their absolute values.
Get lowest min(k-1, n) elements in sorted order.
Find all their combinations and subtract them from the maxsum.
While finding all their combinations we only need lowest k-1 combos. So we have to find a way to keep the number of combinations to that. For that use a sorted data structure and limit its size to k and then for every element in the sorted array iterate through the combos and add those combos to the sorted data structure if the end element of that data structure is greater. Also pop the end element after that.
For taking care of the above point I am using 2 vectors since the order already remains sorted.
The proposed solution has time complexity of O(n*log(k) + k^2).
#include <iostream>
#include <vector>
#include <algorithm>
using namespace std;
typedef long long int ll;
template <class T>
void print(vector<T> topSumm)
{
for (ll itr : topSumm)
cout << itr << '\t';
cout << '\n';
}
vector<ll> mergeSortedArrays(vector<ll> &minns, vector<ll> &temp)
{
vector<ll> ans(minns.size() + temp.size());
int i{0}, j{0}, k{0};
while (i < minns.size() && j < temp.size())
{
if (temp[j] < minns[i])
ans[k++] = temp[j++];
else
ans[k++] = minns[i++];
}
while (i < minns.size())
ans[k++] = minns[i++];
while (j < temp.size())
ans[k++] = temp[j++];
return ans;
}
vector<ll> topKSum(vector<int> &arr, int k)
{
int n{(int)arr.size()};
ll maxSumm{0};
for (int i{0}; i < n; ++i)
{
if (arr[i] > 0)
maxSumm += arr[i];
else
arr[i] = -arr[i];
}
int nk{min(k - 1, n)};
partial_sort(arr.begin(), arr.begin() + nk, arr.end());
vector<ll> minns{0, maxSumm};
ll summ{};
bool breakOuter{false};
for (int i{0}; i < nk; ++i)
{
vector<ll> temp;
for (ll nums : minns)
{
summ = nums + arr[i];
if (minns.size() + temp.size() < k)
temp.push_back(summ);
else
{
if (minns.back() > summ)
{
minns.pop_back();
temp.push_back(summ);
}
else
{
if (nums == 0)
breakOuter = true;
break;
}
}
}
if (breakOuter)
break;
minns = mergeSortedArrays(minns, temp);
}
vector<ll> ans(k);
int i{0};
for (ll nums : minns)
ans[i++] = maxSumm - nums;
return ans;
}
int main()
{
int t;
cin >> t;
while (t--)
{
int n, k;
cin >> n >> k;
vector<int> arr(n);
ll maxSumm{0};
for (int i{0}; i < n; ++i)
cin >> arr[i];
vector<ll> topSums = topKSum(arr, k);
print<ll>(topSums);
}
return 0;
}

Sort digits of a given integer, without '0'

I'm trying to sort the digits of a given integer by turning the integer to a String and creating an array by the size of that String length.
I'm using the modulu option to separate the digits and in the end I'm reversing it by multiplying by 10.
The problem that it's going out of bound each time and I don't know how to make the size of the array to work good for me.
Here are the code :
String s = String.valueOf(num);
int[] arr = new int[s.length()+1];
while(num != 0) {
arr[(int) num % 10]++;
num = num / 10;
}
long result = 0;
for(int i = 0 ; i < arr.length - 1 ; i++){
for(int j = 0 ; j < arr[i] ; j++) {
result = result * 10;
result = result + i;
}
}
return result;

There seems to be a lot of overkill solving this, as in a lot of code, so here is my take on it.
static int sortDigits(int num) {
char[] arr = Integer.toString(num).toCharArray();
Arrays.sort(arr);
return Integer.parseInt(new String(arr));
}
Test
System.out.println(sortDigits(4201514)); // 112445
You can of course do the same for the long and BigInteger versions:
static long sortDigits(long num) {
char[] arr = Long.toString(num).toCharArray();
Arrays.sort(arr);
return Long.parseLong(new String(arr));
}
static BigInteger sortDigits(BigInteger num) {
char[] arr = num.toString().toCharArray();
Arrays.sort(arr);
return new BigInteger(new String(arr));
}

If I understand your question correctly, when given an integer, you want to "sort" each digit, ignoring 0's.
To do so, so you can first convert it to a string:
String value = String.valueOf(num);
Since you have a string, you can use the split() function to split each 'number' like so:
String[] numbers = value.split("");
Then, you can find the indexes of 0's (and store it somewhere).
ArrayList<Integer> indexes = new ArrayList<>();
for (int i = 0; i < numbers.length; i++) {
if (numbers[i].equals("0")) {
indexes.add(i);
}
}
Then, you can sort the array of strings (numbers) using the sort() function:
Arrays.sort(numbers);
Then, you can remove the 0's like this (by creating a new ArrayList):
ArrayList<String> copy = new ArrayList<>();
for (String s : numbers) {
if (!s.equals("0")) {
copy.add(s);
}
}
(Here, you may use ArrayUtils if you already imported the library.)
Then, concatenate each element to make one entire string with join():
String result = String.join("", copy);
Finally, using the indexes, insert 0's to where they were located at initially:
for (int i : indexes) {
result = result.substring(0, i) + "0" + result.substring(i);
}
result would be what you want.
Note: This might not be the most sufficient way to do it, so you can modify it anywhere you want.

Based on your code I made a few modification
size of array should be 10 since in a number only 0 to 9 digits are possible
use this array to make a frequency array of occurrence of each digit
iterate over the array from 1 to 9 and make a sorted number
public static long sortInt(long num) {
int[] arr = new int[10];
while(num != 0) {
arr[(int) num % 10] ++;
num /= 10;
}
long result = 0;
for(int i = 1 ; i < arr.length ; i++)
while(arr[i]-- != 0)
result = result * 10 + i;
return result;
}

Trying to create a array with the intersection of two arrays but fails at creating array with the proper structure

So, I am trying to create 2 randomly generated arrays,(a, and b, each with 10 unique whole numbers from 0 to 20), and then creating 2 arrays with the info of the last two. One containing the numbers that appear in both a and b, and another with the numbers that are unique to a and to b. The arrays must be listed in a "a -> [1, 2, 3,...]" format. At the moment I only know how to generate the 2 arrays, and am currently at the Intersection part. The problem is, that I can create a array with the correct list of numbers, but it will have the same length of the other two, and the spaces where it shouldn't have anything, it will be filled with 0s when its supposed to create a smaller array with only the right numbers.
package tps.tp1.pack2Arrays;
public class P02ArraysExtractUniqsAndReps {
public static void main(String[] args) {
int nbr = 10;
int min = 0;
int max = 20;
generateArray(nbr, min, max);
System.out.println();
}
public static int[] generateArray(int nbr, int min, int max) {
int[] a = new int[nbr];
int[] b = new int[nbr];
int[] s = new int[nbr];
s[0] = 0;
for (int i = 0; i < a.length; i++) {
a[i] = (int) (Math.random() * (max - min));
b[i] = (int) (Math.random() * (max - min));
for (int j = 0; j < i; j++) {
if (a[i] == a[j]) {
i--;
}
if (b[i] == b[j]) {
i--;
}
}
}
System.out.println("a - > " + Arrays.toString(a));
System.out.println("b - > " + Arrays.toString(b));
for (int k = 0; k < a.length; k++) {
for (int l = 0; l < b.length; l++) {
if (a[k] == b[l]) {
s[l] = b[l];
}else {
}
}
}
System.out.println("(a ∪ (b/(a ∩ b)) - > " + Arrays.toString(s));
return null;
}
public static boolean hasValue(int[] array, int value) {
for (int i = 0; i < array.length; i++) {
if (array[i] == value) {
return true;
}
}
return false;
}
}
Is there any way to create the array without the incorrect 0s? (I say incorrect because it is possible to have 0 in both a and b).
Any help/clarification is appreciated.

First, allocate an array large enough to hold the intersection. It needs to be no bigger that the smaller of the source arrays.
When you add a value to the intersection array, always add it starting at the beginning of the array. Use a counter to update the next position. This also allows the value 0 to be a valid value.
Then when finished. use Array.copyOf() to copy only the first part of the array to itself, thus removing the empty (unfilled 0 value) spaces. This works as follow assuming count is the index you have been using to add to the array: Assume count = 3
int[] inter = {1,2,3,0,0,0,0};
inter = Arrays.copyOf(inter, count);
System.out.println(Arrays.toString(inter);
prints
[1,2,3]
Here is an approach using a List
int[] b = {4,3,1,2,5,0,2};
int [] a = {3,5,2,3,7,8,2,0,9,10};
Add one of the arrays to the list.
List<Integer> list = new ArrayList<>();
for(int i : a) {
list.add(i);
}
Allocate the intersection array with count used as the next location. It doesn't matter which array's length you use.
int count = 0;
int [] intersection = new int[a.length];
Now simply iterate thru the other array.
if the list contains the value, add it to the intersection array.
then remove it from the list and increment count. NOTE - The removed value must be converted to an Integer object, otherwise, if a simple int value, it would be interpreted as an index and the value at that index would be removed and not the actual value itself (or an Exception might be thrown).
once finished the intersection array will have the values and probably unseen zeroes at the end.
for(int i = 0; i < b.length; i++) {
int val = b[i];
if (list.contains(val)) {
intersection[count++] = val;
list.remove(Integer.valueOf(val));
}
}
To shorten the array, use the copy method mentioned above.
intersection = Arrays.copyOf(intersection, count);
System.out.println(Arrays.toString(intersection));
prints
[3, 2, 5, 0, 2]
Note that it does not matter which array is which. If you reverse the arrays for a and b above, the same intersection will result, albeit in a different order.

The first thing I notice is that you are declaring your intersection array at the top of the method.
int[] s = new int[nbr];
You are declaring the same amount of space for the array regardless of the amount you actually use.
Method Arrays.toString(int []) will print any uninitialized slots in the array as "0"
There are several different approaches you can take here:
You can delay initializing the array until you have determined the size of the set you are dealing with.
You can transfer your content into another well sized array after figuring out your result set.
You could forego using Array.toString, and build the string up yourself.

I am stuck at implementing Radix sort recursively

I'm required to implement a programm that sorts numbers ranging from 0 to 99999 recursively (this is basically Radix sort). The process itself is kinda simpel: The user types in an array that contains those numbers in the main method. Then, the main method calls for the sort-method where I create a two-dimensional array named 'space' with 10 rows and 1 column. Then, I divide every number in the array by the digit, which would be 10.000 in the first run. So, for example, 23456 / 10000 = 2,3456 = 2 (in java), hence, the programm puts this number in space[2][0], so in the second row. Then, we take this entire row and extend it, which is done in the putInBucket-method. We do this in order to make sure that we can put another number into the same row.
We do this for every number that is inside the 'numbers'-array. Then, we want to work with these rows and sort them again by the same principle, but now we take a look at the second digit. We want to do this from left to right, not from right to left. So, if our second row would look like this
[23456, 24567],
we'd want to compare the 3 and the 4, which leads to 23456 < 24567.
We do this with the help of the recursive call at the end of the sort method. Now, this is where I am lost. I simply don't know how to manipulate the digit-variable in order to be able to work with the second, third, ... digit of each number. In the first run, as you see, this can be simply done by dividing through 10.000, but I didn't find a way to go further from here.
Please note: Yes, this is a homework question, hence, I'm only allowed to use primitives here. We didn't go through stuff like math.pow(...) yet. Thanks in advance!
public static int[] sort(int[] numbers, int digit) {
if (numbers.length == 0)
return numbers;
int[][]space = new int[10][1];
int i, j = 0;
for (j = 0; j < numbers.length; j++) {
i = numbers[j] / digit;
space[i][0] = numbers[j];
space[i] = putInBucket(space[i], numbers[j]);
}
for (i = 0; i < space[i].length; i++) {
sort(space[i], digit); //not sure how to work with digit here
}
return ... //not sure what to return here
}
private static int[] putInBucket(int[] bucket, int number) {
int[] bucket_new = new int[bucket.length+1];
for (int i = 1; i < bucket_new.length; i++) {
bucket_new[i] = bucket[i-1];
}
return bucket_new;
}
public static void main (String [] argv) {
int[] numbers = IO.readInts("Numbers: ");
int digit = 10000;
int[] bucket = sort(numbers, digit);
}

To extract the last digit, the remainder operator % is your friend:
123 % 10 == 3
if you haven't covered the % operator yet, you can use
123 % 10 == 123 - (123 / 10 * 10) == 3
To extract another digit, you can first move it to the end with /:
123 / 10 == 12
12 % 10 == 2
You can therefore extract an arbitrary digit using
(number / mask) % 10
where mask ∈ {..., 10000, 1000, 100, 10, 1}.
Extra credit
Radix sort is usually implemented in the binary number system instead because a binary digit (or a sequence thereof) can be extracted without performing a division, which is more efficient:
x % 16 == x & 15;
x \ 16 == x >> 4;
Also, if you are implementing this for real, you'd need a more efficient way to grow buckets (your implementation takes O(n) to add a single element to the bucket, adding n elements to the bucket therefore takes O(n^2), which makes your radix sort slower than insertion sort). Dynamic arrays are usually implemented with a more efficient geometric expansion.

This should work:
public static int[] sort(int[] numbers, int digit) {
if (numbers.length == 0 || digit <= 0)
return numbers;
int[][]space = new int[10][10];
int[] len = new int[10];
int i, j = 0;
for (j = 0; j < numbers.length; j++) {
i = (numbers[j] / digit) % 10;
len[i]++;
for (int k = len[i] - 1; k > 0; k--) {
space[i][k] = space[i][k - 1];
}
space[i][0] = numbers[j];
}
for (i = 0; i < 10; i++) {
int[] bucket = new int[len[i]];
for (int k = 0; k < len[i]; k++)
bucket[k] = space[i][k];
space[i] = sort(bucket, digit / 10);
}
int k = 0;
for (i = 0; i < 10; i++) {
for (j = 0; j < len[i]; j++) {
numbers[k] = space[i][j];
k++;
}
}
return numbers;
}
a) Firstly, space is allocated as having only one column. So, space[i] = bucket will not work.
Instead, you could declare it as int[10][10]. (Note: it will only support max of 10 values in one bucket). Or you may allocate new arrays programmatically. Or of course, a List might be better suited.
b) i = (numbers[j] / digit) % 10;
To get the required digit only. For eg: if the number is 12130, and digit = 1000, we want to set i to 2, not 12.
c) putInBucket replaced with an in-place loop.
d) For each bucket of space, we sort it by one digit lower by calling sort recursively.
e) Finally, the result to be returned (numbers), can be created by looping through space from digit 0 to 9.
Note:
This solution could probably be made better.

Create all possible binary permutations with a given number of ones in Java

I want to find all possible binary permutations with a given number of ones in Java:
x is the desired number of ones in each sequence
n is the desired length of each sequence
For an example:
x=2, n=4
Output: 1100, 0011, 1010, 1001, 0101, 0110
I'm searching for an elegant and fast way to do this. Can you help me?
I've tested eboix solution in Print list of binary permutations but it is unfortunately too slow because the algorithm in this example is searching for all 2^n binary permutations.
I want to find sequences with a length of 50 or 100.

First of all, you're missing 0110 as an output case.
It's fairly intuitive that there are n choose x possibilities. You're finding all valid arrangements of x identical items among n total slots. So you can find the total number of sequences in O(1).
As a hint, try simply finding all permutations of the bitstring consisting of x ones followed n - x zeros.
To specifically address the problem, try creating a recursive algorithm that decides at every ith iteration to either include 1 or 0. If 1 is included, you need to decrement the count of 1's available for the rest of the string.

Actually, there may be an elegant way, but no fast way to do this. The number of string permutations is given by the binomial coefficient (see https://en.wikipedia.org/wiki/Binomial_coefficient). For example, x=10, n= 50 gives over 10 million different strings.

Here is just a basic version that will generate your desired output. Please work on it to make it more accurate/efficient -
This will not generate all the combinations, but you will get the idea of how to do it. Off course, for all the possible combinations generated by this, you will have to generate all the other possible combinations.
public class Test {
static int iter = 0;
public static void main(String args[]){
int n = 50;
int x = 5;
byte[] perms = new byte[n];
for(int i=0; i<x; i++){
perms[i] = 1;
}
print(perms);
for(int j=x-1; j>=0; j--){
for(int i=1; i<(n/2-j); i++){
iter++;
swap(perms, j, i);
}
}
}
public static void swap(byte[] perms, int pos, int by){
byte val = perms[pos+by];
perms[pos+by] = perms[pos];
perms[pos] = val;
print(perms);
val = perms[pos+by];
perms[pos+by] = perms[pos];
perms[pos] = val;
}
public static void print(byte[] perms){
System.out.println("iter = "+iter);
for(int i=0; i<perms.length; i++){
System.out.print(perms[i]);
}
System.out.println();
for(int i=perms.length-1; i>=0; i--){
System.out.print(perms[i]);
}
System.out.println();
}
}

Another inspiration for you. A dirty version which works. It allocates extra array space (you should adjust size) and uses String Set at the end to remove duplicates.
public static void main(String[] args) {
int x = 2;
int n = 4;
Set<BigInteger> result = new LinkedHashSet<>();
for (int j = x; j > 0; j--) {
Set<BigInteger> a = new LinkedHashSet<>();
for (int i = 0; i < n - j + 1; i++) {
if (j == x) {
a.add(BigInteger.ZERO.flipBit(i));
} else {
for (BigInteger num : result) {
if (num != null && !num.testBit(i) && (i >= (n - j) || num.getLowestSetBit() >= i-1))
a.add(num.setBit(i));
}
}
}
result = a;
}
String zeros = new String(new char[n]).replace("\0", "0");
for (BigInteger i : result) {
String binary = i.toString(2);
System.out.println(zeros.substring(0, n - binary.length()) + binary);
}
}
EDIT: changed the primitives version to use BigInteger instead to support larger n,x values.