We Keep Coding

randomized select not give steady solution

EDIT
try run in the main:
int[] arr = {646 ,94 ,366 ,754 ,948 ,678 ,121 ,320 ,528 ,36};
for(int i=0;i<10;i++){
System.out.println(randomizedSelect(arr,0,arr.length-1,5));
printArr(arr);
}
and see that i got diffrent outpot in each loop..
Got a little problem that I would like some help with, if anyone knows how.
I need to find the kth smallest value in an array by randomized partition.
I've got two problems:
I get array out of bounds with -1 and can't find a way to fix it.
Most of the time it works but sometimes it gives me wrong k place.
For example for array with length of 10, it tells me that 20 is in the 5th place but actually it should be in the 2nd place and it prints the array where not all the values on the left are smaller than 20 and not smaller than the 5th place.
Here is an example array:
{646 ,94 ,366 ,754 ,948 ,678 ,121 ,320 ,528 ,36}
The array input is done by a random number generator.
This is my code:
import java.util.Random;
import java.util.Scanner;
public class Main {
static Scanner scan = new Scanner(System.in);
static Random rand = new Random();
public static void main(String[] args) {
int nSize = askSizeN();
int kSize = askSizeK(nSize);
int[] arr = new int[nSize];
chose(arr);
int[] arrCopy = new int[nSize];
for (int i = 0; i < arrCopy.length; i++) {
arrCopy[i] = arr[i];
}
printArr(arrCopy);
System.out.println(randomizedSelect(arrCopy, 0, arr.length - 1, kSize));
printArr(arrCopy);
}
private static int partition(int[] arr, int p, int r) {
int x = arr[r];
int i = p - 1;
for (int j = p; j < r; j++) {
if (arr[j] <= x) {
i++;
int temp = arr[i];
arr[i] = arr[j];
arr[j] = temp;
}
}
int temp = arr[i + 1];
arr[i + 1] = arr[r];
arr[r] = temp;
return i + 1;
}
private static int randomizedPartition(int[] arr, int p, int r) {
int i = rand.nextInt(r - p);
int temp = arr[r];
arr[r] = arr[i];
arr[i] = temp;
return partition(arr, p, r);
}
private static int randomizedSelect(int[] arr, int p, int r, int i) {
if (p == r) {
return arr[p];
}
int q = randomizedPartition(arr, p, r);
int k = q - p + 1;
if (i == k) {
return arr[q];
}
else if (i < k) {
return randomizedSelect(arr, p, q - 1, i);
}
else {
return randomizedSelect(arr, q + 1, r, i - k);
}
}
private static int askSizeN() {
System.out.println("Please chose the size of the heap: \n" + "(the size of n)");
return scan.nextInt();
}
private static int askSizeK(int nSize) {
System.out.println(
"Please chose how much small values you want to see: \n" + "(the size of k)");
int kSize = scan.nextInt();
if (kSize > nSize) {
System.out.println("cant print more number then the size of the Heap..");
System.out.println("Please enter a number less then " + (nSize + 1));
askSizeK(nSize);
}
return kSize;
}
private static int[] chose(int[] a) {
System.out.println("Chose the option you want: \n" + "\t1. enter your own values."
+ "\n\t2. let me generate random values");
int chose = scan.nextInt();
if (chose == 1) {
for (int i = 0; i < a.length; i++) {
System.out.println("Enter value number " + (i + 1));
a[i] = scan.nextInt();
}
}
else if (chose == 2) {
System.out.println("Generate random numbers.");
for (int i = 0; i < a.length; i++) {
a[i] = rand.nextInt(1000);
}
}
else {
chose(a);
}
return a;
}
private static void printArr(int[] a){
for(int i=0;i<a.length;i++){
System.out.print(a[i] + " ");
}
System.out.println();
}
}

I've solved the problem.
Method randmizedPartition() was generating wrong random pivot for partition.
I solved it by changing the random line to:
int i = rand.nextInt((r - p) + 1) + p;

Java finding the smallest integer in a speciofic position in a sets of integer

Algorithm:
Procedure SELECT( k,S)
{ if ISI =1 then return the single element in S
else { choose an element a randomly from S;
let S1,S2,and S3 be he sequences of elements in S
less than, equal to, and greater than m, respectively;
if IS1I >=k then return SELECT(k,S1)
else
if (IS1I + IS2I >=k then return m
else return SELECT(k-IS1I-IS2I , S3);
}
}
The question is to implement the first algorithm for finding the kth smallest integer in a set of integers and test your program for different sets of integers generated by a random number generator.
Below is my solution.
import java.util.Random;
import java.util.Scanner;
public class main {
private static Random rand = new Random();
private static Scanner keyboard = new Scanner(System.in);
public static int firstAlgorithm(int k, int[] S) {
int m = S[rand.nextInt(S.length)];
int[] S1 = new int[S.length];
int[] S2 = new int[S.length];
int[] S3 = new int[S.length];
int p = 0;
int q = 0;
int r = 0;
if (S.length == 1)
return S[0];
for (int i = 0; i < S.length; i++) {
if (S[i] < m) {
S1[p] = S[i];
p++;
} else if (S[i] == m) {
S2[q] = S[i];
q++;
} else {
S3[r] = S[i];
r++;
}
}
S1 = trimToSize(S1, p);
S2 = trimToSize(S2, q);
S3 = trimToSize(S3, r);
if (S1.length >= k)
return firstAlgorithm(k, S1);
else if (S1.length + S2.length >= k)
return m;
else
return firstAlgorithm(k - S1.length - S2.length, S3);
}
private static int[] trimToSize(int[] arr, int size) {
int[] temp = new int[size];
for (int i = 0; i < size; i++) {
temp[i] = arr[i];
}
return temp;
}
public static void printArray(int[] S) {
for (int i = 0; i < S.length; i++) {
System.out.print(S[i] + "\t");
if (i % 10 == 9)
System.out.println();
}
}
// start main method
public static void main(String[] args) {
System.out.print("Enter the size of an array: ");
int size = keyboard.nextInt();
while (size < 1) {
System.out.println("Size of the array should be greater than 0.");
System.out.print("Enter the size of an array: ");
size = keyboard.nextInt();
}
System.out.print("Enter the value of k: ");
int k = keyboard.nextInt();
while (k < 1 || k > size) {
System.out.println("Value of k should be in the range 1-" + size + ".");
System.out.print("Enter the value of k: ");
k = keyboard.nextInt();
}
int[] S = new int[size];
for (int i = 0; i < size; i++) {
S[i] = 100 + rand.nextInt(900);
}
System.out.println("\nRandom values generated in the array:");
printArray(S);
System.out.println();
System.out.println(k + "th smallest value in the array using Algorithm #1: " + firstAlgorithm(k, S));
}
}
But I need to implement the above algorithm without using a temporary array for partitioning. How can I do it?

The algorithm is Dijkstra's 3-way partition.
You will have to modify the original S.
Untested (pseudo) code ahead
public static int partition(int left, int right, int[] S) {
int m = rand.nextInt(right-left); // protect against malicious data
swap(S[left+m], S[right]);
int equal = left;
while (left < right) {
if (a[left] < a[n])
swap(S, left++, equal++)
else if (a[left] == a[n])
swap(S, left, --right);
else
left++;
}
return left, equal;
}
public static int firstAlgorithm(int k, int left, int right, int[] S) {
if (left == right)
return S[left];
int p, e = partition(left, right, S); // returns 2 values. S1=[0,p), S2=[p,e), S3=[e, n)
if (p >= k)
return firstAlgorithm(k, left, p, S);
else if (e >= k) // p < k
return S[p]; // p is the first equal, e is first larger than equal
else // e < k
return firstAlgorithm(k, e, right, S);
}
// test
S = {1, 4, 2, 6, 2};
k = 2;
int result = firstAlgorithm(2, 0, S.length-1, S);
assert(result == 2);
Warning syntax and off-by-one errors guarantied.
See here multiple ways to return 2 values in java.

Is there a test case scenario in which my program will fail?

Problem : You have L, a list containing some digits (0 to 9). Write a function solution(L) which finds the largest number that can be made from some or all of these digits and is divisible by 3. If it is not possible to make such a number, return 0 as the solution. L will contain anywhere from 1 to 9 digits. The same digit may appear multiple times in the list, but each element in the list may only be used once.
Test Cases :
Input:
Solution.solution({3, 1, 4, 1})
Output: 4311
Input:
Solution.solution({3, 1, 4, 1, 5, 9})
Output: 94311
My Program :
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Comparator;
import java.util.stream.IntStream;
public class Solution {
static ArrayList<Integer> al = new ArrayList<Integer>();
static ArrayList<Integer> largest = new ArrayList<Integer>();
static int o = 1;
static int po = 0;
static void combinations(String[] digits, String[] data, int start, int end, int index, int r)
{
if (index == r)
{
String temp = "0";
for (int j = 0; j < r; j++)
{
temp = temp + data[j];
// System.out.print(data[j]);
}
Integer d = Integer.parseInt(temp);
al.add(d);
// System.out.println(al);
}
for (int i = start; i <= end && ((end - i + 1) >= (r - index)); i++)
{
data[index] = digits[i];
combinations(digits, data, i + 1, end, index + 1, r);
}
}
static void printCombinations(String[] sequence, int N)
{
String[] data = new String[N];
for (int r = 0; r < sequence.length; r++)
combinations(sequence, data, 0, N - 1, 0, r);
}
static String[] convert(int[] x)
{
String c[] = new String[x.length];
for(int i=0; i < x.length; i++)
{
Integer k = x[i];
if(k==0)
{
o = o * 10;
continue;
}
c[i] = k.toString();
}
// System.out.println(o);
c = Arrays.stream(c).filter(s -> (s != null && s.length() > 0)).toArray(String[]::new);
po = c.length;
// System.out.println("Come"+ Arrays.asList(c));
return c;
}
public static int solution(int[] l) {
if(l.length==0)
return 0;
if(IntStream.of(l).sum()%3==0)
{
String x = "";
Arrays.sort(l);
for (int i = l.length - 1; i >= 0; i--) {
x = x + l[i];
}
return Integer.parseInt(x);
}
printCombinations(convert(l),po);
al.sort(Comparator.reverseOrder());
al.remove(al.size()-1);
al.removeIf( num -> num%3!=0);
if(al.isEmpty())
return 0;
for(int i=0; i< al.size(); i++)
{
Integer n = al.get(i);
printMaxNum(n);
}
// System.out.println(al);
// System.out.println(largest);
return largest.get(0)*o;
}
static void printMaxNum(int num)
{
// hashed array to store count of digits
int count[] = new int[10];
// Converting given number to string
String str = Integer.toString(num);
// Updating the count array
for(int i=0; i < str.length(); i++)
count[str.charAt(i)-'0']++;
// result is to store the final number
int result = 0, multiplier = 1;
// Traversing the count array
// to calculate the maximum number
for (int i = 0; i <= 9; i++)
{
while (count[i] > 0)
{
result = result + (i * multiplier);
count[i]--;
multiplier = multiplier * 10;
}
}
// return the result
largest.add(result);
}
public static void main(String[] args) {
System.out.println(solution(new int[]{9,8,2,3}));
}
}
My Code passes both given test cases and 3 other hidden test cases except one. I tried all possible input combinations but couldn't get to the exact failure. The return type by default is given as int and therefore they would not pass values which give output that does not fit in int. Any other scenario where my code fails?

Finding closest number to 0

I have an array of integers, and I need to find the one that's closest to zero (positive integers take priority over negative ones.)
Here is the code I have so far:
public class CloseToZero {
public static void main(String[] args) {
int[] data = {2,3,-2};
int curr = 0;
int near = data[0];
// find the element nearest to zero
for ( int i=0; i < data.length; i++ ){
curr = data[i] * data[i];
if ( curr <= (near * near) ) {
near = data[i];
}
}
System.out.println( near );
}
}
Currently I'm getting a result of -2 but I should be getting 2. What am I doing wrong?

This will do it in O(n) time:
int[] arr = {1,4,5,6,7,-1};
int closestIndex = 0;
int diff = Integer.MAX_VALUE;
for (int i = 0; i < arr.length; ++i) {
int abs = Math.abs(arr[i]);
if (abs < diff) {
closestIndex = i;
diff = abs;
} else if (abs == diff && arr[i] > 0 && arr[closestIndex] < 0) {
//same distance to zero but positive
closestIndex =i;
}
}
System.out.println(arr[closestIndex ]);

If you are using java8:
import static java.lang.Math.abs;
import static java.lang.Math.max;
public class CloseToZero {
public static void main(String[] args) {
int[] str = {2,3,-2};
Arrays.stream(str).filter(i -> i != 0)
.reduce((a, b) -> abs(a) < abs(b) ? a : (abs(a) == abs(b) ? max(a, b) : b))
.ifPresent(System.out::println);
}
}

Sort the array (add one line of code) so the last number you pick up will be positive if the same absolute value is selected for a positive and negative numbers with the same distance.
Source code:
import java.util.Arrays;
public class CloseToZero {
public static void main(String[] args) {
int[] data = {2,3,-2};
int curr = 0;
int near = data[0];
Arrays.sort(data); // add this
System.out.println(Arrays.toString(data));
// find the element nearest to zero
for ( int i=0; i < data.length; i++ ){
System.out.println("dist from " + data[i] + " = " + Math.abs(0 -data[i]));
curr = data[i] * data[i];
if ( curr <= (near * near) ) {
near = data[i];
}
}
System.out.println( near );
}
}

Just add zero to this list.
Then sort the list
Arrays.sort(data);
then grab the number before or after the zero and pick the minimum one greater than zero

Assumption is that the array data has at least 1 value.
int closestToZero = 0;
for ( int i = 1; i < data.length; i++ )
{
if ( Math.abs(data[i]) < Math.abs(data[closestToZero]) ) closestToZero = i;
}
The value in closestToZero is the index of the value closest to zero, not the value itself.

static int Solve(int N, int[] A){
int min = A[0];
for (int i=1; i<N ; i++){
min = min > Math.abs(0- A[i]) ? Math.abs(0- A[i]) : Math.abs(min);
}
return min;
}

As you multiply data[i] with data[i], a value negative and a value positive will have the same impact.
For example, in your example: 2 and -2 will be 4. So, your code is not able to sort as you need.
So, here, it takes -2 as the near value since it has the same "weight" as 2.

I have same answer with different method,Using Collections and abs , we can solved.
static int Solve(int N, int[] A){
List<Integer> mInt=new ArrayList<>();
for ( int i=0; i < A.length; i++ ){
mInt.add(Math.abs(0 -A[i]));
}
return Collections.min(mInt);
}
That all,As simple as that

This is a very easy to read O(n) solution for this problem.
int bigestNegative = Integer.MIN_VALUE;
int smalestpositive = Integer.MAX_VALUE;
int result = 0;
for (int i = 0; i < n; i++) {
//if the zero should be considered as result as well
if ( temperatures[i] == 0 ) {
result = 0;
break;
}
if ( temperatures[i] > 0 && temperatures[i] < smalestpositive ) {
smalestpositive = temperatures[i];
}
if ( temperatures[i] < 0 && temperatures[i] > bigestNegative ) {
bigestNegative = temperatures[i];
}
}
if( (Math.abs(bigestNegative)) < (Math.abs(smalestpositive)) && bigestNegative != Integer.MIN_VALUE)
result = bigestNegative;
else
result = smalestpositive;
System.out.println( result );

First convert the int array into stream. Then sort it with default sorting order. Then filter greater than zero & peek the first element & print it.
Do it in declarative style which describes 'what to do', not 'how to do'. This style is more readable.
int[] data = {2,3,-2};
IntStream.of(data)
.filter(i -> i>0)
.sorted()
.limit(1)
.forEach(System.out::println);

using Set Collection and abs methode to avoid complex algo
public static void main(String[] args) {
int [] temperature={0};
***// will erase double values and order them from small to big***
Set<Integer> s= new HashSet<Integer>();
if (temperature.length!=0) {
for(int i=0; i<temperature.length; i++) {
***// push the abs value to the set***
s.add(Math.abs(temperature[i]));
}
// remove a zero if exists in the set
while(s.contains(0)) {
s.remove(0);
}
***// get first (smallest) element of the set : by default it is sorted***
if (s.size()!=0) {
Iterator iter = s.iterator();
System.out.println(iter.next());
}
else System.out.println(0);
}
else System.out.println(0);
}

static int nearToZero(int[] A){
Arrays.sort(A);
int ans = 0;
List<Integer> list = Arrays.stream(A).boxed().collect(Collectors.toList());
List<Integer> toRemove = new ArrayList<>();
List<Integer> newList = new ArrayList<>();
for(int num: list){
if(newList.contains(num)) toRemove.add(num);
else newList.add(num);
}
list.removeAll(toRemove);
for(int num : list){
if(num == 0 ) return 0;
if(ans == 0 )ans = num;
if(num < 0 && ans < num) ans = num;
if(num < ans) ans = num;
if(num > 0 && Math.abs(ans) >= num) ans = num;
}
return ans;
}

here is a method that gives you the nearest to zero.
use case 1 : {1,3,-2} ==> return 1 : use the Math.abs() for comparison and get the least.
use case 2 : {2,3,-2} ==> return 2 : use the Math.abs() for comparison and get the Math.abs(least)
use case 3 : {-2,3,-2} ==> return -2: use the Math.abs() for comparison and get the least.
public static double getClosestToZero(double[] liste) {
// if the list is empty return 0
if (liste.length != 0) {
double near = liste[0];
for (int i = 0; i < liste.length; i++) {
// here we are using Math.abs to manage the negative and
// positive number
if (Math.abs(liste[i]) <= Math.abs(near)) {
// manage the case when we have two equal neagative numbers
if (liste[i] == -near) {
near = Math.abs(liste[i]);
} else {
near = liste[i];
}
}
}
return near;
} else {
return 0;
}
}

You can do like this:
String res = "";
Arrays.sort(arr);
int num = arr[0];
int ClosestValue = 0;
for (int i = 0; i < arr.length; i++)
{
//for negatives
if (arr[i] < ClosestValue && arr[i] > num)
num = arr[i];
//for positives
if (arr[i] > ClosestValue && num < ClosestValue)
num = arr[i];
}
res = num;
System.out.println(res);
First of all you need to store all your numbers into an array. After that sort the array --> that's the trick who will make you don't use Math.abs(). Now is time to make a loop that iterates through the array. Knowing that array is sorted is important that you start to make first an IF statement for negatives numbers then for the positives (in this way if you will have two values closest to zero, let suppose -1 and 1 --> will print the positive one).
Hope this will help you.

The easiest way to deal with this is split the array into positive and negative sort and push the first two items from both the arrays into another array. Have fun!
function closeToZeroTwo(arr){
let arrNeg = arr.filter(x => x < 0).sort();
let arrPos = arr.filter(x => x > 0).sort();
let retArr = [];
retArr.push(arrNeg[0], arrPos[0]);
console.log(retArr)
}

Easiest way to just sort that array in ascending order suppose input is like :
int[] array = {10,-5,5,2,7,-4,28,65,95,85,12,45};
then after sorting it will gives output like:
{-5,-4,2,5,7,10,12,28,45,65,85,95,}
and for positive integer number, the Closest Positive number is: 2
Logic :
public class Closest {
public static int getClosestToZero(int[] a) {
int temp=0;
//following for is used for sorting an array in ascending nubmer
for (int i = 0; i < a.length-1; i++) {
for (int j = 0; j < a.length-i-1; j++) {
if (a[j]>a[j+1]) {
temp = a[j];
a[j]=a[j+1];
a[j+1]=temp;
}
}
}
//to check sorted array with negative & positive values
System.out.print("{");
for(int number:a)
System.out.print(number + ",");
System.out.print("}\n");
//logic for check closest positive and Integer
for (int i = 0; i < a.length; i++) {
if (a[i]<0 && a[i+1]>0) {
temp = a[i+1];
}
}
return temp;
}
public static void main(String[] args) {
int[] array = {10,-5,5,2,7,-4,28,65,95,85,12,45};
int closets =getClosestToZero(array);
System.out.println("The Closest Positive number is : "+closets);
}
}

static void closestToZero(){
int[] arr = {45,-4,-12,-2,7,4};
int max = Integer.MAX_VALUE;
int closest = 0;
for (int i = 0; i < arr.length; i++){
int value = arr[i];
int abs = Math.abs(value);
if (abs < max){
max = abs;
closest = value;
}else if (abs == max){
if (value > closest){
closest = value;
}
}
}
Return a positive integer if two absolute values are the same.

package solution;
import java.util.Scanner;
public class Solution {
public static void trier(int tab[]) {
int tmp = 0;
for(int i = 0; i < (tab.length - 1); i++) {
for(int j = (i+1); j< tab.length; j++) {
if(tab[i] > tab[j]) {
tmp = tab[i];
tab[i] = tab[j];
tab[j] = tmp;
}
}
}
int prochePositif = TableauPositif(tab);
int procheNegatif = TableauNegatif(tab);
System.out.println(distanceDeZero(procheNegatif,prochePositif));
}
public static int TableauNegatif(int tab[]) {
int taille = TailleNegatif(tab);
int tabNegatif[] = new int[taille];
for(int i = 0; i< tabNegatif.length; i++) {
tabNegatif[i] = tab[i];
}
int max = tabNegatif[0];
for(int i = 0; i <tabNegatif.length; i++) {
if(max < tabNegatif[i])
max = tabNegatif[i];
}
return max;
}
public static int TableauPositif(int tab[]) {
int taille = TailleNegatif(tab);
if(tab[taille] ==0)
taille+=1;
int taillepositif = TaillePositif(tab);
int tabPositif[] = new int[taillepositif];
for(int i = 0; i < tabPositif.length; i++) {
tabPositif[i] = tab[i + taille];
}
int min = tabPositif[0];
for(int i = 0; i< tabPositif.length; i++) {
if(min > tabPositif[i])
min = tabPositif[i];
}
return min;
}
public static int TailleNegatif(int tab[]) {
int cpt = 0;
for(int i = 0; i < tab.length; i++) {
if(tab[i] < 0) {
cpt +=1;
}
}
return cpt;
}
public static int TaillePositif(int tab[]) {
int cpt = 0;
for(int i = 0; i < tab.length; i++) {
if(tab[i] > 0) {
cpt +=1;
}
}
return cpt;
}
public static int distanceDeZero(int v1, int v2) {
int absv1 = v1 * (-1);
if(absv1 < v2)
return v1;
else if(absv1 > v2)
return v2;
else
return v2;
}
public static void main(String[] args) {
int t[] = {6,5,8,8,-2,-5,0,-3,-5,9,7,4};
Solution.trier(t);
}
}

To maintain O(n) time complexity and getting the desired results we have to add another variable called 'num' and assign to it 'near' before changing it's value. And finally make necessary checks. The improvements in the code are are:
public class CloseToZero {
public static void main(String[] args) {
int[] data = {2,3,-2};
int curr = 0;
int near = data[0];
int num=near;
// find the element nearest to zero
for ( int i=0; i < data.length; i++ ){
curr = data[i] * data[i];
if ( curr <= (near * near) ) {
num=near;
near = data[i];
}
}
if(near<0 && near*(-1)==num)
near=num;
System.out.println( near );
}
}

We have to find the Closest number to zero.
The given array can have negative values also.
So the easiest approach would append the '0' in the given array and sort it and return the element next to '0'
append the 0
Sort the Array
Return the element next to 0.
`
N = int(input())
arr = list(map(int, input().split()))
arr.append(0)
arr.sort()
zeroIndex = arr.index(0)
print(arr[zeroIndex + 1])
--> If this solution leaves corner cases please let me know also.
`

if you don't wanna use the inbuilt library function use the below code (just an and condition with your existing code)-
public class CloseToZero {
public static void main(String[] args) {
int[] data = {2,3,-2,-1,1};
int curr = 0;
int near = data[0];
// find the element nearest to zero
for ( int i=0; i < data.length; i++ ){
curr = data[i] * data[i];
if ( curr <= (near * near) && !((curr - (near * near) == 0) && data[i] < 0)) {
near = data[i];
}
}
System.out.println( near );
}
}
!((curr - (near * near) == 0) && data[i] < 0) : skip asignment if if near and curr is just opposit in sign and the curr is negative

public static int find(int[] ints) {
if (ints==null) return 0;
int min= ints[0]; //a random value initialisation
for (int k=0;k<ints.length;k++) {
// if a positive value is matched it is prioritized
if (ints[k]==Math.abs(min) || Math.abs(ints[k])<Math.abs(min))
min=ints[k];
}
return min;
}

public int check() {
int target = 0;
int[] myArray = { 40, 20, 100, 30, -1, 70, -10, 500 };
int result = myArray[0];
for (int i = 0; i < myArray.length; i++) {
if (myArray[i] == target) {
result = myArray[i];
return result;
}
if (myArray[i] > 0 && result >= (myArray[i] - target)) {
result = myArray[i];
}
}
return result;
}
I have added a check for the positive number itself.
Please share your views folks!!

public class ClosesttoZero {
static int closZero(int[] ints) {
int result=ints[0];
for(int i=1;i<ints.length;i++) {
if(Math.abs(result)>=Math.abs(ints[i])) {
result=Math.abs(ints[i]);
}
}
return result;
}
public static void main(String[] args) {
// TODO Auto-generated method stub
int[] ints= {1,1,5,8,4,-9,0,6,7,1};
int result=ClosesttoZero.closZero(ints);
System.out.println(result);
}
}

It can be done simply by making all numbers positive using absolute value then sort the Array:
int[] arr = {9, 1, 4, 5, 6, 7, -1, -2};
for (int i = 0; i < arr.length; ++i)
{
arr[i] = Math.abs(arr[i]);
}
Arrays.sort(arr);
System.out.println("Closest value to 0 = " + arr[0]);

import java.math.*;
class Solution {
static double closestToZero(double[] ts) {
if (ts.length == 0)
return 0;
double closestToZero = ts[0];
double absClosest = Math.abs(closestToZero);
for (int i = 0; i < ts.length; i++) {
double absValue = Math.abs(ts[i]);
if (absValue < absClosest || absValue == absClosest && ts[i] > 0) {
closestToZero = ts[i];
absClosest = absValue;
}
}
return closestToZero;
}
}

//My solution priorizing positive numbers contraint
int closestToZero = Integer.MAX_VALUE;//or we
for(int i = 0 ; i < arrayInt.length; i++) {
if (Math.abs(arrayInt[i]) < closestToZero
|| Math.abs(closestToZero) == Math.abs(arrayInt[i]) && arrayInt[i] > 0 ) {
closestToZero = arrayInt[i];
}
}

java codility Max-Counters

I have been trying to solve the below task:
You are given N counters, initially set to 0, and you have two possible operations on them:
increase(X) − counter X is increased by 1,
max_counter − all counters are set to the maximum value of any counter.
A non-empty zero-indexed array A of M integers is given. This array represents consecutive operations:
if A[K] = X, such that 1 ≤ X ≤ N, then operation K is increase(X),
if A[K] = N + 1 then operation K is max_counter.
For example, given integer N = 5 and array A such that:
A[0] = 3
A[1] = 4
A[2] = 4
A[3] = 6
A[4] = 1
A[5] = 4
A[6] = 4
the values of the counters after each consecutive operation will be:
(0, 0, 1, 0, 0)
(0, 0, 1, 1, 0)
(0, 0, 1, 2, 0)
(2, 2, 2, 2, 2)
(3, 2, 2, 2, 2)
(3, 2, 2, 3, 2)
(3, 2, 2, 4, 2)
The goal is to calculate the value of every counter after all operations.
struct Results {
int * C;
int L;
};
Write a function:
struct Results solution(int N, int A[], int M);
that, given an integer N and a non-empty zero-indexed array A consisting of M integers, returns a sequence of integers representing the values of the counters.
The sequence should be returned as:
a structure Results (in C), or
a vector of integers (in C++), or
a record Results (in Pascal), or
an array of integers (in any other programming language).
For example, given:
A[0] = 3
A[1] = 4
A[2] = 4
A[3] = 6
A[4] = 1
A[5] = 4
A[6] = 4
the function should return [3, 2, 2, 4, 2], as explained above.
Assume that:
N and M are integers within the range [1..100,000];
each element of array A is an integer within the range [1..N + 1].
Complexity:
expected worst-case time complexity is O(N+M);
expected worst-case space complexity is O(N), beyond input storage (not counting the storage required for input arguments).
Elements of input arrays can be modified.
Here is my solution:
import java.util.Arrays;
class Solution {
public int[] solution(int N, int[] A) {
final int condition = N + 1;
int currentMax = 0;
int countersArray[] = new int[N];
for (int iii = 0; iii < A.length; iii++) {
int currentValue = A[iii];
if (currentValue == condition) {
Arrays.fill(countersArray, currentMax);
} else {
int position = currentValue - 1;
int localValue = countersArray[position] + 1;
countersArray[position] = localValue;
if (localValue > currentMax) {
currentMax = localValue;
}
}
}
return countersArray;
}
}
Here is the code valuation:
https://codility.com/demo/results/demo6AKE5C-EJQ/
Can you give me a hint what is wrong with this solution?

The problem comes with this piece of code:
for (int iii = 0; iii < A.length; iii++) {
...
if (currentValue == condition) {
Arrays.fill(countersArray, currentMax);
}
...
}
Imagine that every element of the array A was initialized with the value N+1. Since the function call Arrays.fill(countersArray, currentMax) has a time complexity of O(N) then overall your algorithm will have a time complexity O(M * N). A way to fix this, I think, instead of explicitly updating the whole array A when the max_counter operation is called you may keep the value of last update as a variable. When first operation (incrementation) is called you just see if the value you try to increment is larger than the last_update. If it is you just update the value with 1 otherwise you initialize it to last_update + 1. When the second operation is called you just update last_update to current_max. And finally, when you are finished and try to return the final values you again compare each value to last_update. If it is greater you just keep the value otherwise you return last_update
class Solution {
public int[] solution(int N, int[] A) {
final int condition = N + 1;
int currentMax = 0;
int lastUpdate = 0;
int countersArray[] = new int[N];
for (int iii = 0; iii < A.length; iii++) {
int currentValue = A[iii];
if (currentValue == condition) {
lastUpdate = currentMax
} else {
int position = currentValue - 1;
if (countersArray[position] < lastUpdate)
countersArray[position] = lastUpdate + 1;
else
countersArray[position]++;
if (countersArray[position] > currentMax) {
currentMax = countersArray[position];
}
}
}
for (int iii = 0; iii < N; iii++) {
if (countersArray[iii] < lastUpdate)
countersArray[iii] = lastUpdate;
}
return countersArray;
}
}

The problem is that when you get lots of max_counter operations you get lots of calls to Arrays.fill which makes your solution slow.
You should keep a currentMax and a currentMin:
When you get a max_counter you just set currentMin = currentMax.
If you get another value, let's call it i:
If the value at position i - 1 is smaller or equal to currentMin you set it to currentMin + 1.
Otherwise you increment it.
At the end just go through the counters array again and set everything less than currentMin to currentMin.

Another solution that I have developed and might be worth considering: http://codility.com/demo/results/demoM658NU-DYR/

This is the 100% solution of this question.
// you can also use imports, for example:
// import java.math.*;
class Solution {
public int[] solution(int N, int[] A) {
int counter[] = new int[N];
int n = A.length;
int max=-1,current_min=0;
for(int i=0;i<n;i++){
if(A[i]>=1 && A[i]<= N){
if(counter[A[i] - 1] < current_min) counter[A[i] - 1] = current_min;
counter[A[i] - 1] = counter[A[i] - 1] + 1;
if(counter[A[i] - 1] > max) max = counter[A[i] - 1];
}
else if(A[i] == N+1){
current_min = max;
}
}
for(int i=0;i<N;i++){
if(counter[i] < current_min) counter[i] = current_min;
}
return counter;
}
}

I'm adding another Java 100 solution with some test cases it they're helpful.
// https://codility.com/demo/results/demoD8J6M5-K3T/ 77
// https://codility.com/demo/results/demoSEJHZS-ZPR/ 100
public class MaxCounters {
// Some testcases
// (1,[1,2,3]) = [1]
// (1,[1]) = [1]
// (1,[5]) = [0]
// (1,[1,1,1,2,3]) = 3
// (2,[1,1,1,2,3,1]) = [4,3]
// (5, [3, 4, 4, 5, 1, 4, 4]) = (1, 0, 1, 4, 1)
public int[] solution(int N, int[] A) {
int length = A.length, maxOfCounter = 0, lastUpdate = 0;
int applyMax = N + 1;
int result[] = new int[N];
for (int i = 0; i < length; ++i ) {
if(A[i] == applyMax){
lastUpdate = maxOfCounter;
} else if (A[i] <= N) {
int position = A[i]-1;
result[position] = result[position] > lastUpdate
? result[position] + 1 : lastUpdate + 1;
// updating the max for future use
if(maxOfCounter <= result[position]) {
maxOfCounter = result[position];
}
}
}
// updating all the values that are less than the lastUpdate to the max value
for (int i = 0; i < N; ++i) {
if(result[i] < lastUpdate) {
result[i] = lastUpdate;
}
}
return result;
}
}

My java solution with a detailed explanation 100% Correctness, 100% Performance :
Time Complexity O(N+M)
public static int[] solution(int N, int[] A) {
int[] counters = new int[N];
//The Max value between all counters at a given time
int max = 0;
//The base Max that all counter should have after the "max counter" operation happens
int baseMax = 0;
for (int i = 0; i < A.length; i++) {
//max counter Operation ==> updating the baseMax
if (A[i] > N) {
// Set The Base Max that all counters should have
baseMax = max;
}
//Verify if the value is bigger than the last baseMax because at any time a "max counter" operation can happen and the counter should have the max value
if (A[i] <= N && counters[A[i] - 1] < baseMax) {
counters[A[i] - 1] = baseMax;
}
//increase(X) Operation => increase the counter value
if (A[i] <= N) {
counters[A[i] - 1] = counters[A[i] - 1] + 1;
//Update the max
max = Math.max(counters[A[i] - 1], max);
}
}
//Set The remaining values to the baseMax as not all counters are guaranteed to be affected by an increase(X) operation in "counters[A[i] - 1] = baseMax;"
for (int j = 0; j < N; j++) {
if (counters[j] < baseMax)
counters[j] = baseMax;
}
return counters;
}

Here is my C++ solution which got 100 on codility. The concept is same as explained above.
int maxx=0;
int lastvalue=0;
void set(vector<int>& A, int N,int X)
{
for ( int i=0;i<N;i++)
if(A[i]<lastvalue)
A[i]=lastvalue;
}
vector<int> solution(int N, vector<int> &A) {
// write your code in C++11
vector<int> B(N,0);
for(unsigned int i=0;i<A.size();i++)
{
if(A[i]==N+1)
lastvalue=maxx;
else
{ if(B[A[i]-1]<lastvalue)
B[A[i]-1]=lastvalue+1;
else
B[A[i]-1]++;
if(B[A[i]-1]>maxx)
maxx=B[A[i]-1];
}
}
set(B,N,maxx);
return B;
}

vector<int> solution(int N, vector<int> &A)
{
std::vector<int> counters(N);
auto max = 0;
auto current = 0;
for (auto& counter : A)
{
if (counter >= 1 && counter <= N)
{
if (counters[counter-1] < max)
counters[counter - 1] = max;
counters[counter - 1] += 1;
if (counters[counter - 1] > current)
current = counters[counter - 1];
}
else if (counter > N)
max = current;
}
for (auto&& counter : counters)
if (counter < max)
counter = max;
return counters;
}

Arrays.fill() invocation inside array interation makes the program O(N^2)
Here is a possible solution which has O(M+N) runtime.
The idea is -
For the second operation, keep track of max value that is achieved through increment, this is our base value till the current iteration, no values can't be less than this.
For the first operation, resetting the value to base value if needed before the increment.
public static int[] solution(int N, int[] A) {
int counters[] = new int[N];
int base = 0;
int cMax = 0;
for (int a : A) {
if (a > counters.length) {
base = cMax;
} else {
if (counters[a - 1] < base) {
counters[a - 1] = base;
}
counters[a - 1]++;
cMax = Math.max(cMax, counters[a - 1]);
}
}
for (int i = 0; i < counters.length; i++) {
if (counters[i] < base) {
counters[i] = base;
}
}
return counters;
}

vector<int> solution(int N, vector<int> &A)
{
std::vector<int> counter(N, 0);
int max = 0;
int floor = 0;
for(std::vector<int>::iterator i = A.begin();i != A.end(); i++)
{
int index = *i-1;
if(*i<=N && *i >= 1)
{
if(counter[index] < floor)
counter[index] = floor;
counter[index] += 1;
max = std::max(counter[index], max);
}
else
{
floor = std::max(max, floor);
}
}
for(std::vector<int>::iterator i = counter.begin();i != counter.end(); i++)
{
if(*i < floor)
*i = floor;
}
return counter;
}

Hera is my AC Java solution. The idea is the same as #Inwvr explained:
public int[] solution(int N, int[] A) {
int[] count = new int[N];
int max = 0;
int lastUpdate = 0;
for(int i = 0; i < A.length; i++){
if(A[i] <= N){
if(count[A[i]-1] < lastUpdate){
count[A[i]-1] = lastUpdate+1;
}
else{
count[A[i]-1]++;
}
max = Math.max(max, count[A[i]-1]);
}
else{
lastUpdate = max;
}
}
for(int i = 0; i < N; i++){
if(count[i] < lastUpdate)
count[i] = lastUpdate;
}
return count;
}

I just got 100 in PHP with some help from the above
function solution($N, $A) {
$B = array(0);
$max = 0;
foreach($A as $key => $a) {
$a -= 1;
if($a == $N) {
$max = max($B);
} else {
if(!isset($B[$a])) {
$B[$a] = 0;
}
if($B[$a] < $max) {
$B[$a] = $max + 1;
} else {
$B[$a] ++;
}
}
}
for($i=0; $i<$N; $i++) {
if(!isset($B[$i]) || $B[$i] < $max) {
$B[$i] = $max;
}
}
return $B;
}

This is another C++ solution to the problem.
The rationale is always the same.
Avoid to set to max counter all the counter upon instruction two, as this would bring the complexity to O(N*M).
Wait until we get another operation code on a single counter.
At this point the algorithm remembers whether it had met a max_counter and set the counter value consequently.
Here the code:
vector<int> MaxCounters(int N, vector<int> &A)
{
vector<int> n(N, 0);
int globalMax = 0;
int localMax = 0;
for( vector<int>::const_iterator it = A.begin(); it != A.end(); ++it)
{
if ( *it >= 1 && *it <= N)
{
// this is an increase op.
int value = *it - 1;
n[value] = std::max(n[value], localMax ) + 1;
globalMax = std::max(n[value], globalMax);
}
else
{
// set max counter op.
localMax = globalMax;
}
}
for( vector<int>::iterator it = n.begin(); it != n.end(); ++it)
*it = std::max( *it, localMax );
return n;
}

100%, O(m+n)
public int[] solution(int N, int[] A) {
int[] counters = new int[N];
int maxAIs = 0;
int minAShouldBe = 0;
for(int x : A) {
if(x >= 1 && x <= N) {
if(counters[x-1] < minAShouldBe) {
counters[x-1] = minAShouldBe;
}
counters[x-1]++;
if(counters[x-1] > maxAIs) {
maxAIs = counters[x-1];
}
} else if(x == N+1) {
minAShouldBe = maxAIs;
}
}
for(int i = 0; i < N; i++) {
if(counters[i] < minAShouldBe) {
counters[i] = minAShouldBe;
}
}
return counters;
}

here is my code, but its 88% cause it takes 3.80 sec for 10000 elements instead of 2.20
class Solution {
boolean maxCalled;
public int[] solution(int N, int[] A) {
int max =0;
int [] counters = new int [N];
int temp=0;
int currentVal = 0;
for(int i=0;i<A.length;i++){
currentVal = A[i];
if(currentVal <=N){
temp = increas(counters,currentVal);
if(temp > max){
max = temp;
}
}else{
if(!maxCalled)
maxCounter(counters,max);
}
}
return counters;
}
int increas (int [] A, int x){
maxCalled = false;
return ++A[x-1];
//return t;
}
void maxCounter (int [] A, int x){
maxCalled = true;
for (int i = 0; i < A.length; i++) {
A[i] = x;
}
}
}

Following my solution in JAVA (100/100).
public boolean isToSum(int value, int N) {
return value >= 1 && value <= N;
}
public int[] solution(int N, int[] A) {
int[] res = new int[N];
int max =0;
int minValue = 0;
for (int i=0; i < A.length; i++){
int value = A[i];
int pos = value -1;
if ( isToSum(value, N)) {
if( res[pos] < minValue) {
res[pos] = minValue;
}
res[pos] += 1;
if (max < res[pos]) {
max = res[pos];
}
} else {
minValue = max;
}
}
for (int i=0; i < res.length; i++){
if ( res[i] < minValue ){
res[i] = minValue;
}
}
return res;
}

my solution is :
public class Solution {
public int[] solution(int N, int[] A) {
int[] counters = new int[N];
int[] countersLastMaxIndexes = new int[N];
int maxValue = 0;
int fixedMaxValue = 0;
int maxIndex = 0;
for (int i = 0; i < A.length; i++) {
if (A[i] <= N) {
if (countersLastMaxIndexes[A[i] - 1] != maxIndex) {
counters[A[i] - 1] = fixedMaxValue;
countersLastMaxIndexes[A[i] - 1] = maxIndex;
}
counters[A[i] - 1]++;
if (counters[A[i] - 1] > maxValue) {
maxValue = counters[A[i] - 1];
}
} else {
maxIndex = i;
fixedMaxValue = maxValue;
}
}
for (int i = 0; i < countersLastMaxIndexes.length; i++) {
if (countersLastMaxIndexes[i] != maxIndex) {
counters[i] = fixedMaxValue;
countersLastMaxIndexes[i] = maxIndex;
}
}
return counters;
}
}

In my Java solution I updated values in solution[] only when needed. And finally updated solution[] with a right values.
public int[] solution(int N, int[] A) {
int[] solution = new int[N];
int maxCounter = 0;
int maxCountersSum = 0;
for(int a: A) {
if(a >= 1 && a <= N) {
if(solution[a - 1] < maxCountersSum)
solution[a - 1] = maxCountersSum;
solution[a - 1]++;
if(solution[a - 1] > maxCounter)
maxCounter = solution[a - 1];
}
if(a == N + 1) {
maxCountersSum = maxCounter;
}
}
for(int i = 0; i < N; i++) {
if(solution[i] < maxCountersSum)
solution[i] = maxCountersSum;
}
return solution;
}

Here's my python solution:
def solution(N, A):
# write your code in Python 3.6
RESP = [0] * N
MAX_OPERATION = N + 1
current_max = 0
current_min = 0
for operation in A:
if operation != MAX_OPERATION:
if RESP[operation-1] <= current_min:
RESP[operation-1] = current_min + 1
else:
RESP[operation-1] += 1
if RESP[operation-1] > current_max:
current_max = RESP[operation-1]
else:
if current_min == current_max:
current_min += 1
else:
current_min = current_max
for i, val in enumerate(RESP):
if val < current_min:
RESP[i] = current_min
return RESP

def sample_method(A,N=5):
initial_array = [0,0,0,0,0]
for i in A:
if(i>=1):
if(i<=N):
initial_array[i-1]+=1
else:
for a in range(len(initial_array)):
initial_array[a]+=1
print i
print initial_array

Here's my solution using python 3.6. The result is 100% correctness but 40% performance (most of them were because of timeout). Still cannot figure out how to optimize this code but hopefully someone can find it useful.
def solution(N, A):
count = [0]*(N+1)
for i in range(0,len(A)):
if A[i] >=1 and A[i] <= N:
count[A[i]] += 1
elif A[i] == (N+1):
count = [max(count)] * len(count)
count.pop(0)
return count

Typescript:
function counters(numCounters: number, operations: number[]) {
const counters = Array(numCounters)
let max = 0
let currentMin = 0
for (const operation of operations) {
if (operation === numCounters + 1) {
currentMin = max
} else {
if (!counters[operation - 1] || counters[operation - 1] < currentMin) {
counters[operation - 1] = currentMin
}
counters[operation - 1] = counters[operation - 1] + 1
if (counters[operation - 1] > max) {
max += 1
}
}
}
for (let i = 0; i < numCounters; i++) {
if (!counters[i] || counters[i] < currentMin) {
counters[i] = currentMin
}
}
return counters
}
console.log(solution=${counters(5, [3, 4, 4, 6, 1, 4, 4])})

100 points JavaScript solution, includes performance improvement to ignore repeated max_counter iterations:
function solution(N, A) {
let max = 0;
let counters = Array(N).fill(max);
let maxCounter = 0;
for (let op of A) {
if (op <= N && op >= 1) {
maxCounter = 0;
if (++counters[op - 1] > max) {
max = counters[op - 1];
}
} else if(op === N + 1 && maxCounter === 0) {
maxCounter = 1;
for (let i = 0; i < counters.length; i++) {
counters[i] = max;
}
}
}
return counters;
}

solution in JAVA (100/100)
class Solution {
public int[] solution(int N, int[] A) {
// write your code in Java SE 8
int[] result = new int[N];
int base = 0;
int max = 0;
int needToChange=A.length;;
for (int k = 0; k < A.length; k++) {
int X = A[k];
if (X >= 1 && X <= N) {
if (result[X - 1] < base) {
result[X - 1] = base;
}
result[X - 1]++;
if (max < result[X - 1]) {
max = result[X - 1];
}
}
if (X == N + 1) {
base = max;
needToChange= X-1;
}
}
for (int i = 0; i < needToChange; i++) {
if (result[i] < base) {
result[i] = base;
}
}
return result;
}
}

My Java solution. It gives 100% but is very long (in comparison). I have used HashMap for storing counters.
Detected time complexity: O(N + M)
import java.util.*;
class Solution {
final private Map<Integer, Integer> counters = new HashMap<>();
private int maxCounterValue = 0;
private int maxCounterValueRealized = 0;
public int[] solution(int N, int[] A) {
if (N < 1) return new int[0];
for (int a : A) {
if (a <= N) {
Integer current = counters.putIfAbsent(a, maxCounterValueRealized + 1);
if (current == null) {
updateMaxCounterValue(maxCounterValueRealized + 1);
} else {
++current;
counters.replace(a, current);
updateMaxCounterValue(current);
}
} else {
maxCounterValueRealized = maxCounterValue;
counters.clear();
}
}
return getCountersArray(N);
}
private void updateMaxCounterValue(int currentCounterValue) {
if (currentCounterValue > maxCounterValue)
maxCounterValue = currentCounterValue;
}
private int[] getCountersArray(int N) {
int[] countersArray = new int[N];
for (int j = 0; j < N; j++) {
Integer current = counters.get(j + 1);
if (current == null) {
countersArray[j] = maxCounterValueRealized;
} else {
countersArray[j] = current;
}
}
return countersArray;
}
}

Here is solution in python with 100 %
Codility Max counter 100%
def solution(N, A):
"""
Solution at 100% - https://app.codility.com/demo/results/trainingUQ95SB-4GA/
Idea is first take the counter array of given size N
take item from main A one by one + 1 and put in counter array , use item as index
keep track of last max operation
at the end replace counter items with max of local or counter item it self
:param N:
:param A:
:return:
"""
global_max = 0
local_max = 0
# counter array
counter = [0] * N
for i, item in enumerate(A):
# take item from original array one by one - 1 - minus due to using item as index
item_as_counter_index = item - 1
# print(item_as_counter_index)
# print(counter)
# print(local_max)
# current element less or equal value in array and greater than 1
# if A[K] = X, such that 1 ≤ X ≤ N, then operation K is increase(X),
if N >= item >= 1:
# max of local_max counter at item_as_counter_index
# increase counter array value and put in counter array
counter[item_as_counter_index] = max(local_max, counter[item_as_counter_index]) + 1
# track the status of global_max counter so far
# this is operation K
global_max = max(global_max, counter[item_as_counter_index])
# if A[K] = N + 1 then operation K is max counter.
elif item == N + 1:
# now operation k is as local max
# here we need to replace all items in array with this global max
# we can do using for loop for array length but that will cost bigo n2 complexity
# example - for i, item in A: counter[i] = global_max
local_max = global_max
# print("global_max each step")
# print(global_max)
# print("local max so far....")
# print(local_max)
# print("counter - ")
# print(counter)
# now counter array - replace all elements which are less than the local max found so far
# all counters are set to the maximum value of any counter
for i, item in enumerate(counter):
counter[i] = max(item, local_max)
return counter
result = solution(1, [3, 4, 4, 6, 1, 4, 4])
print("Sol " + str(result))

enter link description here
Got 100% result with O ( N + M )
class Solution {
public int[] solution(int N, int[] A) {
// write your code in Java SE 8
int max = 0;
int[] counter = new int[N];
int upgrade = 0;
for ( int i = 0; i < A.length; i++ )
{
if ( A[i] <= N )
{
if ( upgrade > 0 && upgrade > counter[A[i] - 1 ] )
{
counter[A[i] - 1] = upgrade;
}
counter[A[i] - 1 ]++;
if ( counter[A[i] - 1 ] > max )
{
max = counter[A[i] - 1 ];
}
}
else
{
upgrade = max;
}
}
for ( int i = 0; i < N; i++ )
{
if ( counter[i] < upgrade)
{
counter[i] = upgrade;
}
}
return counter;
}
}

Java 100%/100%, no imports
public int[] solution(int N, int[] A) {
int[] counters = new int[N];
int currentMax = 0;
int sumOfMaxCounters = 0;
boolean justDoneMaxCounter = false;
for (int i = 0; i < A.length ; i++) {
if (A[i] <= N) {
justDoneMaxCounter = false;
counters[A[i]-1]++;
currentMax = currentMax < counters[A[i]-1] ? counters[A[i]-1] : currentMax;
}else if (!justDoneMaxCounter){
sumOfMaxCounters += currentMax;
currentMax = 0;
counters = new int[N];
justDoneMaxCounter = true;
}
}
for (int j = 0; j < counters.length; j++) {
counters[j] = counters[j] + sumOfMaxCounters;
}
return counters;
}

python solution: 100% 100%
def solution(N, A):
c = [0] * N
max_element = 0
base = 0
for item in A:
if item >= 1 and N >= item:
c[item-1] = max(c[item-1], base) + 1
max_element = max(c[item - 1], max_element)
elif item == N + 1:
base = max_element
for i in range(N):
c[i] = max (c[i], base)
return c
pass

Using applyMax to record max operations
Time complexity:
O(N + M)
class Solution {
public int[] solution(int N, int[] A) {
// write your code in Java SE 8
int max = 0, applyMax = 0;;
int[] result = new int[N];
for (int i = 0; i < A.length; ++i) {
int a = A[i];
if (a == N + 1) {
applyMax = max;
}
if (1 <= a && a <= N) {
result[A[i] - 1] = Math.max(applyMax, result[A[i] - 1]);
max = Math.max(max, ++result[A[i] - 1]);
}
}
for (int i = 0; i < N; ++i) {
if (result[i] < applyMax) {
result[i] = applyMax;
}
}
return result;
}
}