Recently I've been assigned a task which asks to me to "calculate the maximum difference between two adjacent numbers in the array that is passed to it". I'm fairly new to Java (I have only done VB in the past) and since this topic was not well explained to me, I'm not quite sure how to go about it.
Here is some additional information about the task itself:
The function has to pass the following test. The function maxDiff should calculate the maximum difference between two adjacent numbers in the array that is passed to it.
#Test
public void assessmentTest() {
int [] numbers = {12, 8, 34, 10, 59};
assertEquals(49, maxDiff(numbers));
int [] numbers2 = {-50, 100, 20, -40};
assertEquals(150, maxDiff(numbers2));
}
You must assure to take the absolute difference, don't forget it. That's why I used the Math.abs() function.
public static int maxDiff(int[] numbers) {
int diff = Math.abs(numbers[1] - numbers[0]);
for(int i = 1; i < numbers.length-1; i++)
if(Math.abs(numbers[i+1]-numbers[i]) > diff)
diff = Math.abs(numbers[i+1] - numbers[i]);
return diff;
}
Something like this should do the trick:
public static int maxDiff(int[] numbers) {
if (numbers.length < 2) {
return 0;
}
if (numbers.length == 2) {
return Math.abs(numbers[1] - numbers[0]);
}
int max = Math.abs(numbers[1] - numbers[0]);
for (int i = 2; i < numbers.length; i++) {
int diff = Math.abs(numbers[i-1] - numbers[i]);
if (diff > max) {
max = diff;
}
}
return max;
}
For the specific question you asked:
public static int maxDiff(int[] arr) {
if(arr.length < 2)
return -1; // error condition: throw exception?
int maxdiff = Integer.MIN_VALUE;
for(int i = 1; i < arr.length; ++i) {
int diff = Math.abs(arr[i] - arr[i-1]);
if(diff > maxdiff)
maxdiff = diff;
}
return maxdiff;
}
If you want the max difference across all numbers in the array (not just adjacent ones) the most efficient way to do it would be to iterate the array just once to find the minimum and maximum, then return the absolute value of the two values subtracted from each other.
public static int maxDiff(int[] arr) {
if(arr.length < 2)
return -1; // error condition: throw exception?
int min = Integer.MAX_VALUE;
int max = Integer.MIN_VALUE;
for(int i = 0; i < arr.length; ++i) {
if(arr[i] < min)
min = arr[i];
if(arr[i] > max)
max = arr[i];
}
return Math.abs(max - min);
}
This piece of code can help you:
int[] numbers = {12, 8, 34, 10, 59};
int diff = 0;
int previous = 0;
for (int n : numbers) {
diff = Math.max(diff, Math.abs(n - previous));
previous = n;
}
Variable "diff" will contain the value you look for.
You can use this for Java;
int arrayMaximalAdjacentDifference(int[] inputArray) {
int max=0;
for( int i = 1 ; i < inputArray.length ; i++ ){
max = Math.max(max,Math.abs(inputArray[i] - inputArray[i-1]));
}
return max;
}
So the goal is to rotate the elements in an array right a times.
As an example; if a==2, then array = {0,1,2,3,4} would become array = {3,4,0,1,2}
Here's what I have:
for (int x = 0; x <= array.length-1; x++){
array[x+a] = array[x];
}
However, this fails to account for when [x+a] is greater than the length of the array. I read that I should store the ones that are greater in a different Array but seeing as a is variable I'm not sure that's the best solution.
Thanks in advance.
Add a modulo array length to your code:
// create a newArray before of the same size as array
// copy
for(int x = 0; x <= array.length-1; x++){
newArray[(x+a) % array.length ] = array[x];
}
You should also create a new Array to copy to, so you do not overwrite values, that you'll need later on.
In case you don't want to reinvent the wheel (maybe it's an exercise but it can be good to know), you can use Collections.rotate.
Be aware that it requires an array of objects, not primitive data type (otherwise you'll swap arrays themselves in the list).
Integer[] arr = {0,1,2,3,4};
Collections.rotate(Arrays.asList(arr), 2);
System.out.println(Arrays.toString(arr)); //[3, 4, 0, 1, 2]
Arraycopy is an expensive operation, both time and memory wise.
Following would be an efficient way to rotate array without using extra space (unlike the accepted answer where a new array is created of the same size).
public void rotate(int[] nums, int k) { // k = 2
k %= nums.length;
// {0,1,2,3,4}
reverse(nums, 0, nums.length - 1); // Reverse the whole Array
// {4,3,2,1,0}
reverse(nums, 0, k - 1); // Reverse first part (4,3 -> 3,4)
// {3,4,2,1,0}
reverse(nums, k, nums.length - 1); //Reverse second part (2,1,0 -> 0,1,2)
// {3,4,0,1,2}
}
public void reverse(int[] nums, int start, int end) {
while (start < end) {
int temp = nums[start];
nums[start] = nums[end];
nums[end] = temp;
start++;
end--;
}
}
Another way is copying with System.arraycopy.
int[] temp = new int[array.length];
System.arraycopy(array, 0, temp, a, array.length - a);
System.arraycopy(array, array.length-a, temp, 0, a);
I think the fastest way would be using System.arrayCopy() which is native method:
int[] tmp = new int[a];
System.arraycopy(array, array.length - a, tmp, 0, a);
System.arraycopy(array, 0, array, a, array.length - a);
System.arraycopy(tmp, 0, array, 0, a);
It also reuses existing array. It may be beneficial in some cases.
And the last benefit is the temporary array size is less than original array. So you can reduce memory usage when a is small.
Time Complexity = O(n)
Space Complexity = O(1)
The algorithm starts with the first element of the array (newValue) and places it at its position after the rotation (newIndex). The element that was at the newIndex becomes oldValue. After that, oldValue and newValue are swapped.
This procedure repeats length times.
The algorithm basically bounces around the array placing each element at its new position.
unsigned int computeIndex(unsigned int len, unsigned int oldIndex, unsigned int times) {
unsigned int rot = times % len;
unsigned int forward = len - rot;
// return (oldIndex + rot) % len; // rotating to the right
return (oldIndex + forward) % len; // rotating to the left
}
void fastArrayRotation(unsigned short *arr, unsigned int len, unsigned int rotation) {
unsigned int times = rotation % len, oldIndex, newIndex, length = len;
unsigned int setIndex = 0;
unsigned short newValue, oldValue, tmp;
if (times == 0) {
return;
}
while (length > 0) {
oldIndex = setIndex;
newValue = arr[oldIndex];
while (1) {
newIndex = computeIndex(len, oldIndex, times);
oldValue = arr[newIndex];
arr[newIndex] = newValue;
length--;
if (newIndex == setIndex) { // if the set has ended (loop detected)
break;
}
tmp = newValue;
newValue = oldValue;
oldValue = tmp;
oldIndex = newIndex;
}
setIndex++;
}
}
int[] rotate(int[] array, int r) {
final int[] out = new int[array.length];
for (int i = 0; i < array.length; i++) {
out[i] = (i < r - 1) ? array[(i + r) % array.length] : array[(i + r) % array.length];
}
return out;
}
The following rotate method will behave exactly the same as the rotate method from the Collections class used in combination with the subList method from the List interface, i.e. rotate (n, fromIndex, toIndex, dist) where n is an array of ints will give the same result as Collections.rotate (Arrays.asList (n).subList (fromIndex, toIndex), dist) where n is an array of Integers.
First create a swap method:
public static void swap (int[] n, int i, int j){
int tmp = n[i];
n[i] = n[j];
n[j] = tmp;
}
Then create the rotate method:
public static void rotate (int[] n, int fromIndex, int toIndex,
int dist){
if(fromIndex > toIndex)
throw new IllegalArgumentException ("fromIndex (" +
fromIndex + ") > toIndex (" + toIndex + ")");
if (fromIndex < toIndex){
int region = toIndex - fromIndex;
int index;
for (int i = 0; i < dist % region + ((dist < 0) ? region : 0);
i++){
index = toIndex - 1;
while (index > fromIndex)
swap (n, index, --index);
}
}
}
Java solution wrapped in a method:
public static int[] rotate(final int[] array, final int rIndex) {
if (array == null || array.length <= 1) {
return new int[0];
}
final int[] result = new int[array.length];
final int arrayLength = array.length;
for (int i = 0; i < arrayLength; i++) {
int nIndex = (i + rIndex) % arrayLength;
result[nIndex] = array[i];
}
return result;
}
For Left Rotate its very simple
Take the difference between length of the array and number of position to shift.
For Example
int k = 2;
int n = 5;
int diff = n - k;
int[] array = {1, 2, 3, 4, 5};
int[] result = new int[array.length];
System.arraycopy(array, 0, result, diff, k);
System.arraycopy(array, k, result, 0, diff);
// print the output
Question : https://www.hackerrank.com/challenges/ctci-array-left-rotation
Solution :
This is how I tried arrayLeftRotation method with complexity o(n)
looping once from k index to (length-1 )
2nd time for 0 to kth index
public static int[] arrayLeftRotation(int[] a, int n, int k) {
int[] resultArray = new int[n];
int arrayIndex = 0;
//first n-k indexes will be populated in this loop
for(int i = k ; i
resultArray[arrayIndex] = a[i];
arrayIndex++;
}
// 2nd k indexes will be populated in this loop
for(int j=arrayIndex ; j<(arrayIndex+k); j++){
resultArray[j]=a[j-(n-k)];
}
return resultArray;
}
package com.array.orderstatistics;
import java.util.Scanner;
public class ArrayRotation {
public static void main(String[] args) {
Scanner scan = new Scanner(System.in);
int n = scan.nextInt();
int r = scan.nextInt();
int[] a = new int[n];
int[] b = new int[n];
for (int i = 0; i < n; i++) {
a[i] = scan.nextInt();
}
scan.close();
if (r % n == 0) {
printOriginalArray(a);
} else {
r = r % n;
for (int i = 0; i < n; i++) {
b[i] = a[(i + r) < n ? (i + r) : ((i + r) - n)];
System.out.print(b[i] + " ");
}
}
}
private static void printOriginalArray(int[] a) {
for (int i = 0; i < a.length; i++) {
System.out.print(a[i] + " ");
}
}
}
Following routine rotates an array in java:
public static int[] rotateArray(int[] array, int k){
int to_move = k % array.length;
if(to_move == 0)
return array;
for(int i=0; i< to_move; i++){
int temp = array[array.length-1];
int j=array.length-1;
while(j > 0){
array[j] = array[--j];
}
array[0] = temp;
}
return array;
}
You can do something like below
class Solution {
public void rotate(int[] nums, int k) {
if (k==0) return;
if (nums == null || nums.length == 0) return;
for(int i=0;i<k;i++){
int j=nums.length-1;
int temp = nums[j];
for(;j>0;j--){
nums[j] = nums[j-1];
}
nums[0] = temp;
}
}
}
In the above solution, k is the number of times you want your array to rotate from left to right.
Question : Rotate array given a specific distance .
Method 1 :
Turn the int array to ArrayList. Then use Collections.rotate(list,distance).
class test1 {
public static void main(String[] args) {
int[] a = { 1, 2, 3, 4, 5, 6 };
List<Integer> list = Arrays.stream(a).boxed().collect(Collectors.toList());
Collections.rotate(list, 3);
System.out.println(list);//[4, 5, 6, 1, 2, 3]
}// main
}
I use this, just loop it a times
public void rotate(int[] arr) {
int temp = arr[arr.length - 1];
for(int i = arr.length - 1; i > 0; i--) {
arr[i] = arr[i - 1];
}
arr[0] = temp;
}
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;
}
}
I'm trying to implement multi-threading using merge sort. I have it making new threads at the point where it cuts an array in half.
The array is sorted depending on the:
[size of the array] vs [how many times I create new threads]
For instance: the array will be sorted if I let it create merely two threads on an array of size 70, but if I let it create 6, it will come back unsorted. One thing I thought it might be is that the threads weren't sync'd, but I used threadName.join()
here is some code: merge.java
import java.util.Random;
public class merge implements Runnable {
int[] list;
int length;
int countdown;
public merge(int size, int[] newList, int numberOfThreadReps, int firstMerge) {
length = size;
countdown = numberOfThreadReps;
list = newList;
if (firstMerge == 1)
threadMerge(0, length - 1);
}
public void run() {
threadMerge(0, length - 1);
}
public void printList(int[] list, int size) {
for (int i = 0; i < size; i++) {
System.out.println(list[i]);
}
}
public void regMerge(int low, int high) {
if (low < high) {
int middle = (low + high) / 2;
regMerge(low, middle);
regMerge(middle + 1, high);
mergeJoin(low, middle, high);
}
}
public void mergeJoin(int low, int middle, int high) {
int[] helper = new int[length];
for (int i = low; i <= high; i++) {
helper[i] = list[i];
}
int i = low;
int j = middle + 1;
int k = low;
while (i <= middle && j <= high) {
if (helper[i] <= helper[j]) {
list[k] = helper[i];
i++;
} else {
list[k] = helper[j];
j++;
}
k++;
}
while (i <= middle) {
list[k] = helper[i];
k++;
i++;
}
helper = null;
}
public void threadMerge(int low, int high) {
if (countdown > 0) {
if (low < high) {
countdown--;
int middle = (low + high) / 2;
int[] first = new int[length / 2];
int[] last = new int[length / 2 + ((length % 2 == 1) ? 1 : 0)];
for (int i = 0; i < length / 2; i++)
first[i] = list[i];
for (int i = 0; i < length / 2 + ((length % 2 == 1) ? 1 : 0); i++)
last[i] = list[i + length / 2];
merge thread1 = new merge(length / 2, first, countdown, 0);// 0
// is
// so
// that
// it
// doesn't
// call
// threadMerge
// twice
merge thread2 = new merge(length / 2
+ ((length % 2 == 1) ? 1 : 0), last, countdown, 0);
Thread merge1 = new Thread(thread1);
Thread merge2 = new Thread(thread2);
merge1.start();
merge2.start();
try {
merge1.join();
merge2.join();
} catch (InterruptedException ex) {
System.out.println("ERROR");
}
for (int i = 0; i < length / 2; i++)
list[i] = thread1.list[i];
for (int i = 0; i < length / 2 + ((length % 2 == 1) ? 1 : 0); i++)
list[i + length / 2] = thread2.list[i];
mergeJoin(low, middle, high);
} else {
System.out.println("elsd)");
}
} else {
regMerge(low, high);
}
}
}
proj4.java
import java.util.Random;
public class proj4 {
public static void main(String[] args) {
int size = 70000;
int threadRepeat = 6;
int[] list = new int[size];
list = fillList(list, size);
list = perm(list, size);
merge mergy = new merge(size, list, threadRepeat, 1);
// mergy.printList(mergy.list,mergy.length);
for (int i = 0; i < mergy.length; i++) {
if (mergy.list[i] != i) {
System.out.println("error)");
}
}
}
public static int[] fillList(int[] list, int size) {
for (int i = 0; i < size; i++)
list[i] = i;
return list;
}
public static int[] perm(int[] list, int size) {
Random generator = new Random();
int rand = generator.nextInt(size);
int temp;
for (int i = 0; i < size; i++) {
rand = generator.nextInt(size);
temp = list[i];
list[i] = list[rand];
list[rand] = temp;
}
return list;
}
}
so TL;DR my array isn't getting sorted by a multithreaded merge sort based on the size of the array and the number of times I split the array by using threads...why is that?
Wow. This was an interesting exercise in masochism. I'm sure you've moved on but I thought for posterity...
The bug in the code is in mergeJoin with the middle argument. This is fine for regMerge but in threadMerge the middle passed in is (low + high) / 2 instead of (length / 2) - 1. Since in threadMerge low is always 0 and high is length - 1 and the first array has (length / 2) size. This means that for lists with an odd number of entries, it will often fail depending on randomization.
There are also a number of style issues which makes this program significantly more complicated and error prone:
The code passes around a size of the arrays when Java has a convenient list.length call which would be more straightforward and safer.
The code duplicates calculations (see length/2) in a number of places.
The code should be able to sort inside the array without creating sub-arrays.
Classes should start with an uppercase letter (Merge instead of merge)
firstMerge should be a boolean
The code names the Thread variable merge1 and the merge variable thread1. Gulp.
The merge constructor calling threadMerge(0,length -1) is strange. I would just put that call after the new call back in proj4. Then firstMerge can be removed.
I would consider switching to having high be one past the maximum value instead of the maximum. We tend to think like for (int i = 0; i < 10; i++) more than i <= 9. Then the code can have j go from low to < middle and k from middle to < high. Better symmetry.
Best of luck.