Related
For this particular problem I am attempting to remove redundant elements in an sorted array and replace them all with 0s at the end of the array. For example, if I had an array consisting of the int elements
1,3,3,4,4,5,6,6,7
My output array should be
1,3,4,5,6,7,0,0,0
My first attempt at the problem was to create a swapper in order to push all the 0s to the end of the list after removing the elements, but it won't seem to push the zeros to the end of the list. Here is my code.
public void implode(int[] ary)
{
int swapper = -1;
int[] newARY = new int[ary.length];
int current = -1;
for (int i = 0; i < ary.length; i++)
{
if (current != ary[i])
{
newARY[i] = ary[i];
current = ary[i];
}
}
for (int i = 0; i < ary.length; i++)
{
if (ary[i] == 0)
{
if (ary[i + 1] != 0)
{
swapper = ary[i + 1];
ary[i] = swapper;
ary[i + 1] = 0;
}
}
}
ary = newARY;
for (int i = 0; i < newARY.length; i++)
{
System.out.print(newARY[i] + " ");
}
}
The array im testing it with is,
int[] aryIn2 = {1, 1, 2, 3, 4, 4, 5, 6};
However, when outputting the imploded array, I receive this one.
1 0 2 3 4 0 5 6
Is there something I am missing?
Thanks in advance.
not an answer to your problem, but using (if possible) java streams can shorten your way:
int[] arr = {1,3,3,4,4,5,6,6,7};
// distinct
List<Integer> list = Arrays.stream(arr).distinct().boxed().collect(Collectors.toList());
// pad with zero's
while(list.size() < arr.length) {
list.add(0);
}
// display
System.out.println(list.stream().map(String::valueOf).collect(Collectors.joining(",")));
will output
1,3,4,5,6,7,0,0,0
Two issue with you code that I observed.
1) Your swapper logic is performing swapping on a different array than the one in which you had done modification earlier
2) You need to have this logic in a bubble-sort way, i.e. loop inside a loop
Below is a working modified sample code of your method. I have modified only the second for-loop logic
public void implode(int[] ary) {
int swapper = -1;
int[] newARY = new int[ary.length];
int current = -1;
for (int i = 0; i < ary.length; i++) {
if (current != ary[i]) {
newARY[i] = ary[i];
current = ary[i];
}
}
for (int i = 0; i < newARY.length - 1; i++) {
if (newARY[i] == 0 && newARY[i + 1] != 0) {
for (int j = i; (j + 1) < newARY.length; j++) {
swapper = newARY[j + 1];
newARY[j] = swapper;
newARY[j + 1] = 0;
}
}
}
for (int i = 0; i < newARY.length; i++) {
System.out.print(newARY[i] + " ");
}
}
In this first loop:
for (int i = 0; i < ary.length; i++) {
if (current != ary[i]) {
newARY[i] = ary[i];
current = ary[i];
}
}
You fill newARY with elements in ary with duplicated value turns to 0:
newARY: 1 0 2 3 4 0 5 6
However, in the second loop:
for (int i = 0; i < ary.length; i++)
{
if (ary[i] == 0)
{
if (ary[i + 1] != 0)
{
swapper = ary[i + 1];
ary[i] = swapper;
ary[i + 1] = 0;
}
}
}
You're modifying your original ary array. So the newARY is not updated.
However, your attempt to push 0 to the end of array also fail if there are more than two 0s consecutive. And it is also vulnerable to ArrayOutOfBoundIndexException since you try to read ary[i+1] without restriction on i
One simple and straight forward way to push 0s to the end of the array is to create new array with non-0s elements and fill 0s later:
int[] result = new int[ary.lenght];
int resultIndex = 0;
for (int i = 0; i < newARY.length; i++) {
if (newARY[i] != 0) {
result[resultIndex++] = newAry[i];
}
}
for (int i = resultIndex; i < newARY.length; i++) {
result[i] = 0;
}
// Print result array
Hint: Using above strategy, you can simplify your code. No need to create immediate array newARY. Just loop over the original array, push unique elements to the result array, then fill any slot left with 0s.
For example if input is:
2 0 6 3 1 6 3 1 6 3 1
then output should be 6 3 1.Need to find the first repetition cycle.
class FindDuplicate
{
void printRepeating(int arr[], int size)
{
int i;
System.out.println("The repeating elements are : ");
for (i = 0; i < size; i++)
{
if (arr[Math.abs(arr[i])] >= 0)
arr[Math.abs(arr[i])] = -arr[Math.abs(arr[i])];
else
System.out.print(Math.abs(arr[i]) + " ");
}
}
public static void main(String[] args)
{
FindDuplicate duplicate = new FindDuplicate();
int arr[] = {1, 2, 3, 1, 2, 3, 1, 2, 3 };
int arr_size = arr.length;
duplicate.printRepeating(arr, arr_size);
}
}
https://pastebin.com/12bnjzfw
Have used java 8 streams for collection creation.
for (int seqSize = ints.size() / 2; seqSize > 0; seqSize--) { //It should be first cycle. Main priority is biggest sequence
for (int i = 0; i < ints.size() / seqSize; i++) { //Start position of the first block
for (int j = i + seqSize; j < ints.size() - seqSize + 1; j++) {
if (ints.subList(i, i + seqSize).equals(ints.subList(j, j + seqSize))) {
System.out.println("Answer is: " + ints.subList(i, i + seqSize));
return;
}
}
}
}
class FindDuplicate {
static int STRING_LENGTH = 3;
void printRepeating(int arr[], int size) {
int i;
System.out.println("The repeating elements are : ");
String strVal = "";
for (int ii = 0; ii < size; ii++) {
strVal += arr[ii];
}
// strVal now has something we can search with.
for (i = 0; i < size; i++) {
int end = Math.min(size,i+STRING_LENGTH );
String searchString = strVal.substring(i, end);
if (searchString.length() != STRING_LENGTH)
break; // at end of arr, doesn't have length to search
int matchIndex = strVal.indexOf(searchString, i+1);
if (matchIndex != -1) {
String match = strVal.substring(matchIndex, matchIndex + STRING_LENGTH);
System.out.print(match + " ");
break; // done with loop
}
}
}
public static void main(String[] args) {
FindDuplicate duplicate = new FindDuplicate();
int arr[] = {1, 2, 3, 1, 2, 3, 1, 2, 3 };
int arr_size = arr.length;
duplicate.printRepeating(arr, arr_size);
}
}
Loop through those array elements and cache your elements until you have the same value for example
List list = Arrays.asList(1,2,3);
if(list.contains(element))
//code to check here
you will need get size of your list and based on that check exactly this amount of items if they match if yes then output if not clear cache and start cache from the begging.
This is the question:
codility.com/programmers/task/number_solitaire
and below link is my result (50% from Codility):
https://codility.com/demo/results/training8AMJZH-RTA/
My code (at the first, I tried to solve this problem using Kadane's Algo):
class Solution {
public int solution(int[] A) {
int temp_max = Integer.MIN_VALUE;
int max = 0;
int k = 1;
if(A.length == 2) return A[0] + A[A.length-1];
for(int i = 1; i < A.length-1; i++) {
if(temp_max < A[i]) temp_max = A[i];
if(A[i] > 0) {
max += A[i];
temp_max = Integer.MIN_VALUE;
k = 0;
} else if(k % 6 == 0) {
max += temp_max;
temp_max = Integer.MIN_VALUE;
k = 0;
}
k++;
}
return A[0] + max + A[A.length-1];
}
And below is the solution (100% from Codility result) that I found from web:
class Solution {
public int solution(int[] A) {
int[] store = new int[A.length];
store[0] = A[0];
for (int i = 1; i < A.length; i++) {
store[i] = store[i-1];
for (int minus = 2; minus <= 6; minus++) {
if (i >= minus) {
store[i] = Math.max(store[i], store[i - minus]);
} else {
break;
}
}
store[i] += A[i];
}
return store[A.length - 1];
}
}
I have no idea what is the problem with my code:(
I tried several test cases but, nothing different with the solution & my code
but, codility test result shows mine is not perfectly correct.
(https://codility.com/demo/results/training8AMJZH-RTA/)
please anyone explain me the problem with my code~~
Try this test case[-1, -2, -3, -4, -3, -8, -5, -2, -3, -4, -5, -6, -1].
you solution return -4 (A[0],A[1],A[length-1],Here is the mistake), but the correct answer is -6 (A[0],A[6],A[length-1]).
Here is a my solution,easy to understand:
public int solution(int[] A) {
int lens = A.length;
int dp[] = new int[6];
for (int i = 0; i < 6; i++) {
dp[i] = A[0];
}
for (int i = 1; i < lens; i++) {
dp[i%6] = getMax6(dp) + A[i];
}
return dp[(lens-1)%6];
}
private int getMax6(int dp[]){
int max = dp[0];
for (int i = 1; i < dp.length; i++) {
max = Math.max(max, dp[i]);
}
return max;
}
Readable solution from Java:
public class Solution {
public static void main(String[] args) {
System.out.println(new Solution().solution(new int[]{1, -2, 0, 9, -1, -2}));
}
private int solution(int[] A) {
int N = A.length;
int[] dp = new int[N];
dp[0] = A[0];
for (int i = 1; i < N; i++) {
double sm = Double.NEGATIVE_INFINITY;
for (int j = 1; j <= 6; j++) {
if (i - j < 0) {
break;
}
double s1 = dp[i - j] + A[i];
sm = Double.max(s1, sm);
}
dp[i] = (int) sm;
}
return dp[N-1];
}
}
Here is a solution similar to #0xAliHn but using less memory. You only need to remember the last 6 moves.
def NumberSolitaire(A):
dp = [0] * 6
dp[-1] = A[0]
for i in range(1, len(A)):
maxVal = -100001
for k in range(1, 7):
if i-k >= 0:
maxVal = max(maxVal, dp[-k] + A[i])
dp.append(maxVal)
dp.pop(0)
return dp[-1]
Based on the solutions posted, I made nice readable code. Not best performance.
int[] mark = new int[A.length];
mark[0] = A[0];
IntStream.range(1, A.length)
.forEach(i -> {
int max = Integer.MIN_VALUE;
mark[i] = IntStream.rangeClosed(1, 6)
.filter(die -> i - die >= 0)
.map(r -> Math.max(mark[i - r] + A[i], max))
.max().orElse(max);
});
return mark[A.length - 1];
Because you are not using dynamic programming, you are using greedy algorithm. Your code will fail when the max number in a range will not be the right choice.
function solution(A) {
// This array contains a maximal value at any index.
const maxTill = [A[0]];
// It's a dynamic programming so we will choose maximal value at each
// Index untill we reach last index (goal)
for (let i = 1; i < A.length; i++) {
// Step 1 . max value of each index will be atleast equal to or greater than
// max value of last index.
maxTill[i] = maxTill[i - 1];
// For each index we are finding the max of last 6 array value
// And storing it into Max value.
for (let dice = 1; dice <= 6; dice++) {
// If array index is itself less than backtrack index
// break as you dont have 6 boxes in your left
if (dice > i) {
break;
} else {
// The most important line .
// Basically checking the max of last 6 boxes using a loop.
maxTill[i] = Math.max(
maxTill[i - dice],
maxTill[i]
);
}
}
// Until this point maxStill contains the maximal value
// to reach to that index.
// To end the game we need to touch that index as well, so
// add the value of the index as well.
maxTill[i] += A[i];
}
return maxTill[A.length - 1];
}
console.log(solution([-1, -2, -3, -4, -3, -8, -5, -2, -3, -4, -5, -6, -1]));
This is my solution. I try to make the code easy to apprehend. It might not save space as much as it can.
private static int solution(int A[])
{
// N // N is an integer within the range [2..100,000];
// A[] // each element of array A is an integer within the range [−10,000..10,000].
int N = A.length;
int[] bestResult = new int[N]; // record the current bestResult
Arrays.fill(bestResult, Integer.MIN_VALUE); // fill in with the smallest integer value
// initialize
bestResult[0] = A[0];
for (int i = 0;i < A.length;i++) {
// calculate six possible results every round
for (int j = i + 1; (j < A.length) && (i < A.length) && j < (i + 1) + 6; j++) {
// compare
int preMaxResult = bestResult[j]; // the max number so far
int nowMaxResult = bestResult[i] + A[j]; // the max number at bestResult[i] + A[j]
bestResult[j] = Math.max(preMaxResult, nowMaxResult);
}
}
return bestResult[bestResult.length-1];
}
Here is the simple Python 3 solution:
import sys
def solution(A):
dp = [0] * len(A)
dp[0] = A[0]
for i in range(1, len(A)):
maxVal = -sys.maxsize - 1
for k in range(1, 7):
if i-k >= 0:
maxVal = max(maxVal, dp[i-k] + A[i])
dp[i] = maxVal
return dp[len(A)-1]
100% c++ solution(
results)
#include <climits>
int solution(vector<int>& A) {
const int N = A.size();
if (N == 2)
return A[0] + A[1];
vector<int> MaxSum(N, INT_MIN);
MaxSum[0] = A[0];
for (int i = 1; i < N; i++) {
for (int dice = 1; dice <= 6; dice++) {
if (dice > i)
break;
MaxSum[i] = max(MaxSum[i], A[i] + MaxSum[i - dice]);
}
}
return MaxSum[N-1];
}
100% python solution
with the help of the answers above and https://sapy.medium.com/cracking-the-coding-interview-30eb419c4c57
def solution(A):
# write your code in Python 3.6
# initialize maxUntil [0]*n
n = len(A)
maxUntil = [0 for i in range(n)]
maxUntil[0]=A[0]
# fill in maxUntil, remember to chack limits
for i in range(1, n): # for each
maxUntil[i] = maxUntil [i-1]
# check the max 6 to the left:
# for 1,..,6:
for dice in range(1,7):
if dice > i: # if dice bigger than loc - we are out of range
break
#else: check if bigger than cur elem, if so - update elem
maxUntil[i] = max(maxUntil[i],maxUntil[i-dice])
# add the current jump:
maxUntil[i] +=A[i]
# must reach the last sq:
return maxUntil[n-1]
I would like to explain the algorithm I have come up with and then show you the implementation in C++.
Create a hash for the max sums. We only need to store the elements within reach, so the last 6 elements. This is because the dice can only go back so much.
Initialise the hash with the first element in the array for simplicity since the first element in this hash equals to the first element of the inputs.
Then go through the input elements from the second element.
For each iteration, find the maximum values from the last 6 indices. Add the current value to that to get the current max sum.
When we reach the end of the inputs, exit the loop.
Return the max sum of the last element calculated. For this, we need clipping with module due to the space optimisation
The runtime complexity of this dynamic programming solution is O(N) since we go through element in the inputs. If we consider the dice range K, then this would be O(N * K).
The space complexity is O(1) because we have a hash for the last six elements. It is O(K) if we does not consider the number of dice faces constant, but K.
int solution(vector<int> &A)
{
vector<int> max_sums(6, A[0]);
for (size_t i = 1; i < A.size(); ++i) max_sums[i % max_sums.size()] = *max_element(max_sums.cbegin(), max_sums.cend()) + A[i];
return max_sums[(A.size() - 1) % max_sums.size()];
}
Here's my answer which gives 100% for Kotlin
val pr = IntArray(A.size) { Int.MIN_VALUE }
pr[0] = A.first()
for ((index, value) in pr.withIndex()) {
for (i in index + 1..min(index + 6, A.lastIndex)) {
pr[i] = max(value + A[i], pr[i])
}
}
return pr.last()
I used forwarded prediction, where I fill the next 6 items of the max value the current index can give.
As a part of the Java interview question paper I have got following issue to solve.
But I am bit wonder whether how can I implement it without any Collection or intermediate Array.
Question:- Count duplicates from int array without using any Collection or another intermediate Array
Input values:- {7,2,6,1,4,7,4,5,4,7,7,3, 1}
Output:- Number of duplicates values: 3
Duplicates values: 7, 4, 1
I have implemented following solution but was not completed one.
Any one has some idea? Thanks.
public static void duplicate(int numbers[]) {
for (int i = 0; i < numbers.length; i++) {
boolean duplicate = false;
int j = 0;
while (j < i){
if ((i != j) && numbers[i] == numbers[j]) {
duplicate = true;
}
j++;
}
if (duplicate) {
System.out.print(numbers[i] + " ");
}
}
}
The easiest way to solve this problem is to sort the array first, and then just walk through the array counting duplicates as you encounter them:
int[] numbers = new int[]{7,2,6,1,4,7,4,5,4,7,7,3,1};
int temp = 0;
// I chose to do a bubble sort of the array,
// but you are free to use any method you wish (e.g. Arrays.sort)
System.out.print("Duplicates values: ");
for (int i=0; i < numbers.length; ++i) {
for (int j=1; j < (numbers.length - i); ++j) {
if (numbers[j-1] > numbers[j]) {
temp = numbers[j-1];
numbers[j-1] = numbers[j];
numbers[j] = temp;
}
}
}
// walk through the sorted array and count duplicates
int numDup = 0, dupCount = 0;
int previous = -1;
for (int i=0; i < numbers.length; ++i) {
if (numbers[i] == previous) {
++numDup;
if (numDup == 1) {
++dupCount;
if (dupCount == 1) {
System.out.print(numbers[i]);
}
else {
System.out.print(", " + numbers[i]);
}
}
}
else {
previous = numbers[i];
numDup = 0;
}
}
System.out.println("\nNumber of duplicates values: " + dupCount);
Output:
Duplicates values: 1, 4, 7
Number of duplicates values: 3
Note that my output order is reverse of what you have, because you need to read through the entire array before you know how many total duplicates you have. Also, I will point out that the only state this solution uses is the input array itself, plus a couple of int varibles here and there.
This code has been tested in IntelliJ and it works correctly.
Agreed to Tim #tim-biegeleisen. Just minor change. Use the Arrays to sort the array.
import java.util.*;
public class DuplicateClass {
public static void main(String[] args) {
int[] values = { 7, 2, 6, 1, 4, 7, 4, 5, 4, 7, 7, 3, 1 };
duplicate(values);
}
public static void duplicate(int numbers[]) {
Arrays.sort(numbers);
int previous = numbers[0] - 1;
int dupCount = 0;
for (int i = 0; i < numbers.length; ++i) {
if (numbers[i] == previous) {
++dupCount;
} else {
previous = numbers[i];
}
}
System.out.println("There were " + dupCount + " duplicates in the array.");
}
}
These are all great answers. One other is to use an int/double and set it's bits when you encounter a number. This works if the array's values are less than 32/64 depending on the type you use.
Below is an example of how you would do that with an integer.
public class SetThoseBits{
// 0000 0000 0000 0000 000 0000 0000 0000
public static int data = 0;
public static void main(String [] args){
// Gurantee that the numbers are less than 32
int[] values = { 7, 2, 6, 1, 4, 7, 4, 5, 4, 7, 7, 3, 1 };
duplicates(values);
}
public static void duplicates(int [] values){
for(int i : values){
if(testBit(i)){
System.out.println("Duplicate :" + i);
} else{
setBit(i);
}
//printBits();
}
System.out.println("Finished!");
}
// Sets the bit at a specific position
public static void setBit(int index){
data = data | (1 << index);
}
// This function will test the bit at the index of the given integer
// If it's set, it returns true
public static boolean testBit(int index){
return ((data & (1 << index)) != 0);
}
public static void printBits(){
for (int x = 31; x >= 0; x--){
if(testBit(x)){
System.out.print("1");
} else{
System.out.print("0");
}
}
System.out.println("0");
}
}
I believe the the other answers are better given your question..but demonstrating this as an alternative shows that you're thinking about it dynamically. If the requirements of the question changed a little this answer might be more appropriate.
Further if you only need to keep track of duplicates given the smallest footprint possible, you could do something similar to what is above or use java's BitSet class to make your life easier.
http://docs.oracle.com/javase/7/docs/api/java/util/BitSet.html
Edit: It is also possible to have values higher than 64 given that you create a function that holds an array of bytes like the BitSet class. For this exact question this isn't helpful given the constraint to not use an array or collection.
private static int solution3(List<Integer> inputArr) {
// Time Complexity O(N)
// Space Complexity O(1)
// Stream
return (int) inputArr.stream()
.collect(Collectors
.toMap(Function.identity(), v -> 1, Integer::sum))
.entrySet().stream()
.filter(k -> k.getValue() >= 2)
.count();
}
Keeping one extra variable for maintaining count, plus sorting of array in the initial phase.
public static void main(String[] args) {
int[] numbers = { 7, 2, 6, 1, 4, 7, 4, 5, 4, 7, 7, 3, 1 };
Arrays.sort(numbers);
System.out.println("Sorted Array is :: = " + Arrays.toString(numbers));
int count = 0;
int tempCount = 0; // to keep local count of matched numbers
String duplicates = "";
for (int i = 1; i < numbers.length; i++) {
if (numbers[i] == numbers[i - 1]) {
if ((tempCount == 0)) { // If same number is repeated more than
// two times, like 444, 7777
count = count + 1;
tempCount = tempCount + 1;
duplicates = duplicates.concat(Integer.toString(numbers[i])
+ ",");
}
} else {
tempCount = 0;
}
}
System.out.println("No of duplicates :: = " + count);
System.out.println("Duplicate Numbers are :: = " + duplicates);
}
output
Sorted Array is :: = [1, 1, 2, 3, 4, 4, 4, 5, 6, 7, 7, 7, 7]
No of duplicates :: = 3
Duplicate Numbers are :: = 1,4,7,
int numbers[]={7,2,6,1,4,7,4,5,4,7,7,3, 1};
String temp="";
int count=0;
Arrays.sort(numbers);
for (int i = 0; i < numbers.length; i++) {
boolean duplicate = false;
for(int j = 0; j < numbers.length; j++) {
if ((i != j) && numbers[i] == numbers[j]) {
duplicate = true;
}
}
if (duplicate) {
if(!temp.contains(""+numbers[i]))
{
temp+=numbers[i]+", ";//adding a number if its duplicate
count++;//counting unique duplicate number
}
System.out.print(numbers[i] + " ");
}
}
System.out.println("\nDuplicates are: "+temp+" count: "+count);
Output:
Duplicates are: 1, 4, 7, count: 3
I think, this is also a way to calculate it:
public class App {
public static void main(String[] args) {
Integer[] intArr = { 7, 2, 6, 1, 4, 7, 4 };
List<Integer> listInt = Arrays.asList(intArr);
Map<Integer, Integer> map = new HashMap<>();
Integer dupCount = 0;
StringBuilder dupvalues = new StringBuilder();
for (Integer integer : intArr) {
int times = Collections.frequency(listInt, integer);
if (map.containsKey(integer)) {
dupvalues.append(integer).append(",");
dupCount++;
} else
map.put(integer, times);
}
System.out.println("There were " + dupCount + " duplicates in the array. The value are : "+dupvalues);
}
}
This is the simplest solution I can think of. I just added an extra counter so that integers with two or more repetitions still in the array are ignored.
static int findNumber(int[] arr)
{
int duplicateCounter = 0;
System.out.print("Duplicates: ");
for(int i = 0; i < arr.length; i++)
{
boolean duplicate = false;
int numOfOccurrences = 1;
for (int j = (i+1); j < arr.length; j++)
{
if (arr[i] == arr[j])
{
numOfOccurrences++;
duplicate = true;
}
}
if(numOfOccurrences == 2 && duplicate == true)
{
duplicateCounter++;
System.out.print(arr[i] + " ");
}
}
return duplicateCounter;
}
My test run: Test run
Input: 1, 2, 3, 4, 2, 4, 1, 1, 1
Duplicates: 2 4 1
Number of duplicates: 3
Below method not use any collection, just use Arrays.sort() method to help sort array into ascending order as default, e.g array = [9,3,9,3,9] will sort into [3,3,9,9,9].If input [9,9,9,9,9], expected result is 1, since only repeated number is 9.If input [9,3,9,3,9,255,255,1], expected result is 3, since repeated numbers are 3,9,255. If input [7,2,6,1,4,7,4,5,4,7,7,3,1], expected result is 3, since repeated numbers are 1,4,7.
public static int findDuplicateCountsInArray(int[] nums) {
// Sort the input array into default ascending order
Arrays.sort(nums);
int prev = nums[0];
int count = 0;
// Recording a number already a repeated one
// e.g [9,9,9] the 3rd 9 will not increase duplicate count again
boolean numAlreadyRepeated = false;
for(int i = 1; i < nums.length; i++) {
if(prev == nums[i] && !numAlreadyRepeated) {
count++;
numAlreadyRepeated = true;
} else if(prev != nums[i]) {
prev = nums[i];
numAlreadyRepeated = false;
}
}
return count;
}
Here I have written code in JAVA. also the inputted numbers, have been considered as String. This question has also been added to CODEWARS. and I hope this simple solution helps You
public class countingduplicates {
public static void main(String[] args) {
int i=0,j=0,c=0,a=0;
String text="7261474547731";
text=text.toLowerCase();
for(i=0; i<text.length(); i++) {
for(j=0; j<text.length(); j++) {
if(text.charAt(i) == text.charAt(j)) {
c++;
}
}
System.out.println(text.charAt(i) + " occured " + c + " times");
if(c>1) {
a++;
}
String d = String.valueOf(text.charAt(i)).trim();
text = text.replaceAll(d,"");
c = 0;
i = 0; //cause i have trimmed the string and by default i increases by 1, so i have to assign it =0
j = 0; //cause i have trimmed the string and by default j increases by 1, so i have to assign it =0
}
System.out.println("Total count of Duplicates:" + a);
}
}
This is practically very easy in Python. You can check this code. I am giving you 2 methods. Please take a look at it.
array = ['a','b','c','d','a','b','c','d','e']
array1 = [1,2,2,3,3,3,4,5,6,4,4,5,5,5,5]
output = {i : array1.count(i) for i in array1 }
print(output) #{1: 1, 2: 2, 3: 3, 4: 3, 5: 5, 6: 1}
output2 = dict(Counter(array1))
print(output2) #{1: 1, 2: 2, 3: 3, 4: 3, 5: 5, 6: 1}
If you want only the Duplicate numbers, then :
#method 1
output = [k for k,v in Counter(array1).items() if v>1 ]
print(output)
If you want only the Distinct numbers, then :
#method 1
#Prints only Distinct absolute values
O2 = set([abs(i) for i in array1])
print(O2) #1,2,3,4,5,6
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I just had a codility problem give me a hard time and I'm still trying to figure out how the space and time complexity constraints could have been met.
The problem is as follows:
A dominant member in the array is one that occupies over half the positions in the array, for example:
{3, 67, 23, 67, 67}
67 is a dominant member because it appears in the array in 3/5 (>50%) positions.
Now, you are expected to provide a method that takes in an array and returns an index of the dominant member if one exists and -1 if there is none.
Easy, right? Well, I could have solved the problem handily if it were not for the following constraints:
Expected time complexity is O(n)
Expected space complexity is O(1)
I can see how you could solve this for O(n) time with O(n) space complexities as well as O(n^2) time with O(1) space complexities, but not one that meets both O(n) time and O(1) space.
I would really appreciate seeing a solution to this problem. Don't worry, the deadline has passed a few hours ago (I only had 30 minutes), so I'm not trying to cheat. Thanks.
Googled "computing dominant member of array", it was the first result. See the algorithm described on page 3.
element x;
int count ← 0;
For(i = 0 to n − 1) {
if(count == 0) { x ← A[i]; count++; }
else if (A[i] == x) count++;
else count−−;
}
Check if x is dominant element by scanning array A
Basically observe that if you find two different elements in the array, you can remove them both without changing the dominant element on the remainder. This code just keeps tossing out pairs of different elements, keeping track of the number of times it has seen the single remaining unpaired element.
Find the median with BFPRT, aka median of medians (O(N) time, O(1) space). Then scan through the array -- if one number dominates, the median will be equal to that number. Walk through the array and count the number of instances of that number. If it's over half the array, it's the dominator. Otherwise, there is no dominator.
Adding a Java 100/100 O(N) time with O(1) space:
https://codility.com/demo/results/demoPNG8BT-KEH/
class Solution {
public int solution(int[] A) {
int indexOfCandidate = -1;
int stackCounter = 0, candidate=-1, value=-1, i =0;
for(int element: A ) {
if (stackCounter == 0) {
value = element;
++stackCounter;
indexOfCandidate = i;
} else {
if (value == element) {
++stackCounter;
} else {
--stackCounter;
}
}
++i;
}
if (stackCounter > 0 ) {
candidate = value;
} else {
return -1;
}
int countRepetitions = 0;
for (int element: A) {
if( element == candidate) {
++countRepetitions;
}
if(countRepetitions > (A.length / 2)) {
return indexOfCandidate;
}
}
return -1;
}
}
If you want to see the Java source code it's here, I added some test cases as comments as the beginning of the file.
Java solution with score 100%
public int solution(int[] array) {
int candidate=0;
int counter = 0;
// Find candidate for leader
for(int i=0; i<array.length; i++){
if(counter == 0) candidate = i;
if(array[i] == array[candidate]){
counter++;
}else {
counter--;
}
}
// Count candidate occurrences in array
counter = 0;
for(int i=0; i<array.length; i++){
if(array[i] == array[candidate]) counter++;
}
// Check that candidate occurs more than array.lenght/2
return counter>array.length/2 ? candidate : -1;
}
In python, we are lucky some smart people have bothered to implement efficient helpers using C and shipped it in the standard library. The collections.Counter is useful here.
>>> data = [3, 67, 23, 67, 67]
>>> from collections import Counter
>>> counter = Counter(data) # counter accepts any sequence/iterable
>>> counter # dict like object, where values are the occurrence
Counter({67: 3, 3: 1, 23: 1})
>>> common = counter.most_common()[0]
>>> common
(67, 3)
>>> common[0] if common[1] > len(data) / 2.0 + 1 else -1
67
>>>
If you prefer a function here is one ...
>>> def dominator(seq):
counter = Counter(seq)
common = counter.most_common()[0]
return common[0] if common[1] > len(seq) / 2.0 + 1 else -1
...
>>> dominator([1, 3, 6, 7, 6, 8, 6])
-1
>>> dominator([1, 3, 6, 7, 6, 8, 6, 6])
6
This question looks hard if a small trick does not come to the mind :). I found this trick in this document of codility : https://codility.com/media/train/6-Leader.pdf.
The linear solution is explained at the bottom of this document.
I implemented the following java program which gave me a score of 100 on the same lines.
public int solution(int[] A) {
Stack<Integer> stack = new Stack<Integer>();
for (int i =0; i < A.length; i++)
{
if (stack.empty())
stack.push(new Integer(A[i]));
else
{
int topElem = stack.peek().intValue();
if (topElem == A[i])
{
stack.push(new Integer(A[i]));
}
else
{
stack.pop();
}
}
}
if (stack.empty())
return -1;
int elem = stack.peek().intValue();
int count = 0;
int index = 0;
for (int i = 0; i < A.length; i++)
{
if (elem == A[i])
{
count++;
index = i;
}
}
if (count > ((double)A.length/2.0))
return index;
else
return -1;
}
Here's my C solution which scores 100%
int solution(int A[], int N) {
int candidate;
int count = 0;
int i;
// 1. Find most likely candidate for the leader
for(i = 0; i < N; i++){
// change candidate when count reaches 0
if(count == 0) candidate = i;
// count occurrences of candidate
if(A[i] == A[candidate]) count++;
else count--;
}
// 2. Verify that candidate occurs more than N/2 times
count = 0;
for(i = 0; i < N; i++) if(A[i] == A[candidate]) count++;
if (count <= N/2) return -1;
return candidate; // return index of leader
}
100%
import java.util.HashMap;
import java.util.Map;
class Solution {
public static int solution(int[] A) {
final int N = A.length;
Map<Integer, Integer> mapOfOccur = new HashMap((N/2)+1);
for(int i=0; i<N; i++){
Integer count = mapOfOccur.get(A[i]);
if(count == null){
count = 1;
mapOfOccur.put(A[i],count);
}else{
mapOfOccur.replace(A[i], count, ++count);
}
if(count > N/2)
return i;
}
return -1;
}
}
Does it have to be a particularly good algorithm? ;-)
static int dominant(final int... set) {
final int[] freqs = new int[Integer.MAX_VALUE];
for (int n : set) {
++freqs[n];
}
int dom_freq = Integer.MIN_VALUE;
int dom_idx = -1;
int dom_n = -1;
for (int i = set.length - 1; i >= 0; --i) {
final int n = set[i];
if (dom_n != n) {
final int freq = freqs[n];
if (freq > dom_freq) {
dom_freq = freq;
dom_n = n;
dom_idx = i;
} else if (freq == dom_freq) {
dom_idx = -1;
}
}
}
return dom_idx;
}
(this was primarily meant to poke fun at the requirements)
Consider this 100/100 solution in Ruby:
# Algorithm, as described in https://codility.com/media/train/6-Leader.pdf:
#
# * Iterate once to find a candidate for dominator.
# * Count number of candidate occurences for the final conclusion.
def solution(ar)
n_occu = 0
candidate = index = nil
ar.each_with_index do |elem, i|
if n_occu < 1
# Here comes a new dominator candidate.
candidate = elem
index = i
n_occu += 1
else
if candidate == elem
n_occu += 1
else
n_occu -= 1
end
end # if n_occu < 1
end
# Method result. -1 if no dominator.
# Count number of occurences to check if candidate is really a dominator.
if n_occu > 0 and ar.count {|_| _ == candidate} > ar.size/2
index
else
-1
end
end
#--------------------------------------- Tests
def test
sets = []
sets << ["4666688", [1, 2, 3, 4], [4, 6, 6, 6, 6, 8, 8]]
sets << ["333311", [0, 1, 2, 3], [3, 3, 3, 3, 1, 1]]
sets << ["313131", [-1], [3, 1, 3, 1, 3, 1]]
sets << ["113333", [2, 3, 4, 5], [1, 1, 3, 3, 3, 3]]
sets.each do |name, one_of_expected, ar|
out = solution(ar)
raise "FAILURE at test #{name.inspect}: #{out.inspect} not in #{expected.inspect}" if not one_of_expected.include? out
end
puts "SUCCESS: All tests passed"
end
Here is an easy to read, 100% score version in Objective-c
if (A.count > 100000)
return -1;
NSInteger occur = 0;
NSNumber *candidate = nil;
for (NSNumber *element in A){
if (!candidate){
candidate = element;
occur = 1;
continue;
}
if ([candidate isEqualToNumber:element]){
occur++;
}else{
if (occur == 1){
candidate = element;
continue;
}else{
occur--;
}
}
}
if (candidate){
occur = 0;
for (NSNumber *element in A){
if ([candidate isEqualToNumber:element])
occur++;
}
if (occur > A.count / 2)
return [A indexOfObject:candidate];
}
return -1;
100% score JavaScript solution. Technically it's O(nlogn) but still passed.
function solution(A) {
if (A.length == 0)
return -1;
var S = A.slice(0).sort(function(a, b) {
return a - b;
});
var domThresh = A.length/2;
var c = S[Math.floor(domThresh)];
var domCount = 0;
for (var i = 0; i < A.length; i++) {
if (A[i] == c)
domCount++;
if (domCount > domThresh)
return i;
}
return -1;
}
This is the solution in VB.NET with 100% performance.
Dim result As Integer = 0
Dim i, ladderVal, LadderCount, size, valCount As Integer
ladderVal = 0
LadderCount = 0
size = A.Length
If size > 0 Then
For i = 1 To size - 1
If LadderCount = 0 Then
LadderCount += 1
ladderVal = A(i)
Else
If A(i) = ladderVal Then
LadderCount += 1
Else
LadderCount -= 1
End If
End If
Next
valCount = 0
For i = 0 To size - 1
If A(i) = ladderVal Then
valCount += 1
End If
Next
If valCount <= size / 2 Then
result = 0
Else
LadderCount = 0
For i = 0 To size - 1
If A(i) = ladderVal Then
valCount -= 1
LadderCount += 1
End If
If LadderCount > (LadderCount + 1) / 2 And (valCount > (size - (i + 1)) / 2) Then
result += 1
End If
Next
End If
End If
Return result
See the correctness and performance of the code
Below solution resolves in complexity O(N).
public int solution(int A[]){
int dominatorValue=-1;
if(A != null && A.length>0){
Hashtable<Integer, Integer> count=new Hashtable<>();
dominatorValue=A[0];
int big=0;
for (int i = 0; i < A.length; i++) {
int value=0;
try{
value=count.get(A[i]);
value++;
}catch(Exception e){
}
count.put(A[i], value);
if(value>big){
big=value;
dominatorValue=A[i];
}
}
}
return dominatorValue;
}
100% in PHP https://codility.com/demo/results/trainingVRQGQ9-NJP/
function solution($A){
if (empty($A)) return -1;
$copy = array_count_values($A); // 3 => 7, value => number of repetition
$max_repetition = max($copy); // at least 1 because the array is not empty
$dominator = array_search($max_repetition, $copy);
if ($max_repetition > count($A) / 2) return array_search($dominator, $A); else return -1;
}
i test my code its work fine in arrays lengths between 2 to 9
public static int sol (int []a)
{
int count = 0 ;
int candidateIndex = -1;
for (int i = 0; i <a.length ; i++)
{
int nextIndex = 0;
int nextOfNextIndex = 0;
if(i<a.length-2)
{
nextIndex = i+1;
nextOfNextIndex = i+2;
}
if(count==0)
{
candidateIndex = i;
}
if(a[candidateIndex]== a[nextIndex])
{
count++;
}
if (a[candidateIndex]==a[nextOfNextIndex])
{
count++;
}
}
count -- ;
return count>a.length/2?candidateIndex:-1;
}
Adding a Java 100/100 O(N) time with O(1) space:
// you can also use imports, for example:
import java.util.Stack;
// you can write to stdout for debugging purposes, e.g.
// System.out.println("this is a debug message");
class Solution {
public int solution(int[] A) {
// write your code in Java SE 8
int count = 0;
Stack<Integer> integerStack = new Stack<Integer>();
for (int i = 0; i < A.length; i++) {
if (integerStack.isEmpty()) {
integerStack.push(A[i]);
} else if (integerStack.size() > 0) {
if (integerStack.peek() == A[i])
integerStack.push(A[i]);
else
integerStack.pop();
}
}
if (!integerStack.isEmpty()) {
for (int i = 0; i < integerStack.size(); i++) {
for (int j = 0; j < A.length; j++) {
if (integerStack.get(i) == A[j])
count++;
if (count > A.length / 2)
return j;
}
count = 0;
}
}
return -1;
}
}
Here is test result from codility.
I think this question has already been resolved somewhere. The "official" solution should be :
public int dominator(int[] A) {
int N = A.length;
for(int i = 0; i< N/2+1; i++)
{
int count=1;
for(int j = i+1; j < N; j++)
{
if (A[i]==A[j]) {count++; if (count > (N/2)) return i;}
}
}
return -1;
}
How about sorting the array first? You then compare middle and first and last elements of the sorted array to find the dominant element.
public Integer findDominator(int[] arr) {
int[] arrCopy = arr.clone();
Arrays.sort(arrCopy);
int length = arrCopy.length;
int middleIndx = (length - 1) /2;
int middleIdxRight;
int middleIdxLeft = middleIndx;
if (length % 2 == 0) {
middleIdxRight = middleIndx+1;
} else {
middleIdxRight = middleIndx;
}
if (arrCopy[0] == arrCopy[middleIdxRight]) {
return arrCopy[0];
}
if (arrCopy[middleIdxLeft] == arrCopy[length -1]) {
return arrCopy[middleIdxLeft];
}
return null;
}
C#
int dominant = 0;
int repeat = 0;
int? repeatedNr = null;
int maxLenght = A.Length;
int halfLenght = A.Length / 2;
int[] repeations = new int[A.Length];
for (int i = 0; i < A.Length; i++)
{
repeatedNr = A[i];
for (int j = 0; j < A.Length; j++)
{
if (repeatedNr == A[j])
{
repeations[i]++;
}
}
}
repeatedNr = null;
for (int i = 0; i < repeations.Length; i++)
{
if (repeations[i] > repeat)
{
repeat = repeations[i];
repeatedNr = A[i];
}
}
if (repeat > halfLenght)
dominant = int.Parse(repeatedNr.ToString());
class Program
{
static void Main(string[] args)
{
int []A= new int[] {3,6,2,6};
int[] B = new int[A.Length];
Program obj = new Program();
obj.ABC(A,B);
}
public int ABC(int []A, int []B)
{
int i,j;
int n= A.Length;
for (j=0; j<n ;j++)
{
int count = 1;
for (i = 0; i < n; i++)
{
if ((A[j]== A[i] && i!=j))
{
count++;
}
}
int finalCount = count;
B[j] = finalCount;// to store the no of times a number is repeated
}
// int finalCount = count / 2;
int finalCount1 = B.Max();// see which number occurred max times
if (finalCount1 > (n / 2))
{ Console.WriteLine(finalCount1); Console.ReadLine(); }
else
{ Console.WriteLine("no number found"); Console.ReadLine(); }
return -1;
}
}
In Ruby you can do something like
def dominant(a)
hash = {}
0.upto(a.length) do |index|
element = a[index]
hash[element] = (hash[element] ? hash[element] + 1 : 1)
end
res = hash.find{|k,v| v > a.length / 2}.first rescue nil
res ||= -1
return res
end
#Keith Randall solution is not working for {1,1,2,2,3,2,2}
his solution was:
element x;
int count ← 0;
For(i = 0 to n − 1) {
if(count == 0) { x ← A[i]; count++; }
else if (A[i] == x) count++;
else count−−;
}
Check if x is dominant element by scanning array A
I converted it into java as below:
int x = 0;
int count = 0;
for(int i = 0; i < (arr.length - 1); i++) {
if(count == 0) {
x = arr[i];
count++;
}
else if (arr[i] == x)
count++;
else count--;
}
return x;
Out put : 3
Expected: 2
This is my answer in Java: I store a count in seperate array which counts duplicates of each of the entries of the input array and then keeps a pointer to the array position that has the most duplicates. This is the dominator.
private static void dom(int[] a) {
int position = 0;
int max = 0;
int score = 0;
int counter = 0;
int[]result = new int[a.length];
for(int i = 0; i < a.length; i++){
score = 0;
for(int c = 0; c < a.length;c++){
if(a[i] == a[c] && c != i ){
score = score + 1;
result[i] = score;
if(result[i] > position){
position = i;
}
}
}
}
//This is just to facilitate the print function and MAX = the number of times that dominator number was found in the list.
for(int x = 0 ; x < result.length-1; x++){
if(result[x] > max){
max = result[x] + 1;
}
}
System.out.println(" The following number is the dominator " + a[position] + " it appears a total of " + max);
}