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Creating random numbers with no duplicates
(20 answers)
Closed 1 year ago.
This is probably already asked, but it is a little difficult for me to understand. I created a for loop to add random integers into my array, but when the integer is already in the array, restart the loop. But I keep on getting the same integers into the array + when there already is a duplicate, the array size increases. Does anyone know what I'm doing wrong?
Random r = new Random();
int[] tes = new int[5];
for (int i = 0; i < tes.length; i++) {
int q = r.nextInt(10);
for (int j = 0; j < i; j++) {
if (q == tes[j]){
i=i-1;
}
}
tes[i] = q;
System.out.println(tes[i]);
}
and the output:
If you want a collection without duplicates you should use a Set:
Random r = new Random();
int desirableSize = 5;
Set<Integer> uniques = new HashSet<>(desirableSize);
while(uniques.size() < desirableSize){
uniques.add(r.nextInt(10));
}
System.out.println(uniques);
The add method already ensures that a value is not added if it already exist on the set.
boolean add(E e)
Adds the specified element to this set if it is not already present (optional operation).
I have used HashSet, however if the insertion order is important for you, use instead LinkedHashSet:
As pjs have pointed out the aforementioned approach is good when:
desirableSize is much less than the pool size, but if the
desirableSize is a substantial proportion of pool size you're better
off shuffling the pool and selecting the first desirableSize elements.
Something as follows:
int start = 0;
int end = 10;
int size = 5;
List<Integer> collect = IntStream.rangeClosed(start, end)
.boxed()
.limit(size)
.collect(Collectors.toList());
Collections.shuffle(collect);
System.out.println(collect);
The rational is the following (quoting pjs):
With rejection-based schemes such as repeated attempts to add to a
set, the expected number of iterations is O(poolsize *
log(desirableSize)) with O(desirableSize) storage for the set.
Shuffling is O(poolsize) but requires O(poolsize) storage for the
shuffle. As desirableSize -> poolsize, shuffling wins on expected
iterations and becomes competitive on storage. With partial shuffling
implementations, the number of iterations for shuffling is
O(desirableSize) although the storage remains the same.
Or more informally, the higher it is the unique finite set of numbers that will be pickup from a finite set of possible numbers, the more desirable it is to use the second approach.
For instance, if one generates numbers from 0 to 1000 and is only interested in 5 numbers, since the probability of picking randomly the same numbers is lower, one is better off with the first approach. However, if you would be (instead) interested in 800 numbers, then one would be better off generating and shuffling the 1000 numbers, and extracting the 800 unique values from them.
Memory-wise the first approach is better then second approach, however performance-wise it depends in the context as we have already described.
i dont see a problem.
Your System.out.println(tes[i]); is in loop
your array has only following ints: 5,9,2,7,1
make println in own loop
for (int i = 0; i < tes.length; i++) {
System.out.println(tes[i]);
}
because you make i=i-1; one value is printed many times
I managed to solve it in a different way:
List<Integer> tes = new ArrayList<>(5);
Random r = new Random();
for (int i = 0; i < 5; i++) {
int testNummer = r.nextInt(10);
if(!tes.contains(testNummer)) {
tes.add(testNummer);
System.out.println(testNummer);
}else{
i=i-1;
}
}
this way is more efficient, I have noticed.
Some logic problem
Increment i variable when you store value in array and don't decrement i variable just break inner loop when found duplicate.
when duplicate found then restart outer loop. use if else condition for that
try below code and for simple understanding i have changed outer loop in while
int i = 0;
while(i<5)
{
int q = r.nextInt(10);
System.out.println("random value generated"+ q );
int j=0;
for (;j < i; j++)
{
if (q == tes[j])
{
System.out.println("duplicate value found"+ q );
break;
}
}
if(j!=i)
{
continue;
}
else
{
if(j==i)
{
tes[i] = q;
i=i+1;
}
}
System.out.println("value at "+ tes[i]);
}
If you want an easy way to generate unique values you can do it with a stream.
Random r = new Random();
int minVal = 1;
int upperBound = 20;
int count = 10;
As long as count is less than upperBound - minVal it will finish without duplicates. For very large counts with the appropriate range, it may take some time.
int[] unique = r.ints(minVal, upperBound).distinct().limit(count).toArray();
System.out.println(Arrays.toString(unique));
Prints something like this.
[14, 1, 7, 13, 5, 16, 2, 8, 12, 4]
An easy way to generate random numbers of a fixed range is to simply shuffle the array.
Integer[] vals = new Integer[20];
for (int i = 0; i < vals.length; i++) {
vals[i] = i+1;
}
// Object array will be shuffle since it backs up the list.
Collections.shuffle(Arrays.asList(vals));
System.out.println(Arrays.toString(vals));
Prints something like
[7, 20, 5, 10, 17, 18, 3, 13, 11, 1, 2, 8, 4, 9, 19, 12, 15, 16, 6, 14]
excuse me for the confusing title, I need to implement an algorithm which can be simplified as the following:
given an array of integers, and the number of merges needed (denoted as k), return the maximum min value of the merged array, a merge can only happen with adjacent elements.
E.g. array = [3,2,8,2,9], k = 2
The maximum min value of the array after two merges is 5, and the merged array is [5, 10, 9]. In this example, we need to merge elements 3 & 2 and 8 & 2.
Any other merge strategies will yield min val that is smaller or equal to 5, e.g.:
[5,8,11], [3,10,11], [13,2,9](merged elements can be merged again)
What is the best data structure to represent the data and what is an efficient algorithm to address the problem? As far as I can think of, a greedy algorithm needs to be applied where a merge needs to happen with the current min value of the array and one of its smaller neighboring element.
Edit: I just realized that greedy algorithm might not apply, sorry for the misleading comment, if it doesn't distinguish between merging with left or right elements, this will generate the wrong answer. Take this as an example, given an array = [4,5,3,5], and we need to remove 2 elements.
With greedy, [4,5,3,5] -> [4,8,5] -> [12,5], so the answer is 5; however the correct answer should be 8 with the following merge sequence:
[4,5,3,5] -> [4,5,8] -> [9,8]
ValPosFrom is a simple class that stores those things, from being the place to merge from . you can get non deterministic results from things like List = 3,2,6,3,2 and k=1 it will merge one of the 2 mins to 5 but it doesn't matter which one. it converges when all of any positions neighbors values are unique.
private static List<Integer> merge(List<Integer> things, int merges) {
List<Integer> result = new ArrayList<>(things);
for (int i = 0; i < merges; i++) {
int min = Integer.MAX_VALUE;
List<Integer> positions = new ArrayList<>();
for (int j = 0; j < result.size(); j++) {
if (result.get(j) < min) {
positions.clear();
positions.add(j);
min = result.get(j);
} else if (result.get(j) == min) {
positions.add(j);
}
}
List<ValPosFrom> neighbors = new ArrayList<>();
positions.forEach(p -> {
if (p - 1 >= 0) {
neighbors.add(new ValPosFrom(result.get(p - 1), p - 1, p));
}
if (p + 1 < result.size()) {
neighbors.add(new ValPosFrom(result.get(p + 1), p + 1, p));
}
});
ValPosFrom vpf = Collections.min(neighbors, Comparator.comparingInt(v -> v.val));
result.set(vpf.pos, result.get(vpf.pos) + result.get(vpf.from));
result.remove(vpf.from);
}
return result;
}
have following problem. suppose i have an array number[n] , i want search multiple number , for example i want to search 12, 45 ,1 ,6,8,5, and if every number present array then i can get favorable result. so there is one way , i just pick one element like 7
if it is present in array number[n], then can get inside the loop , and again initialize another loop and check that if second number is in the number[n] , and so on, so here i need same number of loop as the number of searching numbers. so is there is another way to deal with such problem. because it will running time will be polynomial.
here is my code:
import java.util.Scanner;
class Number {
boolean check(int[] num)
{
for (int i = 0; i < 5; i++) {
if (num[i] == 7) {
for (j = 0; j < 5; j++) {
if (num[j] == 8) {
for (int k = 0; k < 5; k++) {
if (num[k] == 9) {
return true;
}
else
continue;
}
} else
continue;
}
} else
return false;
}
}
public static void main(string [] args)
{
Number obj1 = new Number();
Scanner input = new Scanner(System.in);
int [] num =new int[5];
for(int i=0;i<5;i++)
num[i] =input.nextInt();
boolean get ;
get = obj1.check(num []);
System.out.print(response);
}
}
You could do something like this.
public static boolean allFoundIn( int[] toSearch, int... numbers )
Set numbersSet = new HashSet(Arrays.asList(numbers));
numbersSet.removeAll(Arrays.asList(toSearch));
return numbersSet.isEmpty();
}
Then in your main, just call
allFoundIn(num, 7, 8, 9);
which will return true if 7, 8 and 9 are all found in the array num.
If you want a sub-polynomial solution then there are a few possibilities.
1) Sort both lists, then loop like so (pseudocode)
toFind = <first element of listToFind>
for i in listToSearch:
if i == toFind:
if toFind is last element of listToFind:
return true
toFind = next element of listToFind
else if i > toFind:
return false
2) Put all the elements of the list to search in a HashSet. Then loop over the elements you want to find and see if it's in the HashSet. If they all are then they're all in the list. If not then they're not all in the list. HashSet has fast lookup, so it will likely be better than polynomial time.
and since I was already beaten to the punch for 2, I'll stop thinking of alternatives and post.
Yes, you can dramatically reduce the number of passes. Firstly though, don't hard code you search numbers like that with a separate loop for each. Create one array to store the numbers being searched for and one containing the numbers being searched. Sort each in the same direction, eg ascending order. Create two ints to act as counters, one for each array. Now use a while loop to compare the numbers in each array at the positions the counters are at.
How you advance the counters depends on how the numbers compare. If the number in the array of ones being searched for is larger than the one being searched, you advance the one being searched. If the other way around you advance the one being searched and if equal you advance both and record the match. Keep going until the end of one array is reached.
Using this method you only traverse the arrays a maximum of one time. I'd write example code but I'm typing on my phone!
This solution is not the fastest since it does a binary search for every number. Additionally, it has to be sorted first. It would be better to put all your source numbers into a hash set, like in David Wallace's solution. Then each search time is constant instead of depending on the size of your source array.
boolean check(int[] num) {
int[] toSearch = new int[] { 12, 45, 1, 6, 8, 5 };
for (int search : toSearch) {
if (Arrays.binarySearch(num, search) == -1) {
return false;
}
}
return true;
}
If you want to use a hash set, you could do it like this:
boolean check(Integer[] num) {
HashSet<Integer> numSet = new HashSet<>(Arrays.asList(num));
int[] toSearch = new int[] { 12, 45, 1, 6, 8, 5 };
for (int search : toSearch) {
if (!numSet.Contains(search)) {
return false;
}
}
return true;
}
I have been asked this question in a job interview and I have been wondering about the right answer.
You have an array of numbers from 0 to n-1, one of the numbers is removed, and replaced with a number already in the array which makes a duplicate of that number. How can we detect this duplicate in time O(n)?
For example, an array of 4,1,2,3 would become 4,1,2,2.
The easy solution of time O(n2) is to use a nested loop to look for the duplicate of each element.
This can be done in O(n) time and O(1) space.
(The algorithm only works because the numbers are consecutive integers in a known range):
In a single pass through the vector, compute the sum of all the numbers, and the sum of the squares of all the numbers.
Subtract the sum of all the numbers from N(N-1)/2. Call this A.
Subtract the sum of the squares from N(N-1)(2N-1)/6. Divide this by A. Call the result B.
The number which was removed is (B + A)/2 and the number it was replaced with is (B - A)/2.
Example:
The vector is [0, 1, 1, 2, 3, 5]:
N = 6
Sum of the vector is 0 + 1 + 1 + 2 + 3 + 5 = 12. N(N-1)/2 is 15. A = 3.
Sum of the squares is 0 + 1 + 1 + 4 + 9 + 25 = 40. N(N-1)(2N-1)/6 is 55. B = (55 - 40)/A = 5.
The number which was removed is (5 + 3) / 2 = 4.
The number it was replaced by is (5 - 3) / 2 = 1.
Why it works:
The sum of the original vector [0, ..., N-1] is N(N-1)/2. Suppose the value a was removed and replaced by b. Now the sum of the modified vector will be N(N-1)/2 + b - a. If we subtract the sum of the modified vector from N(N-1)/2 we get a - b. So A = a - b.
Similarly, the sum of the squares of the original vector is N(N-1)(2N-1)/6. The sum of the squares of the modified vector is N(N-1)(2N-1)/6 + b2 - a2. Subtracting the sum of the squares of the modified vector from the original sum gives a2 - b2, which is the same as (a+b)(a-b). So if we divide it by a - b (i.e., A), we get B = a + b.
Now B + A = a + b + a - b = 2a and B - A = a + b - (a - b) = 2b.
We have the original array int A[N]; Create a second array bool B[N] too, of type bool=false. Iterate the first array and set B[A[i]]=true if was false, else bing!
You can do it in O(N) time without any extra space. Here is how the algorithm works :
Iterate through array in the following manner :
For each element encountered, set its corresponding index value to negative.
Eg : if you find a[0] = 2. Got to a[2] and negate the value.
By doing this you flag it to be encountered. Since you know you cannot have negative numbers, you also know that you are the one who negated it.
Check if index corresponding to the value is already flagged negative, if yes you get the duplicated element. Eg : if a[0]=2 , go to a[2] and check if it is negative.
Lets say you have following array :
int a[] = {2,1,2,3,4};
After first element your array will be :
int a[] = {2,1,-2,3,4};
After second element your array will be :
int a[] = {2,-1,-2,3,4};
When you reach third element you go to a[2] and see its already negative. You get the duplicate.
Scan the array 3 times:
XOR together all the array elements -> A. XOR together all the numbers from 0 to N-1 -> B. Now A XOR B = X XOR D, where X is the removed element, and D is the duplicate element.
Choose any non-zero bit in A XOR B. XOR together all the array elements where this bit is set -> A1. XOR together all the numbers from 0 to N-1 where this bit is set -> B1. Now either A1 XOR B1 = X or A1 XOR B1 = D.
Scan the array once more and try to find A1 XOR B1. If it is found, this is the duplicate element. If not, the duplicate element is A XOR B XOR A1 XOR B1.
Use a HashSet to hold all numbers already seen. It operates in (amortized) O(1) time, so the total is O(N).
I suggest using a BitSet. We know N is small enough for array indexing, so the BitSet will be of reasonable size.
For each element of the array, check the bit corresponding to its value. If it is already set, that is the duplicate. If not, set the bit.
#rici is right about the time and space usage: "This can be done in O(n) time and O(1) space."
However, the question can be expanded to broader requirement: it's not necessary that there is only one duplicate number, and numbers might not be consecutive.
OJ puts it this way here:
(note 3 apparently can be narrowed)
Given an array nums containing n + 1 integers where each integer is between 1 and n (inclusive), prove that at least one duplicate number must exist. Assume that there is only one duplicate number, find the duplicate one.
Note:
You must not modify the array (assume the array is read only).
You must use only constant, O(1) extra space.
Your runtime complexity should be less than O(n2).
There is only one duplicate number in the array, but it could be repeated more than once.
The question is very well explained and answered here by Keith Schwarz, using Floyd's cycle-finding algorithm:
The main trick we need to use to solve this problem is to notice that because we have an array of n elements ranging from 0 to n - 2, we can think of the array as defining a function f from the set {0, 1, ..., n - 1} onto itself. This function is defined by f(i) = A[i]. Given this setup, a duplicated value corresponds to a pair of indices i != j such that f(i) = f(j). Our challenge, therefore, is to find this pair (i, j). Once we have it, we can easily find the duplicated value by just picking f(i) = A[i].
But how are we to find this repeated value? It turns out that this is a well-studied problem in computer science called cycle detection. The general form of the problem is as follows. We are given a function f. Define the sequence x_i as
x_0 = k (for some k)
x_1 = f(x_0)
x_2 = f(f(x_0))
...
x_{n+1} = f(x_n)
Assuming that f maps from a domain into itself, this function will have one of three forms. First, if the domain is infinite, then the sequence could be infinitely long and nonrepeating. For example, the function f(n) = n + 1 on the integers has this property - no number is ever duplicated. Second, the sequence could be a closed loop, which means that there is some i so that x_0 = x_i. In this case, the sequence cycles through some fixed set of values indefinitely. Finally, the sequence could be "rho-shaped." In this case, the sequence looks something like this:
x_0 -> x_1 -> ... x_k -> x_{k+1} ... -> x_{k+j}
^ |
| |
+-----------------------+
That is, the sequence begins with a chain of elements that enters a cycle, then cycles around indefinitely. We'll denote the first element of the cycle that is reached in the sequence the "entry" of the cycle.
An python implementation can also be found here:
def findDuplicate(self, nums):
# The "tortoise and hare" step. We start at the end of the array and try
# to find an intersection point in the cycle.
slow = 0
fast = 0
# Keep advancing 'slow' by one step and 'fast' by two steps until they
# meet inside the loop.
while True:
slow = nums[slow]
fast = nums[nums[fast]]
if slow == fast:
break
# Start up another pointer from the end of the array and march it forward
# until it hits the pointer inside the array.
finder = 0
while True:
slow = nums[slow]
finder = nums[finder]
# If the two hit, the intersection index is the duplicate element.
if slow == finder:
return slow
Use hashtable. Including an element in a hashtable is O(1).
One working solution:
asume number are integers
create an array of [0 .. N]
int[] counter = new int[N];
Then iterate read and increment the counter:
if (counter[val] >0) {
// duplicate
} else {
counter[val]++;
}
This can be done in O(n) time and O(1) space.
Without modifying the input array
The idea is similar to finding the starting node of a loop in a linked list.
Maintain two pointers: fast and slow
slow = a[0]
fast = a[a[0]]
loop till slow != fast
Once we find the loop (slow == fast)
Reset slow back to zero
slow = 0
find the starting node
while(slow != fast){
slow = a[slow];
fast = a[fast];
}
slow is your duplicate number.
Here's a Java implementation:
class Solution {
public int findDuplicate(int[] nums) {
if(nums.length <= 1) return -1;
int slow = nums[0], fast = nums[nums[0]]; //slow = head.next, fast = head.next.next
while(slow != fast){ //check for loop
slow = nums[slow];
fast = nums[nums[fast]];
}
if(slow != fast) return -1;
slow = 0; //reset one pointer
while(slow != fast){ //find starting point of loop
slow = nums[slow];
fast = nums[fast];
}
return slow;
}
}
This is an alternative solution in O(n) time and O(1) space. It is similar to rici's. I find it a bit easier to understand but, in practice, it will overflow faster.
Let X be the missing number and R be the repeated number.
We can assume the numbers are from [1..n], i.e. zero does not appear. In fact, while looping through the array, we can test if zero was found and return immediately if not.
Now consider:
sum(A) = n (n + 1) / 2 - X + R
product(A) = n! R / X
where product(A) is the product of all element in A skipping the zero. We have two equations in two unknowns from which X and R can be derived algebraically.
Edit: by popular demand, here is a worked-out example:
Let's set:
S = sum(A) - n (n + 1) / 2
P = n! / product(A)
Then our equations become:
R - X = S
X = R P
which can be solved to:
R = S / (1 - P)
X = P R = P S / (1 - P)
Example:
A = [0 1 2 2 4]
n = A.length - 1 = 4
S = (1 + 2 + 2 + 4) - 4 * 5 / 2 = -1
P = 4! / (1 * 2 * 2 * 4) = 3 / 2
R = -1 / (1 - 3/2) = -1 / -1/2 = 2
X = 3/2 * 2 = 3
You could proceed as follows:
sort your array by using a Linear-time sorting algorithm (e.g. Counting sort) - O(N)
scan the sorted array and stop as soon as two consecutive elements are equal - O(N)
public class FindDuplicate {
public static void main(String[] args) {
// assume the array is sorted, otherwise first we have to sort it.
// time efficiency is o(n)
int elementData[] = new int[] { 1, 2, 3, 3, 4, 5, 6, 8, 8 };
int count = 1;
int element1;
int element2;
for (int i = 0; i < elementData.length - 1; i++) {
element1 = elementData[i];
element2 = elementData[count];
count++;
if (element1 == element2) {
System.out.println(element2);
}
}
}
}
public void duplicateNumberInArray {
int a[] = new int[10];
Scanner inp = new Scanner(System.in);
for(int i=1;i<=5;i++){
System.out.println("enter no. ");
a[i] = inp.nextInt();
}
Set<Integer> st = new HashSet<Integer>();
Set<Integer> s = new HashSet<Integer>();
for(int i=1;i<=5;i++){
if(!st.add(a[i])){
s.add(a[i]);
}
}
Iterator<Integer> itr = s.iterator();
System.out.println("Duplicate numbers are");
while(itr.hasNext()){
System.out.println(itr.next());
}
}
First of all creating an array of integer using Scanner class. Then iterating a loop through the numbers and checking if the number can be added to set (Numbers can be added to set only when that particular number should not be in set already, means set does not allow duplicate no. to add and return a boolean vale FALSE on adding duplicate value).If no. cannot be added means it is duplicate so add that duplicate number into another set, so that we can print later. Please note onething that we are adding the duplicate number into a set because it might be possible that duplicate number might be repeated several times, hence add it only once.At last we are printing set using Iterator.
//This is similar to the HashSet approach but uses only one data structure:
int[] a = { 1, 4, 6, 7, 4, 6, 5, 22, 33, 44, 11, 5 };
LinkedHashMap<Integer, Integer> map = new LinkedHashMap<Integer, Integer>();
for (int i : a) {
map.put(i, map.containsKey(i) ? (map.get(i)) + 1 : 1);
}
Set<Entry<Integer, Integer>> es = map.entrySet();
Iterator<Entry<Integer, Integer>> it = es.iterator();
while (it.hasNext()) {
Entry<Integer, Integer> e = it.next();
if (e.getValue() > 1) {
System.out.println("Dupe " + e.getKey());
}
}
We can do using hashMap efficiently:
Integer[] a = {1,2,3,4,0,1,5,2,1,1,1,};
HashMap<Integer,Integer> map = new HashMap<Integer,Integer>();
for(int x : a)
{
if (map.containsKey(x)) map.put(x,map.get(x)+1);
else map.put(x,1);
}
Integer [] keys = map.keySet().toArray(new Integer[map.size()]);
for(int x : keys)
{
if(map.get(x)!=1)
{
System.out.println(x+" repeats : "+map.get(x));
}
}
This program is based on c# and if you want to do this program using another programming language you have to firstly change an array in accending order and compare the first element to the second element.If it is equal then repeated number found.Program is
int[] array=new int[]{1,2,3,4,5,6,7,8,9,4};
Array.Sort(array);
for(int a=0;a<array.Length-1;a++)
{
if(array[a]==array[a+1]
{
Console.WriteLine("This {0} element is repeated",array[a]);
}
}
Console.WriteLine("Not repeated number in array");
sort the array O(n ln n)
using the sliding window trick to traverse the array O(n)
Space is O(1)
Arrays.sort(input);
for(int i = 0, j = 1; j < input.length ; j++, i++){
if( input[i] == input[j]){
System.out.println(input[i]);
while(j < input.length && input[i] == input[j]) j++;
i = j - 1;
}
}
Test case int[] { 1, 2, 3, 7, 7, 8, 3, 5, 7, 1, 2, 7 }
output 1, 2, 3, 7
Traverse through the array and check the sign of array[abs(array[i])], if positive make it as negative and if it is negative then print it, as follows:
import static java.lang.Math.abs;
public class FindRepeatedNumber {
private static void findRepeatedNumber(int arr[]) {
int i;
for (i = 0; i < arr.length; i++) {
if (arr[abs(arr[i])] > 0)
arr[abs(arr[i])] = -arr[abs(arr[i])];
else {
System.out.print(abs(arr[i]) + ",");
}
}
}
public static void main(String[] args) {
int arr[] = { 4, 2, 4, 5, 2, 3, 1 };
findRepeatedNumber(arr);
}
}
Reference: http://www.geeksforgeeks.org/find-duplicates-in-on-time-and-constant-extra-space/
As described,
You have an array of numbers from 0 to n-1, one of the numbers is
removed, and replaced with a number already in the array which makes a
duplicate of that number.
I'm assuming elements in the array are sorted except the duplicate entry. If this is the scenario , we can achieve the goal easily as below :
public static void main(String[] args) {
//int arr[] = { 0, 1, 2, 2, 3 };
int arr[] = { 1, 2, 3, 4, 3, 6 };
int len = arr.length;
int iMax = arr[0];
for (int i = 1; i < len; i++) {
iMax = Math.max(iMax, arr[i]);
if (arr[i] < iMax) {
System.out.println(arr[i]);
break;
}else if(arr[i+1] <= iMax) {
System.out.println(arr[i+1]);
break;
}
}
}
O(n) time and O(1) space ;please share your thoughts.
Here is the simple solution with hashmap in O(n) time.
#include<iostream>
#include<map>
using namespace std;
int main()
{
int a[]={1,3,2,7,5,1,8,3,6,10};
map<int,int> mp;
for(int i=0;i<10;i++){
if(mp.find(a[i]) == mp.end())
mp.insert({a[i],1});
else
mp[a[i]]++;
}
for(auto i=mp.begin();i!=mp.end();++i){
if(i->second > 1)
cout<<i->first<<" ";
}
}
int[] a = {5, 6, 8, 9, 3, 4, 2, 9 };
int[] b = {5, 6, 8, 9, 3, 6, 1, 9 };
for (int i = 0; i < a.Length; i++)
{
if (a[i] != b[i])
{
Console.Write("Original Array manipulated at position {0} + "\t\n"
+ "and the element is {1} replaced by {2} ", i,
a[i],b[i] + "\t\n" );
break;
}
}
Console.Read();
///use break if want to check only one manipulation in original array.
///If want to check more then one manipulation in original array, remove break
This video If Programming Was An Anime is too fun not to share. It is the same problem and the video has the answers:
Sorting
Creating a hashmap/dictionary.
Creating an array. (Though this is partially skipped over.)
Using the Tortoise and Hare Algorithm.
Note: This problem is more of a trivia problem than it is real world. Any solution beyond a hashmap is premature optimization, except in rare limited ram situations, like embedded programming.
Furthermore, when is the last time you've seen in the real world an array where all of the variables within the array fit within the size of the array? Eg, if the data in the array is bytes (0-255) when do you have an array 256 elements or larger without nulls or inf within it, and you need to find a duplicate number? This scenario is so rare you will probably never get to use this trick in your entire career.
Because it is a trivia problem and is not real world the question, I'd be cautious accepting an offer from a company that asks trivia questions like this, because people will pass the interview by sheer luck instead of skill. This implies the devs there are not guaranteed to be skilled, which unless you're okay teaching your seniors skills, you might have a bad time.
int a[] = {2,1,2,3,4};
int b[] = {0};
for(int i = 0; i < a.size; i++)
{
if(a[i] == a[i+1])
{
//duplicate found
//copy it to second array
b[i] = a[i];
}
}
I'm trying to figure out how to modify the n greatest elements of an array without modifying their position. For example, suppose I have an array of ints {5, 2, 3, 4, 8, 9, 1, 3};
I want to add 1 to the two greatest elements, making the array {5, 2, 3, 4, 9, 10, 1, 3}.
All of the methods I can think of to go about doing this end up feeling clunky and unintuitive when I try to implement them, signaling to me that I'm not thinking about it correctly. For example, I could use a TreeMap with the values of the array as keys and their indices as values to find the greatest values, modify them, and then throw them back into the array, but then I would have have to implement my own Comparator to sort the TreeMap in reverse order(unless there's an easier way I'm not aware of?). I was also considering copying the contents of the array into a list, iterating through n times, each time finding the greatest element and its index, putting the modified greatest element back into the array at that index, removing the element from the list, and repeat, but that feels sloppy and inefficient to me.
Any suggestions as to how to approach this type of problem?
The simplest thing would be to scan your array, and store the indices of the n highest values. Increment the values of those elements.
This is going to be O(n) performance, and I don't think any fancier methods can beat that.
edit to add: you can sort the array in place in O(n) at best, in which case you can get the n highest values very quickly, but the requirement is to not change position of the elements, so you'd have to start with a copy of the array if you wanted to do that (or preserve ordering information so you could put everything back afterward).
You might be over engineering the solution to this problem: scan the array, from beginning to end, and mark the two largest elements. Return to the two greatest elements and add 1 to it. The solution shouldn't be longer than 10 lines.
Loop over the array and keep track of the indices and values of the two largest items
a. Initialize the tracker with -1 for an index and MIN_INT for a value or the first two values of the array
b. At each step of the loop compare the current value against the two tracker values and update if necessary
Increment the two items
Any algorithm you choose should be O(n) for this. Sorting and n passes are way overkill.
Find the nth largest element (call it K) using techniques here and here (can be done in linear time), then go through the array modifying all elements >= K.
i would do something like this
int[] indices = new int[2];
int[] maximas = new int[] { 0, 0 };
int[] data = new int[] { 3, 4, 5, 1, 9 };
for (int i = 0; i < 5; ++i)
{
if (data[i] > maximas[1])
{
maximas[0] = maximas[1];
maximas[1] = data[i];
indices[0] = indices[1];
indices[1] = i;
}
else if (data[i] > maximas[0])
{
maximas[0] = data[i];
indices[0] = i;
}
}
didn't test it, but I think it should work :)
I have tought a bit about this but I cannot achieve more than worstcase:
O( n + (m-n) * n ) : (m > n)
best case:
O(m) : (m <= n)
where m = number of values, n = number of greatest value to search
This is the implementation in C#, but you can easily adapt to java:
int n = 3;
List<int> values = new List<int> {1,1,1,8,7,6,5};
List<int> greatestIndexes = new List<int>();
for (int i = 0; i < values.Count; i++) {
if (greatestIndexes.Count < n)
{
greatestIndexes.Add(i);
}
else {
int minIndex = -1, minValue = int.MaxValue;
for (int j = 0; j < n; j++)
{
if (values[greatestIndexes[j]] < values[i]) {
if (minValue > values[greatestIndexes[j]])
{
minValue = values[greatestIndexes[j]];
minIndex = j;
}
}
}
if (minIndex != -1)
{
greatestIndexes.RemoveAt(minIndex);
greatestIndexes.Add(i);
}
}
}
foreach (var i in greatestIndexes) {
Console.WriteLine(values[i]);
}
Output:
8
7
6