I am new to coding and struggling with a section in my code. I am at the part where i want to remove duplicate int values from my vector.
my duplicated vector contains: 1 1 2 1 4
my goal is to get a deduplicated vector: 1, 2, 4.
This is what I have so far, It also needs to be a rather simple solution. No pointers and fancy stuff as I still need to study those in the future.
for(int i = 0; i < duplicatedVector.size(); i++) {
int temp = duplicatedVector.at(i);
int counter = 0;
if(temp == duplicatedVector.at(i)) {
counter++;
if(counter > 1) {
deduplicatedVector.push_back(temp);
}
}
}
Could anyone tell me what I do wrong ? I genuinly am trying to iterate through the vector and delete duplicated int, in the given order.
Your algorithm is not well-enough thought out.
Break it up:
for each element of the original vector:
is it in the result vector?
yes: do nothing
no: add it to the result vector
You have your (1) loop, but the (2) part is confused. The result vector is not the same as the original vector, and is not to be indexed the same.
To determine whether an element is in a vector, you need a loop. Loop through your result vector to see if the element is in it. If you find it, it is, so break the inner loop. If you do not, you don't.
You can tell whether or not you found a duplicate by the final value of your inner loop index (the index into the result vector). If it equals result.size() then no duplicate was found.
Clearer variable naming might help as well. You are calling your original/source vector duplicatedVector, and your result vector deduplicatedVector. Even hasDuplicates and noDuplicates would be easier to mentally parse.
You could use a set since it eliminates duplicates:
#include <bits/stdc++.h>
using namespace std;
int main () {
vector<int> vec = vector<int>();
vector<int> dedupl = vector<int>();
vec.push_back(2);
vec.push_back(4);
vec.push_back(2);
vec.push_back(7);
vec.push_back(34);
vec.push_back(34);
set<int> mySet = set<int>();
for (int i = 0; i < vec.size(); i++) {
mySet.insert(vec[i]);
}
for (int elem : mySet) {
dedupl.push_back(elem);
}
for (int elem : dedupl) {
cout << elem << " ";
}
}
Related
The below question was asked in the atlassian company online test ,I don't have test cases , this is the below question I took from this link
find the number of ways you can form a string on size N, given an unlimited number of 0s and 1s. But
you cannot have D number of consecutive 0s and T number of consecutive 1s. N, D, T were given as inputs,
Please help me on this problem,any approach how to proceed with it
My approach for the above question is simply I applied recursion and tried for all possiblity and then I memoized it using hash map
But it seems to me there must be some combinatoric approach that can do this question in less time and space? for debugging purposes I am also printing the strings generated during recursion, if there is flaw in my approach please do tell me
#include <bits/stdc++.h>
using namespace std;
unordered_map<string,int>dp;
int recurse(int d,int t,int n,int oldd,int oldt,string s)
{
if(d<=0)
return 0;
if(t<=0)
return 0;
cout<<s<<"\n";
if(n==0&&d>0&&t>0)
return 1;
string h=to_string(d)+" "+to_string(t)+" "+to_string(n);
if(dp.find(h)!=dp.end())
return dp[h];
int ans=0;
ans+=recurse(d-1,oldt,n-1,oldd,oldt,s+'0')+recurse(oldd,t-1,n-1,oldd,oldt,s+'1');
return dp[h]=ans;
}
int main()
{
int n,d,t;
cin>>n>>d>>t;
dp.clear();
cout<<recurse(d,t,n,d,t,"")<<"\n";
return 0;
}
You are right, instead of generating strings, it is worth to consider combinatoric approach using dynamic programming (a kind of).
"Good" sequence of length K might end with 1..D-1 zeros or 1..T-1 of ones.
To make a good sequence of length K+1, you can add zero to all sequences except for D-1, and get 2..D-1 zeros for the first kind of precursors and 1 zero for the second kind
Similarly you can add one to all sequences of the first kind, and to all sequences of the second kind except for T-1, and get 1 one for the first kind of precursors and 2..T-1 ones for the second kind
Make two tables
Zeros[N][D] and Ones[N][T]
Fill the first row with zero counts, except for Zeros[1][1] = 1, Ones[1][1] = 1
Fill row by row using the rules above.
Zeros[K][1] = Sum(Ones[K-1][C=1..T-1])
for C in 2..D-1:
Zeros[K][C] = Zeros[K-1][C-1]
Ones[K][1] = Sum(Zeros[K-1][C=1..T-1])
for C in 2..T-1:
Ones[K][C] = Ones[K-1][C-1]
Result is sum of the last row in both tables.
Also note that you really need only two active rows of the table, so you can optimize size to Zeros[2][D] after debugging.
This can be solved using dynamic programming. I'll give a recursive solution to the same. It'll be similar to generating a binary string.
States will be:
i: The ith character that we need to insert to the string.
cnt: The number of consecutive characters before i
bit: The character which was repeated cnt times before i. Value of bit will be either 0 or 1.
Base case will: Return 1, when we reach n since we are starting from 0 and ending at n-1.
Define the size of dp array accordingly. The time complexity will be 2 x N x max(D,T)
#include<bits/stdc++.h>
using namespace std;
int dp[1000][1000][2];
int n, d, t;
int count(int i, int cnt, int bit) {
if (i == n) {
return 1;
}
int &ans = dp[i][cnt][bit];
if (ans != -1) return ans;
ans = 0;
if (bit == 0) {
ans += count(i+1, 1, 1);
if (cnt != d - 1) {
ans += count(i+1, cnt + 1, 0);
}
} else {
// bit == 1
ans += count(i+1, 1, 0);
if (cnt != t-1) {
ans += count(i+1, cnt + 1, 1);
}
}
return ans;
}
signed main() {
ios_base::sync_with_stdio(false), cin.tie(nullptr);
cin >> n >> d >> t;
memset(dp, -1, sizeof dp);
cout << count(0, 0, 0);
return 0;
}
The target is simple--find the longest substring without repeating characters,here is the code:
class Solution {
public:
int lengthOfLongestSubstring(string s) {
int ans = 0;
int dic[256];
memset(dic, -1, sizeof(dic));
int len = s.size();
int idx = -1;
for (int i = 0;i < len;i++) {
char c = s[i];
if (dic[c] > idx)
idx = dic[c];
ans = max(ans, i - idx);
dic[c] = i;
}
return ans;
}
};
From its concise expression,I think this is a high-performance method,and we can get that its Time Complexity is just O(n).But I'm confused about this method,though I came up with some examples to understand,can anyone give some tips or idea to me?
What it is doing is recording the position where each character was last seen.
As you step through, it takes each new encountered character and the length of non-repeat goes back at least as far as that last-seen, but for future indices can't go back further, as we have now seen a duplicate.
So we are maintaining in idx, the start index of the latest-seen highest-starting duplicate, which is the candidate for the start of the longest non-duplicating sequence.
I'm certain that the ans = max() code code be optimised slightly, as after encountering a new duplicate, you have to go forward at least ans chars from the start of that duplicate before ans can be improved again. You still need to do the rest of the work maintaining dic and idx, but you could avoid that particular test for ans for a few iterations. You would have to do a lot of unrolling to benefit, though.
We need to find the maximum element in an array which is also equal to product of two elements in the same array. For example [2,3,6,8] , here 6=2*3 so answer is 6.
My approach was to sort the array and followed by a two pointer method which checked whether the product exist for each element. This is o(nlog(n)) + O(n^2) = O(n^2) approach. Is there a faster way to this ?
There is a slight better solution with O(n * sqrt(n)) if you are allowed to use O(M) memory M = max number in A[i]
Use an array of size M to mark every number while you traverse them from smaller to bigger number.
For each number try all its factors and see if those were already present in the array map.
Here is a pseudo code for that:
#define M 1000000
int array_map[M+2];
int ans = -1;
sort(A,A+n);
for(i=0;i<n;i++) {
for(j=1;j<=sqrt(A[i]);j++) {
int num1 = j;
if(A[i]%num1==0) {
int num2 = A[i]/num1;
if(array_map[num1] && array_map[num2]) {
if(num1==num2) {
if(array_map[num1]>=2) ans = A[i];
} else {
ans = A[i];
}
}
}
}
array_map[A[i]]++;
}
There is an ever better approach if you know how to find all possible factors in log(M) this just becomes O(n*logM). You have to use sieve and backtracking for that
#JerryGoyal 's solution is correct. However, I think it can be optimized even further if instead of using B pointer, we use binary search to find the other factor of product if arr[c] is divisible by arr[a]. Here's the modification for his code:
for(c=n-1;(c>1)&& (max==-1);c--){ // loop through C
for(a=0;(a<c-1)&&(max==-1);a++){ // loop through A
if(arr[c]%arr[a]==0) // If arr[c] is divisible by arr[a]
{
if(binary_search(a+1, c-1, (arr[c]/arr[a]))) //#include<algorithm>
{
max = arr[c]; // if the other factor x of arr[c] is also in the array such that arr[c] = arr[a] * x
break;
}
}
}
}
I would have commented this on his solution, unfortunately I lack the reputation to do so.
Try this.
Written in c++
#include <vector>
#include <algorithm>
using namespace std;
int MaxElement(vector< int > Input)
{
sort(Input.begin(), Input.end());
int LargestElementOfInput = 0;
int i = 0;
while (i < Input.size() - 1)
{
if (LargestElementOfInput == Input[Input.size() - (i + 1)])
{
i++;
continue;
}
else
{
if (Input[i] != 0)
{
LargestElementOfInput = Input[Input.size() - (i + 1)];
int AllowedValue = LargestElementOfInput / Input[i];
int j = 0;
while (j < Input.size())
{
if (Input[j] > AllowedValue)
break;
else if (j == i)
{
j++;
continue;
}
else
{
int Product = Input[i] * Input[j++];
if (Product == LargestElementOfInput)
return Product;
}
}
}
i++;
}
}
return -1;
}
Once you have sorted the array, then you can use it to your advantage as below.
One improvement I can see - since you want to find the max element that meets the criteria,
Start from the right most element of the array. (8)
Divide that with the first element of the array. (8/2 = 4).
Now continue with the double pointer approach, till the element at second pointer is less than the value from the step 2 above or the match is found. (i.e., till second pointer value is < 4 or match is found).
If the match is found, then you got the max element.
Else, continue the loop with next highest element from the array. (6).
Efficient solution:
2 3 8 6
Sort the array
keep 3 pointers C, B and A.
Keeping C at the last and A at 0 index and B at 1st index.
traverse the array using pointers A and B till C and check if A*B=C exists or not.
If it exists then C is your answer.
Else, Move C a position back and traverse again keeping A at 0 and B at 1st index.
Keep repeating this till you get the sum or C reaches at 1st index.
Here's the complete solution:
int arr[] = new int[]{2, 3, 8, 6};
Arrays.sort(arr);
int n=arr.length;
int a,b,c,prod,max=-1;
for(c=n-1;(c>1)&& (max==-1);c--){ // loop through C
for(a=0;(a<c-1)&&(max==-1);a++){ // loop through A
for(b=a+1;b<c;b++){ // loop through B
prod=arr[a]*arr[b];
if(prod==arr[c]){
System.out.println("A: "+arr[a]+" B: "+arr[b]);
max=arr[c];
break;
}
if(prod>arr[c]){ // no need to go further
break;
}
}
}
}
System.out.println(max);
I came up with below solution where i am using one array list, and following one formula:
divisor(a or b) X quotient(b or a) = dividend(c)
Sort the array.
Put array into Collection Col.(ex. which has faster lookup, and maintains insertion order)
Have 2 pointer a,c.
keep c at last, and a at 0.
try to follow (divisor(a or b) X quotient(b or a) = dividend(c)).
Check if a is divisor of c, if yes then check for b in col.(a
If a is divisor and list has b, then c is the answer.
else increase a by 1, follow step 5, 6 till c-1.
if max not found then decrease c index, and follow the steps 4 and 5.
Check this C# solution:
-Loop through each element,
-loop and multiply each element with other elements,
-verify if the product exists in the array and is the max
private static int GetGreatest(int[] input)
{
int max = 0;
int p = 0; //product of pairs
//loop through the input array
for (int i = 0; i < input.Length; i++)
{
for (int j = i + 1; j < input.Length; j++)
{
p = input[i] * input[j];
if (p > max && Array.IndexOf(input, p) != -1)
{
max = p;
}
}
}
return max;
}
Time complexity O(n^2)
The definition of the problem is:
Given two strings, find the longest common substring.
Return the length of it.
I was solving this problem and I think I solved it with O(m*n) time complexity. However I don't know why when I look up the solution, it's all talking about the optimal solution being dynamic programming - http://www.geeksforgeeks.org/longest-common-substring/
Here's my solution, you can test it here: http://www.lintcode.com/en/problem/longest-common-substring/
int longestCommonSubstring(string &A, string &B) {
int ans = 0;
for (int i=0; i<A.length(); i++) {
int counter = 0;
int k = i;
for (int j=0; j<B.length() && k <A.length(); j++) {
if (A[k]!=B[j]) {
counter = 0;
k = i;
} else {
k++;
counter++;
ans = max(ans, counter);
}
}
}
return ans;
}
My idea is simple, start from the first position of string A and see what's the longest substring I can match with string B, then start from the second position of string A and see what's the longest substring I can match....
Is there something wrong with my solution? Or is it not O(m*n) complexity?
Good news: your algorithm is O(mn). Bad news: it doesn't work correctly.
Your inner loop is wrong: it's intended to find the longest initial substring of A[i:] in B, but it works like this:
j = 0
While j < len(B)
Match as much of A[i:] against B[j:]. Call it s.
Remember s if it's the longest so far found.
j += len(s)
This fails to find the longest match. For example, when A = "XXY" and B = "XXXY" and i=0 it'll find "XX" as the longest match instead of the complete match "XXY".
Here's a runnable version of your code (lightly transcribed into C) that shows the faulty result:
#include <string.h>
#include <stdio.h>
int lcs(const char* A, const char* B) {
int al = strlen(A);
int bl = strlen(B);
int ans = 0;
for (int i=0; i<al; i++) {
int counter = 0;
int k = i;
for (int j=0; j<bl && k<al; j++) {
if (A[k]!=B[j]) {
counter = 0;
k = i;
} else {
k++;
counter++;
if (counter >= ans) ans = counter;
}
}
}
return ans;
}
int main(int argc, char**argv) {
printf("%d\n", lcs("XXY", "XXXY"));
return 0;
}
Running this program outputs "2".
Your solution is O(nm) complexity and if you look compare the structure to the provided algorithm its the exact same; however, yours does not memoize.
One advantage that the dynamic algorithm provided in the link has is that in the same complexity class time it can recall different substring lengths in O(1); otherwise, it looks good to me.
This is a kind of thing will happen from time to time because storing subspace solutions will not always result in a better run time (on first call) and result in the same complexity class runtime instead (eg. try to compute the nth Fibonacci number with a dynamic solution and compare that to a tail recursive solution. Note that in this case like your case, after the array is filled the first time, its faster to return an answer each successive call.
public void DoSomething(byte[] array, byte[] array2, int start, int counter)
{
int length = array.Length;
int index = 0;
while (count >= needleLen)
{
index = Array.IndexOf(array, array2[0], start, count - length + 1);
int i = 0;
int p = 0;
for (i = 0, p = index; i < length; i++, p++)
{
if (array[p] != array2[i])
{
break;
}
}
Given that your for loop appears to be using a loop body dependent on ordering, it's most likely not a candidate for parallelization.
However, you aren't showing the "work" involved here, so it's difficult to tell what it's doing. Since the loop relies on both i and p, and it appears that they would vary independently, it's unlikely to be rewritten using a simple Parallel.For without reworking or rethinking your algorithm.
In order for a loop body to be a good candidate for parallelization, it typically needs to be order independent, and have no ordering constraints. The fact that you're basing your loop on two independent variables suggests that these requirements are not valid in this algorithm.