The problem is fairly simple and straight .However i cannot solve it exclusively using dp knapsack style . I have solution for that but since the number of coins in each denomination here is limited (in this question it's )it's creating a problem . I want to arrive at a 2d recurrence that i can use to implement the knapsack .
My actual solution which runs fine goes below :
#include<iostream>
using namespace std ;
int main ()
{ int flag ;
int N,i ;
int sum ;
int counter ;
while (cin >> N >>sum )
{
counter = 0;
flag= 0 ;
int count =0;
for( i = N ; i>=1;i--){
count += i ;
counter++;
if (count >sum){
count-=i ;
counter -- ;
}
if(count == sum){
flag = 1 ;
break ;
}
}
if (flag==1)
cout << counter<<"\n" ;
else cout <<-1<<"\n" ;
}
return 0 ;
}
Dynamic programming solution is not required for the problem as the constraint are quite high.A simple greedy approach would work fine.
The algorithm works as follows:
If the sum of all the values form 1 to n is less than m then you cannot pay m coins because even after using all the n coins you have money remaining to be paid.
If the sum of all the values form 1 to n is greater than or equal to m then you can definitely pay because you have enough coins.
Since you have to minimize the number of coins to be given you consecutively pick coins that have the maximum value until your m become zero and you need to only keep track of number of coins that you have picked.
Below is the code that implements the above algorithm
#include <bits/stdc++.h>
using namespace std;
int main() {
int n, m;
cin >> n >> m;
if (m > (n * (n + 1) / 2)) {
//if sum of all coins form 1 to n is less than m
cout << "-1";
} else {
int cnt = 0;
while (m != 0) {
if (n >= m) {
m = 0;
} else {
m -= n;
--n;
}
++cnt;
}
cout << cnt;
}
return 0;
}
Related
You are given a string S initially and some Q queries. For each query you will have 2 integers L and R. For each query, you have to perform the following operations:
Arrange the letters from L to R inclusive to make a Palindrome. If you can form many such palindromes, then take the one that is lexicographically minimum. Ignore the query if no palindrome is possible on rearranging the letters.
You have to find the final string after all the queries.
Constraints:
1 <= length(S) <= 10^5
1 <= Q <= 10^5
1<= L <= R <= length(S)
Sample Input :
4
mmcs 1
1 3
Sample Output:
mcms
Explanation:
The initial string is mmcs, there is 1 query which asks to make a palindrome from 1 3, so the palindrome will be mcm. Therefore the string will mcms.
If each query takes O(N) time, the overall time complexity would be O(NQ) which will give TLE. So each query should take around O(logn) time. But I am not able to think of anything which will solve this question. I think since we only need to find the final string rather than what every query result into, I guess there must be some other way to approach this question. Can anybody help me?
We can solve this problem using Lazy Segment Tree with range updates.
We will make Segment Tree for each character , so there will be a total of 26 segment trees.
In each node of segment tree we will store the frequency of that character over the range of that node and also keep a track of whether to update that range or not.
So for each query do the following ->
We are given a range L to R
So first we will find frequency of each character over L to R (this will take O(26*log(n)) time )
Now from above frequencies count number of characters who have odd frequency.
If count > 1 , we cannot form palindrome, otherwise we can form palindrome
If we can form palindrome then,first we will assign 0 over L to R for each character in Segment Tree and then we will start from smallest character and assign it over (L,L+count/2-1) and (R-count/2+1,R) and then update L += count/2 and R -= count/2
So the time complexity of each query is O(26log(n)) and for building Segment Tree time complexity is O(nlog(n)) so overall time complexity is O(nlogn + q26logn).
For a better understanding please see my code,
#include <bits/stdc++.h>
using namespace std;
#define enl '\n'
#define int long long
#define sz(s) (int)s.size()
#define all(v) (v).begin(),(v).end()
#define input(vec) for (auto &el : vec) cin >> el;
#define print(vec) for (auto &el : vec) cout << el << " "; cout << "\n";
const int mod = 1e9+7;
const int inf = 1e18;
struct SegTree {
vector<pair<bool,int>>lazy;
vector<int>cnt;
SegTree () {}
SegTree(int n) {
lazy.assign(4*n,{false,0});
cnt.assign(4*n,0);
}
int query(int l,int r,int st,int en,int node) {
int mid = (st+en)/2;
if(st!=en and lazy[node].first) {
if(lazy[node].second) {
cnt[2*node] = mid - st + 1;
cnt[2*node+1] = en - mid;
}
else {
cnt[2*node] = cnt[2*node+1] = 0;
}
lazy[2*node] = lazy[2*node+1] = lazy[node];
lazy[node] = {false,0};
}
if(st>r or en<l) return 0;
if(st>=l and en<=r) return cnt[node];
return query(l,r,st,mid,2*node) + query(l,r,mid+1,en,2*node+1);
}
void update(int l,int r,int val,int st,int en,int node) {
int mid = (st+en)/2;
if(st!=en and lazy[node].first) {
if(lazy[node].second) {
cnt[2*node] = mid - st + 1;
cnt[2*node+1] = en - mid;
}
else {
cnt[2*node] = cnt[2*node+1] = 0;
}
lazy[2*node] = lazy[2*node+1] = lazy[node];
lazy[node] = {false,0};
}
if(st>r or en<l) return;
if(st>=l and en<=r) {
cnt[node] = (en - st + 1)*val;
lazy[node] = {true,val};
return;
}
update(l,r,val,st,mid,2*node);
update(l,r,val,mid+1,en,2*node+1);
cnt[node] = cnt[2*node] + cnt[2*node+1];
}
};
void solve() {
int n;
cin>>n;
string s;
cin>>s;
vector<SegTree>tr(26,SegTree(n));
for(int i=0;i<n;i++) {
tr[s[i]-'a'].update(i,i,1,0,n-1,1);
}
int q;
cin>>q;
while(q--) {
int l,r;
cin>>l>>r;
vector<int>cnt(26);
for(int i=0;i<26;i++) {
cnt[i] = tr[i].query(l,r,0,n-1,1);
}
int odd = 0;
for(auto u:cnt) odd += u%2;
if(odd>1) continue;
for(int i=0;i<26;i++) {
tr[i].update(l,r,0,0,n-1,1);
}
int x = l,y = r;
for(int i=0;i<26;i++) {
if(cnt[i]/2) {
tr[i].update(x,x+cnt[i]/2-1,1,0,n-1,1);
tr[i].update(y-cnt[i]/2+1,y,1,0,n-1,1);
x += cnt[i]/2;
y -= cnt[i]/2;
cnt[i]%=2;
}
}
for(int i=0;i<26;i++) {
if(cnt[i]) {
tr[i].update(x,x,1,0,n-1,1);
}
}
}
string ans(n,'a');
for(int i=0;i<26;i++) {
for(int j=0;j<n;j++) {
if(tr[i].query(j,j,0,n-1,1)) {
ans[j] = (char)('a'+i);
}
}
}
cout<<ans<<enl;
}
signed main() {
ios_base::sync_with_stdio(false);
cin.tie(nullptr);cout.tie(nullptr);
int testcases = 1;
cin>>testcases;
while(testcases--) solve();
return 0;
}
I'm facing difficulty in understanding O(sum) complexity solution of coin changing problem.
The problem statement is:
You are given a set of coins A. In how many ways can you make sum B assuming you have infinite amount of each coin in the set.
NOTE:
Coins in set A will be unique. Expected space complexity of this problem is O(B).
The solution is:
int count( int S[], int m, int n )
{
int table[n+1];
memset(table, 0, sizeof(table));
table[0] = 1;
for(int i=0; i<m; i++)
for(int j=S[i]; j<=n; j++)
table[j] += table[j-S[i]];
return table[n];
}
can someone explain me this code.?
First, let's identify the parameters and variables used in the function:
Parameters:
S contain the denomination of all m coins. i.e. Each element contain the value of each coin.
m represents the number of coin denominations. Essentially, it's the length of array S.
n represents the sum B to be achieved.
Variables:
table: Element i in array table contains the number of ways sum i can be achieved with the given coins. table[0] = 1 because there is a single way to achieve a sum of 0 (not using any coin).
i loops through each coin.
Logic:
The number of ways to achieve a sum j = sum of the following:
number of ways to achieve a sum of j - S[0]
number of ways to achieve a sum of j - S[1]
...
number of ways to achieve a sum of j - S[m-1] (S[m-1] is the value of the mth coin)
I did not completely decipher nor validate the rest of the code, but I hope this is a step in the right direction.
Added comments to code:
#include <stdio.h>
#include <string.h>
int count( int S[], int m, int n )
{
int table[n+1];
memset(table, 0, sizeof(table));
table[0] = 1;
for(int i=0; i<m; i++) // Loop through all of the coins
for(int j=S[i]; j<=n; j++) // Achieve sum j between the value of S[i] and n.
table[j] += table[j-S[i]]; // Add to the number of ways to achieve sum j the number of ways to achieve sum j - S[i]
return table[n];
}
int main() {
int S[] = {1, 2};
int m = 2;
int n = 3;
int c = count(S, m, n);
printf("%d\n", c);
}
Notes:
The code avoids repeats: 3 = 1+1+1, 1+2 (2 ways instead of 3 if 2+1 was considered.
No dependence on the order of the coins in term of value.
For a given integer, n, find the number following n that is a multiple of 10.
I wrote code that seems to be correct, but the site reviewer writes that it is only 90% correct. What could be the problem?
#include <iostream>
using namespace std;
int main()
{
int n;
cin >> n;
if (n == 0) n = n + 10;
while (n % 10 != 0) n++;
cout << n;
}
Your code doesn't work if the given n is itself a multiple of 10, in which case it returns 'itself' rather than the next multiple of 10 (i.e. 1 in 10 possible cases = 90% success rate).
To fix this, increment the n before testing for a multiple of 10:
#include <iostream>
int main()
{
int n;
std::cin >> n;
while (++n % 10 != 0)
;
std::cout << n;
return 0;
}
Alternatively, you can avoid the loop entirely. The following will work for both positive and negative numbers (it's a lot simpler if you don't cater for negative numbers):
n += ( n >= 0 ? 10 : 0 ) - (n % 10);
As the question states,we are given a positive integer M and a non-negative integer S. We have to find the smallest and the largest of the numbers that have length M and sum of digits S.
Constraints:
(S>=0 and S<=900)
(M>=1 and M<=100)
I thought about it and came to conclusion that it must be Dynamic Programming.However I failed to build DP state.
This is what I thought:-
dp[i][j]=First 'i' digits having sum 'j'
And tried to make program.This is how it looks like
/*
*** PATIENCE ABOVE PERFECTION ***
"When in doubt, use brute force. :D"
-Founder of alloj.wordpress.com
*/
#include<bits/stdc++.h>
using namespace std;
#define pb push_back
#define mp make_pair
#define nline cout<<"\n"
#define fast ios_base::sync_with_stdio(false),cin.tie(0)
#define ull unsigned long long int
#define ll long long int
#define pii pair<int,int>
#define MAXX 100009
#define fr(a,b,i) for(int i=a;i<b;i++)
vector<int>G[MAXX];
int main()
{
int m,s;
cin>>m>>s;
int dp[m+1][s+1];
fr(1,m+1,i)
fr(1,s+1,j)
fr(0,10,k)
dp[i][j]=min(dp[i-1][j-k]+k,dp[i][j]); //Tried for Minimum
cout<<dp[m][s]<<endl;
return 0;
}
Please guide me about this DP state and what will be the time complexity of the program.This is my first try of DP.
dp solution goes here :-
#include<iostream>
using namespace std;
int dp[102][902][2] ;
void print_ans(int m , int s , int flag){
if(m==0)
return ;
cout<<dp[m][s][flag];
if(dp[m][s][flag]!=-1)
print_ans(m-1 , s-dp[m][s][flag] , flag );
return ;
}
int main(){
//freopen("problem.in","r",stdin);
//freopen("out.txt","w",stdout);
//int t;
//cin>>t;
//while(t--){
int m , s ;
cin>>m>>s;
if(s==0){
cout<<(m==1?"0 0":"-1 -1");
return 0;
}
for(int i = 0 ; i <=m ; i++){
for(int j=0 ; j<=s ;j++){
dp[i][j][0]=-1;
dp[i][j][1]=-1;
}
}
for(int i = 0 ; i < 10 ; i++){
dp[1][i][0]=i;
dp[1][i][1]=i;
}
for(int i = 2 ; i<=m ; i++){
for(int j = 0 ; j<=s ; j++){
int flag = -1;
int f = -1;
for(int k = 0 ; k <= 9 ; k++){
if(i==m&&k==0)
continue;
if( j>=k && flag==-1 && dp[i-1][j-k][0]!=-1)
flag = k;
}
for(int k = 9 ; k >=0 ;k--){
if(i==m&&k==0)
continue;
if( j>=k && f==-1 && dp[i-1][j-k][1]!=-1)
f = k;
}
dp[i][j][0]=flag;
dp[i][j][1]=f;
}
}
if(m!=0){
print_ans(m , s , 0);
cout<<" ";
print_ans(m,s,1);
}
else
cout<<"-1 -1";
cout<<endl;
// }
}
The DP state is (i,j). It can be thought of as the parameters of a mathematical function defined in terms of recurrences(Smaller problems ,Hence sub problems!)
More deeply,
State is generally the number of parameters to identify the problem uniquely , so that we always know on what we are computing on!!
Let us take the example of your question only
Just to define your problem we will need Number of Digits in the state + Sums that can be formed with these Digits (Note: You are kind of collectively keeping the sum while traversing through digits!)
I think that is enough for the state part.
Now,
Running time of Dynamic Programming is very simple.
First Let us see how many sub problems exist in a problem :
You need to fill up each and every state i.e. You have to cover all the unique sub problems smaller than or equal to the whole problem !!
Which problem is smaller than the other is known by the recurrent relation !!
For example:
Fibonacci Sequence
F(n)=F(n-1)+F(n-2)
Note the base case , is always the smallest sub problem .!!
Note Here for F(n) We have to calculate F(n-1) and F(n-2) , And it will reach a stage where n=1 , where you need to return the base case!!
Hence the total number of sub problems can be said as all the problems between the base case and the current problem!
Now,
In bottom up , we need to process each and every state in terms of size between this base case and problem!
Now, This tells us that the Running time should be
O(Number of Subproblems * Time per each subproblem).
So how many subproblems exist in your solution DP[0][0] to DP[M][S]
and for every problem you are running a loop of 10
O( M*S (Subproblems ) * 10 )
Chop that constant of!
But it is not necessarily a constant always!!
Here is some code which you might want to look! Feel free to ask anything !
#include<bits/stdc++.h>
using namespace std;
bool DP[9][101];
int Number[9][101];
int main()
{
DP[0][0]=true; // It is possible to form 0 using NULL digits!!
int N=9,S=100,i,j,k;
for(i=1;i<=9;++i)
for(j=0;j<=100;++j)
{
if(DP[i-1][j])
{
for(k=0;k<=9;++k)
if(j+k<=100)
{
DP[i][j+k]=true;
Number[i][j+k]=Number[i-1][j]*10+k;
}
}
}
cout<<Number[9][81]<<"\n";
return 0;
}
You can rather use backtracking rather than storing the numbers directly just because your constraints are high!
DP[i][j] represents if it is possible to form sum of digits using i digits only!!
Number[i][j]
is my laziness to avoid typing a backtrack way(Sleepy, its already 3A.M.)
I am trying to add all the possible digits to extend the state.
It is essentially kind of forward DP style!! You can read more about it at Topcoder
I want to know efficient approach for the New Lottery Game problem.
The Lottery is changing! The Lottery used to have a machine to generate a random winning number. But due to cheating problems, the Lottery has decided to add another machine. The new winning number will be the result of the bitwise-AND operation between the two random numbers generated by the two machines.
To find the bitwise-AND of X and Y, write them both in binary; then a bit in the result in binary has a 1 if the corresponding bits of X and Y were both 1, and a 0 otherwise. In most programming languages, the bitwise-AND of X and Y is written X&Y.
For example:
The old machine generates the number 7 = 0111.
The new machine generates the number 11 = 1011.
The winning number will be (7 AND 11) = (0111 AND 1011) = 0011 = 3.
With this measure, the Lottery expects to reduce the cases of fraudulent claims, but unfortunately an employee from the Lottery company has leaked the following information: the old machine will always generate a non-negative integer less than A and the new one will always generate a non-negative integer less than B.
Catalina wants to win this lottery and to give it a try she decided to buy all non-negative integers less than K.
Given A, B and K, Catalina would like to know in how many different ways the machines can generate a pair of numbers that will make her a winner.
For small input we can check all possible pairs but how to do it with large inputs. I guess we represent the binary number into string first and then check permutations which would give answer less than K. But I can't seem to figure out how to calculate possible permutations of 2 binary strings.
I used a general DP technique that I described in a lot of detail in another answer.
We want to count the pairs (a, b) such that a < A, b < B and a & b < K.
The first step is to convert the numbers to binary and to pad them to the same size by adding leading zeroes. I just padded them to a fixed size of 40. The idea is to build up the valid a and b bit by bit.
Let f(i, loA, loB, loK) be the number of valid suffix pairs of a and b of size 40 - i. If loA is true, it means that the prefix up to i is already strictly smaller than the corresponding prefix of A. In that case there is no restriction on the next possible bit for a. If loA ist false, A[i] is an upper bound on the next bit we can place at the end of the current prefix. loB and loK have an analogous meaning.
Now we have the following transition:
long long f(int i, bool loA, bool loB, bool loK) {
// TODO add memoization
if (i == 40)
return loA && loB && loK;
int hiA = loA ? 1: A[i]-'0'; // upper bound on the next bit in a
int hiB = loB ? 1: B[i]-'0'; // upper bound on the next bit in b
int hiK = loK ? 1: K[i]-'0'; // upper bound on the next bit in a & b
long long res = 0;
for (int a = 0; a <= hiA; ++a)
for (int b = 0; b <= hiB; ++b) {
int k = a & b;
if (k > hiK) continue;
res += f(i+1, loA || a < A[i]-'0',
loB || b < B[i]-'0',
loK || k < K[i]-'0');
}
return res;
}
The result is f(0, false, false, false).
The runtime is O(max(log A, log B)) if memoization is added to ensure that every subproblem is only solved once.
What I did was just to identify when the answer is A * B.
Otherwise, just brute force the rest, this code passed the large input.
// for each test cases
long count = 0;
if ((K > A) || (K > B)) {
count = A * B;
continue; // print count and go to the next test case
}
count = A * B - (A-K) * (B-K);
for (int i = K; i < A; i++) {
for (int j = K; j < B; j++) {
if ((i&j) < K) count++;
}
}
I hope this helps!
just as Niklas B. said.
the whole answer is.
#include <algorithm>
#include <cstring>
#include <iomanip>
#include <iostream>
#include <iterator>
#include <map>
#include <sstream>
#include <string>
#include <vector>
using namespace std;
#define MAX_SIZE 32
int A, B, K;
int arr_a[MAX_SIZE];
int arr_b[MAX_SIZE];
int arr_k[MAX_SIZE];
bool flag [MAX_SIZE][2][2][2];
long long matrix[MAX_SIZE][2][2][2];
long long
get_result();
int main(int argc, char *argv[])
{
int case_amount = 0;
cin >> case_amount;
for (int i = 0; i < case_amount; ++i)
{
const long long result = get_result();
cout << "Case #" << 1 + i << ": " << result << endl;
}
return 0;
}
long long
dp(const int h,
const bool can_A_choose_1,
const bool can_B_choose_1,
const bool can_K_choose_1)
{
if (MAX_SIZE == h)
return can_A_choose_1 && can_B_choose_1 && can_K_choose_1;
if (flag[h][can_A_choose_1][can_B_choose_1][can_K_choose_1])
return matrix[h][can_A_choose_1][can_B_choose_1][can_K_choose_1];
int cnt_A_max = arr_a[h];
int cnt_B_max = arr_b[h];
int cnt_K_max = arr_k[h];
if (can_A_choose_1)
cnt_A_max = 1;
if (can_B_choose_1)
cnt_B_max = 1;
if (can_K_choose_1)
cnt_K_max = 1;
long long res = 0;
for (int i = 0; i <= cnt_A_max; ++i)
{
for (int j = 0; j <= cnt_B_max; ++j)
{
int k = i & j;
if (k > cnt_K_max)
continue;
res += dp(h + 1,
can_A_choose_1 || (i < cnt_A_max),
can_B_choose_1 || (j < cnt_B_max),
can_K_choose_1 || (k < cnt_K_max));
}
}
flag[h][can_A_choose_1][can_B_choose_1][can_K_choose_1] = true;
matrix[h][can_A_choose_1][can_B_choose_1][can_K_choose_1] = res;
return res;
}
long long
get_result()
{
cin >> A >> B >> K;
memset(arr_a, 0, sizeof(arr_a));
memset(arr_b, 0, sizeof(arr_b));
memset(arr_k, 0, sizeof(arr_k));
memset(flag, 0, sizeof(flag));
memset(matrix, 0, sizeof(matrix));
int i = 31;
while (i >= 1)
{
arr_a[i] = A % 2;
A /= 2;
arr_b[i] = B % 2;
B /= 2;
arr_k[i] = K % 2;
K /= 2;
i--;
}
return dp(1, 0, 0, 0);
}