Suppose a_1 is known and a_2, ..., a_q can be computed recursively by a_k=a_{k-1} + f(k), where f(k) is some function of k.
However q is minimum number such that a_1+ \sum_{k=2}^q f(k) >= 1000 and unknown.
I want to find a_2,..., a_q using c++. A straight-forward way is to find the q first; then initialize an array of size q and store the value in to an array, as follows.
However, I feel it computed f(k) twice and is a waste of resource. Is there any way I can initialize an unknown size array in c++ and solve it in one loop?
//find the max ***q*** first
int k=1;
int sum=a_1;
while(sum < 1000){
int inc = some equation of k;
sum += inc;
k++;
//compute a_2, ..., a_q
int array[k-1];
int sum=a_1;
for(int h=0; h<k; h++){
int inc = some equation of k; // repeated computation
sum += inc;
array[h]=sum;
}
Using a vector will be a good solution.
In vector, you don't even need to worry about the new entries - allocation (and deletion later if any) as the vector will take care of it without your knowledge.
And also it gives a lot of options than a regular array.
Use either std::vector or std::unique_ptr<int[]>.
See embedded comments:
#include <vector>
#include <memory>
int some_equation(int k) { return 0; }
void test(int a_1)
{
//find the max ***q*** first
int k=1;
int sum=a_1;
while(sum < 1000){
int inc = some_equation(k);
sum += inc;
k++;
//
// 2 alternate methods - you should normally prefer the std::vector approach
//
auto array = std::vector<int>(k-1); // should this be k-1? don't you need k elements?
// auto array = std::make_unique<int[]>(k-1);
int sum=a_1;
for(int h=0; h<k; h++){
int inc = some_equation(k); // repeated computation
sum += inc;
array[h]=sum;
}
}
}
I solved this problem but I got TLE Time Limit Exceed on online judge
the output of program is right but i think the way can be improved to be more efficient!
the problem :
Given n integer numbers, count the number of ways in which we can choose two elements such
that their absolute difference is less than 32.
In a more formal way, count the number of pairs (i, j) (1 ≤ i < j ≤ n) such that
|V[i] - V[j]| < 32. |X|
is the absolute value of X.
Input
The first line of input contains one integer T, the number of test cases (1 ≤ T ≤ 128).
Each test case begins with an integer n (1 ≤ n ≤ 10,000).
The next line contains n integers (1 ≤ V[i] ≤ 10,000).
Output
For each test case, print the number of pairs on a single line.
my code in c++ :
int main() {
int T,n,i,j,k,count;
int a[10000];
cin>>T;
for(k=0;k<T;k++)
{ count=0;
cin>>n;
for(i=0;i<n;i++)
{
cin>>a[i];
}
for(i=0;i<n;i++)
{
for(j=i;j<n;j++)
{
if(i!=j)
{
if(abs(a[i]-a[j])<32)
count++;
}
}
}
cout<<count<<endl;
}
return 0;
}
I need help how can I solve it in more efficient algorithm ?
Despite my previous (silly) answer, there is no need to sort the data at all. Instead you should count the frequencies of the numbers.
Then all you need to do is keep track of the number of viable numbers to pair with, while iterating over the possible values. Sorry no c++ but java should be readable as well:
int solve (int[] numbers) {
int[] frequencies = new int[10001];
for (int i : numbers) frequencies[i]++;
int solution = 0;
int inRange = 0;
for (int i = 0; i < frequencies.length; i++) {
if (i > 32) inRange -= frequencies[i - 32];
solution += frequencies[i] * inRange;
solution += frequencies[i] * (frequencies[i] - 1) / 2;
inRange += frequencies[i];
}
return solution;
}
#include <bits/stdc++.h>
using namespace std;
int a[10010];
int N;
int search (int x){
int low = 0;
int high = N;
while (low < high)
{
int mid = (low+high)/2;
if (a[mid] >= x) high = mid;
else low = mid+1;
}
return low;
}
int main() {
cin >> N;
for (int i=0 ; i<N ; i++) cin >> a[i];
sort(a,a+N);
long long ans = 0;
for (int i=0 ; i<N ; i++)
{
int t = search(a[i]+32);
ans += (t -i - 1);
}
cout << ans << endl;
return 0;
}
You can sort the numbers, and then use a sliding window. Starting with the smallest number, populate a std::deque with the numbers so long as they are no larger than the smallest number + 31. Then in an outer loop for each number, update the sliding window and add the new size of the sliding window to the counter. Update of the sliding window can be performed in an inner loop, by first pop_front every number that is smaller than the current number of the outer loop, then push_back every number that is not larger than the current number of the outer loop + 31.
One faster solution would be to first sort the array, then iterate through the sorted array and for each element only visit the elements to the right of it until the difference exceeds 31.
Sorting can probably be done via count sort (since you have 1 ≤ V[i] ≤ 10,000). So you get linear time for the sorting part. It might not be necessary though (maybe quicksort suffices in order to get all the points).
Also, you can do a trick for the inner loop (the "going to the right of the current element" part). Keep in mind that if S[i+k]-S[i]<32, then S[i+k]-S[i+1]<32, where S is the sorted version of V. With this trick the whole algorithm turns linear.
This can be done constant number of passes over the data, and actually can be done without being affected by the value of the "interval" (in your case, 32).
This is done by populating an array where a[i] = a[i-1] + number_of_times_i_appears_in_the_data - informally, a[i] holds the total number of elements that are smaller/equals to i.
Code (for a single test case):
static int UPPER_LIMIT = 10001;
static int K = 32;
int frequencies[UPPER_LIMIT] = {0}; // O(U)
int n;
std::cin >> n;
for (int i = 0; i < n; i++) { // O(n)
int x;
std::cin >> x;
frequencies[x] += 1;
}
for (int i = 1; i < UPPER_LIMIT; i++) { // O(U)
frequencies[i] += frequencies[i-1];
}
int count = 0;
for (int i = 1; i < UPPER_LIMIT; i++) { // O(U)
int low_idx = std::max(i-32, 0);
int number_of_elements_with_value_i = frequencies[i] - frequencies[i-1];
if (number_of_elements_with_value_i == 0) continue;
int number_of_elements_with_value_K_close_to_i =
(frequencies[i-1] - frequencies[low_idx]);
std::cout << "i: " << i << " number_of_elements_with_value_i: " << number_of_elements_with_value_i << " number_of_elements_with_value_K_close_to_i: " << number_of_elements_with_value_K_close_to_i << std::endl;
count += number_of_elements_with_value_i * number_of_elements_with_value_K_close_to_i;
// Finally, add "duplicates" of i, this is basically sum of arithmetic
// progression with d=1, a0=0, n=number_of_elements_with_value_i
count += number_of_elements_with_value_i * (number_of_elements_with_value_i-1) /2;
}
std::cout << count;
Working full example on IDEone.
You can sort and then use break to end loop when ever the range goes out.
int main()
{
int t;
cin>>t;
while(t--){
int n,c=0;
cin>>n;
int ar[n];
for(int i=0;i<n;i++)
cin>>ar[i];
sort(ar,ar+n);
for(int i=0;i<n;i++){
for(int j=i+1;j<n;j++){
if(ar[j]-ar[i] < 32)
c++;
else
break;
}
}
cout<<c<<endl;
}
}
Or, you can use a hash array for the range and mark occurrence of each element and then loop around and check for each element i.e. if x = 32 - y is present or not.
A good approach here is to split the numbers into separate buckets:
constexpr int limit = 10000;
constexpr int diff = 32;
constexpr int bucket_num = (limit/diff)+1;
std::array<std::vector<int>,bucket_num> buckets;
cin>>n;
int number;
for(i=0;i<n;i++)
{
cin >> number;
buckets[number/diff].push_back(number%diff);
}
Obviously the numbers that are in the same bucket are close enough to each other to fit the requirement, so we can just count all the pairs:
int result = std::accumulate(buckets.begin(), buckets.end(), 0,
[](int s, vector<int>& v){ return s + (v.size()*(v.size()-1))/2; });
The numbers that are in non-adjacent buckets cannot form any acceptable pairs, so we can just ignore them.
This leaves the last corner case - adjacent buckets - which can be solved in many ways:
for(int i=0;i<bucket_num-1;i++)
if(buckets[i].size() && buckets[i+1].size())
result += adjacent_buckets(buckets[i], buckets[i+1]);
Personally I like the "occurrence frequency" approach on the one bucket scale, but there may be better options:
int adjacent_buckets(const vector<int>& bucket1, const vector<int>& bucket2)
{
std::array<int,diff> pairs{};
for(int number : bucket1)
{
for(int i=0;i<number;i++)
pairs[i]++;
}
return std::accumulate(bucket2.begin(), bucket2.end(), 0,
[&pairs](int s, int n){ return s + pairs[n]; });
}
This function first builds an array of "numbers from lower bucket that are close enough to i", and then sums the values from that array corresponding to the upper bucket numbers.
In general this approach has O(N) complexity, in the best case it will require pretty much only one pass, and overall should be fast enough.
Working Ideone example
This solution can be considered O(N) to process N input numbers and constant in time to process the input:
#include <iostream>
using namespace std;
void solve()
{
int a[10001] = {0}, N, n, X32 = 0, ret = 0;
cin >> N;
for (int i=0; i<N; ++i)
{
cin >> n;
a[n]++;
}
for (int i=0; i<10001; ++i)
{
if (i >= 32)
X32 -= a[i-32];
if (a[i])
{
ret += a[i] * X32;
ret += a[i] * (a[i]-1)/2;
X32 += a[i];
}
}
cout << ret << endl;
}
int main()
{
int T;
cin >> T;
for (int i=0 ; i<T ; i++)
solve();
}
run this code on ideone
Solution explanation: a[i] represents how many times i was in the input series.
Then you go over entire array and X32 keeps track of number of elements that's withing range from i. The only tricky part really is to calculate properly when some i is repeated multiple times: a[i] * (a[i]-1)/2. That's it.
You should start by sorting the input.
Then if your inner loop detects the distance grows above 32, you can break from it.
Thanks for everyone efforts and time to solve this problem.
I appreciated all Attempts to solve it.
After testing the answers on online judge I found the right and most efficient solution algorithm is Stef's Answer and AbdullahAhmedAbdelmonem's answer also pavel solution is right but it's exactly same as Stef solution in different language C++.
Stef's code got time execution 358 ms in codeforces online judge and accepted.
also AbdullahAhmedAbdelmonem's code got time execution 421 ms in codeforces online judge and accepted.
if they put detailed explanation to there algorithm the bounty will be to one of them.
you can try your solution and submit it to codeforces online judge at this link after choosing problem E. Time Limit Exceeded?
also I found a great algorithm solution and more understandable using frequency array and it's complexity O(n).
in this algorithm you only need to take specific range for each inserted element to the array which is:
begin = element - 32
end = element + 32
and then count number of pair in this range for each inserted element in the frequency array :
int main() {
int T,n,i,j,k,b,e,count;
int v[10000];
int freq[10001];
cin>>T;
for(k=0;k<T;k++)
{
count=0;
cin>>n;
for(i=1;i<=10000;i++)
{
freq[i]=0;
}
for(i=0;i<n;i++)
{
cin>>v[i];
}
for(i=0;i<n;i++)
{
count=count+freq[v[i]];
b=v[i]-31;
e=v[i]+31;
if(b<=0)
b=1;
if(e>10000)
e=10000;
for(j=b;j<=e;j++)
{
freq[j]++;
}
}
cout<<count<<endl;
}
return 0;
}
finally i think the best approach to solve this kind of problems to use frequency array and count number of pairs in specific range because it's time complexity is O(n).
I am pretty noobie with C++ and am trying to do some HackerRank challenges as a way to work on that.
Right now I am trying to solve Angry Children problem: https://www.hackerrank.com/challenges/angry-children
Basically, it asks to create a program that given a set of N integer, finds the smallest possible "unfairness" for a K-length subset of that set. Unfairness is defined as the difference between the max and min of a K-length subset.
The way I'm going about it now is to find all K-length subsets and calculate their unfairness, keeping track of the smallest unfairness.
I wrote the following C++ program that seems to the problem correctly:
#include <cmath>
#include <cstdio>
#include <iostream>
using namespace std;
int unfairness = -1;
int N, K, minc, maxc, ufair;
int *candies, *subset;
void check() {
ufair = 0;
minc = subset[0];
maxc = subset[0];
for (int i = 0; i < K; i++) {
minc = min(minc,subset[i]);
maxc = max(maxc, subset[i]);
}
ufair = maxc - minc;
if (ufair < unfairness || unfairness == -1) {
unfairness = ufair;
}
}
void process(int subsetSize, int nextIndex) {
if (subsetSize == K) {
check();
} else {
for (int j = nextIndex; j < N; j++) {
subset[subsetSize] = candies[j];
process(subsetSize + 1, j + 1);
}
}
}
int main() {
cin >> N >> K;
candies = new int[N];
subset = new int[K];
for (int i = 0; i < N; i++)
cin >> candies[i];
process(0, 0);
cout << unfairness << endl;
return 0;
}
The problem is that HackerRank requires the program to come up with a solution within 3 seconds and that my program takes longer than that to find the solution for 12/16 of the test cases. For example, one of the test cases has N = 50 and K = 8; the program takes 8 seconds to find the solution on my machine. What can I do to optimize my algorithm? I am not very experienced with C++.
All you have to do is to sort all the numbers in ascending order and then get minimal a[i + K - 1] - a[i] for all i from 0 to N - K inclusively.
That is true, because in optimal subset all numbers are located successively in sorted array.
One suggestion I'd give is to sort the integer list before selecting subsets. This will dramatically reduce the number of subsets you need to examine. In fact, you don't even need to create subsets, simply look at the elements at index i (starting at 0) and i+k, and the lowest difference for all elements at i and i+k [in valid bounds] is your answer. So now instead of n choose k subsets (factorial runtime I believe) you just have to look at ~n subsets (linear runtime) and sorting (nlogn) becomes your bottleneck in performance.
Let's say you have a number of unsorted arrays containing integers. Your job is to make sums of the arrays. The sums have to contain exactly one value from each array, i.e. (for 3 arrays)
sum = array1[2]+array2[12]+array3[4];
Goal: You should output the 20 combinations that generate the lowest possible sums.
The solution below is off-limits as the algorithm needs to be able to handle 10 arrays that can contain a huge number of integers. The following solution is way too slow for larger number of arrays:
//You already have int array1, array2 and array3
int top[20];
for(int i=0; i<20; i++)
top[i] = 1e99;
int sum = 0;
for(int i=0; i<array1.size(); i++) //One for loop per array is trouble for
for(int j=0; j<array2.size(); j++) //increasing numbers of arrays
for(int k=0; k<array3.size(); k++)
{
sum = array1[i] + array2[j] + array3[k];
if (sum < top[19])
swapFunction(sum, top); //Function that adds sum to top
//and sorts top in increasing order
}
printResults(top); // Outputs top 20 lowest sums in increasing order
What would you do to achieve correct results more efficiently (with a lower Big O notation)?
The answer can be found by considering how to find the absolute lowest sum, and how to find the 2nd lowest sum and so on.
As you only need 20 sums at most, you only need the lowest 20 values from each array at most. I would recommend using std::partial_sort for this.
The rest should be able to be accomplished with a priority_queue in which each element contains the current sum and the indicies of the arrays for this sum. Simply take each index of indicies and increase it by one, calculate the new sum and add that to the priority queue. The top most item of the queue should always be the one of the lowest sum. Remove the lowest sum, generate the next possibilities, and then repeat until you have enough answers.
Assuming that the number of answers needed is much less than Big O should be predominately be the efficiency of partial_sort (N + k*log(k)) * number of arrays
Here's some basic code to demonstrate the idea. There's very likely ways of improving on this. For example, I'm sure that with some work, you could avoid adding the same set of indicies multiple times, and there by eliminate the need for the do-while pop.
for (size_t i = 0; i < arrays.size(); i++)
{
auto b = arrays[i].begin();
partial_sort(b, b + numAnswers, arrays[i].end());
}
struct answer
{
answer(int s, vector<int> i)
: sum(s), indices(i)
{
}
int sum;
vector<int> indices;
bool operator <(const answer &o) const
{
return sum > o.sum;
}
};
auto getSum =[&arrays](const vector<int> &indices) {
auto retval = 0;
for (size_t i = 0; i < arrays.size(); i++)
{
retval += arrays[i][indices[i]];
}
return retval;
};
vector<int> initalIndices(arrays.size());
priority_queue<answer> q;
q.emplace(getSum(initalIndices), initalIndices );
for (auto i = 0; i < numAnswers; i++)
{
auto ans = q.top();
cout << ans.sum << endl;
do
{
q.pop();
} while (!q.empty() && q.top().indices == ans.indices);
for (size_t i = 0; i < ans.indices.size(); i++)
{
auto nextIndices = ans.indices;
nextIndices[i]++;
q.emplace(getSum(nextIndices), nextIndices);
}
}
Problem Statement
Mark is an undergraduate student and he is interested in rotation. A conveyor belt competition is going on in the town which Mark wants to win. In the competition, there's A conveyor belt which can be represented as a strip of 1xN blocks. Each block has a number written on it. The belt keeps rotating in such a way that after each rotation, each block is shifted to left of it and the first block goes to last position.
There is a switch near the conveyer belt which can stop the belt. Each participant would be given a single chance to stop the belt and his PMEAN would be calculated.
PMEAN is calculated using the sequence which is there on the belt when it stops. The participant having highest PMEAN is the winner. There can be multiple winners.
Mark wants to be among the winners. What PMEAN he should try to get which guarantees him to be the winner.
Definitions
PMEAN = (Summation over i = 1 to n) (i * i th number in the list)
where i is the index of a block at the conveyor belt when it is stopped. Indexing starts from 1.
Input Format
First line contains N denoting the number of elements on the belt.
Second line contains N space separated integers.
Output Format
Output the required PMEAN
Constraints
1 ≤ N ≤ 10^6
-10^9 ≤ each number ≤ 10^9
Code
#include <iostream>
#include <vector>
#include <algorithm>
using namespace std;
int main (void)
{
int n;
cin>>n;
vector <int> foo;
int i = 0,j = 0,k,temp,fal,garb=0;
while (i < n)
{
cin>>fal;
foo.push_back(fal);
i++;
}
vector<int> arr;
//arr.reserve(10000);
for ( i = 0; i < n; i++ )
{
garb = i+1;
arr.push_back(garb);
}
long long product = 0;
long long bar = 0;
while (j < n)
{
i = 0;
temp = foo[0];
while ( i < n-1 )
{
foo[i] = foo[i+1];
i++;
}
foo[i] = temp;
for ( k = 0; k < n; k++ )
bar = bar + arr[k]*foo[k];
if ( bar > product )
product = bar;
j++;
}
return 0;
}
My Question:
What I am doing is basically trying out different combinations of the original array and then multiplying it with the array containing the values 1 2 3 ...... and then returning the maximum value. However, I am getting a segmentation fault in this.
Why is that happening?
Here's some of your code:
vector <int> foo;
int i = 0;
while (i < n)
{
cin >> fal;
foo[i] = fal;
i++;
}
When you do foo[0] = fal, you cause undefined behavior. There's no room in foo for [0] yet. You probably want to use std::vector::push_back() instead.
This same issue also occurs when you work on vector<int> arr;
And just as an aside, people will normally write that loop using a for-loop:
for (int i=0; i<n; i++) {
int fal;
cin >> fal;
foo.push_back(fal);
}
With regards to the updated code:
You never increment i in the first loop.
garb is never initialized.