This submission is migrated from previous version of oj.uz, which used different machine for grading. This submission may have different result if resubmitted.
/*
#pragma GCC optimize("Ofast,unroll-loops")
#pragma GCC target("avx2,fma,bmi,bmi2,sse4.2,popcnt,lzcnt")
*/
#include <bits/stdc++.h>
#define taskname ""
#define all(x) x.begin(), x.end()
#define rall(x) x.rbegin(), x.rend()
#define i64 long long
#define pb push_back
#define ff first
#define ss second
#define isz(x) (int)x.size()
using namespace std;
const int mxN = 2e5 + 5;
const int mod = 1e9 + 7;
const i64 oo = 1e18;
// smawck for max
template<class F>
std::vector<int> smawck(F f, const std::vector<int> &rows, const std::vector<int> &cols) {
std::vector<int> ans(rows.size(), -1);
if((int) std::max(rows.size(), cols.size()) <= 2) {
for(int i = 0; i < (int) rows.size(); i++) {
for(auto j : cols) {
if(ans[i] == -1 || f(rows[i], ans[i], j)) {
ans[i] = j;
}
}
}
} else if(rows.size() < cols.size()) {
// reduce
std::vector<int> st;
for(int j : cols) {
while(1) {
if(st.empty()) {
st.push_back(j);
break;
} else if(f(rows[(int) st.size() - 1], st.back(), j)) {
st.pop_back();
} else if(st.size() < rows.size()) {
st.push_back(j);
break;
} else {
break;
}
}
}
ans = smawck(f, rows, st);
} else {
std::vector<int> newRows;
for(int i = 1; i < (int) rows.size(); i += 2) {
newRows.push_back(rows[i]);
}
auto otherAns = smawck(f, newRows, cols);
for(int i = 0; i < (int) newRows.size(); i++) {
ans[2*i+1] = otherAns[i];
}
for(int i = 0, l = 0, r = 0; i < (int) rows.size(); i += 2) {
if(i+1 == (int) rows.size()) r = (int) cols.size();
while(r < (int) cols.size() && cols[r] <= ans[i+1]) r++;
ans[i] = cols[l++];
for(; l < r; l++) {
if(f(rows[i], ans[i], cols[l])) {
ans[i] = cols[l];
}
}
l--;
}
}
return ans;
}
// max smawck
// F(i, j, k) checks if M[i][j] <= M[i][k]
// another interpretations is:
// F(i, j, k) checks if M[i][k] is at least as good as M[i][j]
// higher == better
// when comparing 2 columns as vectors
// for j < k, column j can start better than column k
// as soon as column k is at least as good, it's always at least as good
template<class F>
std::vector<int> smawck(F f, int n, int m) {
std::vector<int> rows(n), cols(m);
for(int i = 0; i < n; i++) rows[i] = i;
for(int i = 0; i < m; i++) cols[i] = i;
return smawck(f, rows, cols);
}
template<class T>
void MaxConvolutionWithConvexShape(const std::vector<T> &anyShape, const std::vector<T> &convexShape, std::vector<T> &ans) {
if((int) convexShape.size() <= 1) {
ans = anyShape;
return;
}
// if(anyShape.empty()) anyShape.push_back(0);
int n = (int) anyShape.size(), m = (int) convexShape.size();
auto function = [&](int i, int j) {
return anyShape[j] + convexShape[i-j];
};
auto comparator = [&](int i, int j, int k) {
if(i < k) return false;
if(i - j >= m) return true;
return function(i, j) <= function(i, k);
};
const std::vector<int> best = smawck(comparator, n + m - 1, n);
// ans.resize(n + m - 1);
for(int i = 0; i < n + m - 1; i++) {
ans[i] = max(ans[i], function(i, best[i]));
}
// return ans;
}
void solve() {
int n;
cin >> n;
vector<i64> a(n);
for (auto &val : a) cin >> val;
// int sum = 0;
// auto dfs = [&](auto self, int l, int r) -> void {
// if (mp.find(pair{l, r}) != mp.end()) return;
// mp[{l, r}] = 1;
// if (r - l == 1) { mp[{l, r}]++; return; }
// if (r - l == 2) { mp[{l, r}]++; return; }
// if (r - l == 3) { mp[{l, r}]++; return; }
// // cout << l << " " << r << endl;
// int mr = (l + r) >> 1, ml = mr - 1;
// self(self, l, ml); self(self, ml + 1, r);
// self(self, l, mr); self(self, mr + 1, r);
// };
// dfs(dfs, 0, n);
// cout << sum << endl;
// vector<int> A = {-2, -1, -2};
// vector<int> B = {-2, -0, -1, -3};
// vector<int> ans;
// MaxConvolutionWithConvexShape(A, B, ans);
// for (auto val : ans) cout << val << " ";
// cout << endl;
// return;
map<pair<int, int>, vector<i64>> mp;
auto dfs = [&](auto self, int l, int r) -> void {
if (r - l == 1) {
mp[{l, r}] = {0, *max_element(a.begin() + l, a.begin() + r)};
return;
}
if (r - l == 2) {
mp[{l, r}] = {0, *max_element(a.begin() + l, a.begin() + r)};
return;
}
if (r - l == 3) {
mp[{l, r}] = {0, *max_element(a.begin() + l, a.begin() + r), a[l] + a[l + 2]};
return;
}
mp[{l, r}].resize(((r - l + 1) >> 1) + 1);
int mr = (l + r) >> 1, ml = mr - 1;
if (mp.find({l, ml}) == mp.end()) self(self, l, ml);
if (mp.find({ml + 1, r}) == mp.end()) self(self, ml + 1, r);
MaxConvolutionWithConvexShape(mp[{l, ml}], mp[{ml + 1, r}], mp[{l, r}]);
if (mp.find({l, mr}) == mp.end()) self(self, l, mr);
if (mp.find({mr + 1, r}) == mp.end()) self(self, mr + 1, r);
MaxConvolutionWithConvexShape(mp[{l, mr}], mp[{mr + 1, r}], mp[{l, r}]);
return;
};
dfs(dfs, 0, n);
mp[{0, n}].erase(mp[{0, n}].begin());
for (auto val : mp[{0, n}]) cout << val << endl;
}
signed main() {
if (fopen("in.txt", "r"))
{
freopen("in.txt", "r", stdin);
freopen("out.txt", "w", stdout);
}
ios_base::sync_with_stdio(false);
cin.tie(nullptr);
int t = 1; //cin >> t;
while(t--) solve();
}
Compilation message (stderr)
candies.cpp: In function 'int main()':
candies.cpp:185:16: warning: ignoring return value of 'FILE* freopen(const char*, const char*, FILE*)' declared with attribute 'warn_unused_result' [-Wunused-result]
185 | freopen("in.txt", "r", stdin);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~
candies.cpp:186:16: warning: ignoring return value of 'FILE* freopen(const char*, const char*, FILE*)' declared with attribute 'warn_unused_result' [-Wunused-result]
186 | freopen("out.txt", "w", stdout);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~
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