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")
#include <bits/stdc++.h>
using namespace std;
void OJize(){cin.tie(NULL);ios_base::sync_with_stdio(false);}
typedef long long ll;
const int IINF = 0x3f3f3f3f;
const ll LINF = 0x3f3f3f3f3f3f3f3f;
#define sz(X) (int)((X).size())
#define entire(X) X.begin(),X.end()
template <class T1, class T2>ostream&operator<<(ostream &os,pair<T1,T2>const&x){os<<'('<<x.first<<", "<<x.second<<')';return os;}
template <class Ch, class Tr, class Container>basic_ostream<Ch,Tr>&operator<<(basic_ostream<Ch,Tr>&os,Container const&x){os<<"[ ";for(auto&y:x)os<<y<<" ";return os<<"]";}
template <typename T>
struct Compress{
int n; vector<T> arr;
void add(T x){arr.push_back(x); n++;}
void init(){sort(entire(arr));}
int lb(T x){return lower_bound(entire(arr), x) - arr.begin();}
int ub(T x){return upper_bound(entire(arr), x) - arr.begin();}
};
// NOTE: this is not a "sparse table" related to
// binary lifting, it's literally an array which is sparse!!
template<typename T>
struct SparseArray{
// not actually sparse yet!!
int n, L;
vector<int> idxs;
Compress<int> C;
vector<T> val, sum, prefm, sufm;
SparseArray(int N): n{N} {}
map<int, T> M;
void write(int i, T x){M[i] = x;}
void init(){
L = sz(M);
if(!L) return;
sum.resize(L), prefm.resize(L), sufm.resize(L);
for(auto [i, x]: M) C.add(i), val.push_back(x);
C.init();
sum[0] = prefm[0] = val[0];
for(int i=1; i<L; i++){
sum[i] = sum[i-1]+val[i];
prefm[i] = max(prefm[i-1], val[i]);
}
idxs = C.arr;
sufm[L-1] = val[L-1];
for(int i=L-2; i>=0; i--)
sufm[i] = max(sufm[i+1], val[i]);
}
T operator[](int i){
int idx = C.lb(i);
if(idx == L || C.arr[idx] != i) return 0;
return val[idx];
}
T prefsum(int i){
i = C.ub(i)-1;
return i>=0? sum[i] : (T)0;
}
T getsum(int l, int r){return prefsum(r) - prefsum(l);}
T allmax(){return prefm.back();}
T prefmax(int i){
i = C.ub(i)-1;
return i>=0? prefm[i] : (T)0;
}
T sufmax(int i){
i = C.lb(i);
return i<L? sufm[i] : (T)0;
}
};
ll max_weights(int L, int n,
vector<int> X, vector<int> Y, vector<int> W){
vector<SparseArray<ll>> grid(L, SparseArray<ll>(L+1));
for(int i=0; i<L; i++)
grid[i].write(0, 0), grid[i].write(L, 0);
for(int i=0; i<n; i++) grid[X[i]].write(Y[i], (ll)W[i]);
for(auto &A: grid) A.init();
SparseArray<ll> dinc(L+1), ddec(L+1);
dinc.init(); ddec.init();
// column _,
// last column height j,
// next will increase/decrease
for(int i=1; i<L; i++){
SparseArray<ll> ndinc(L+1), nddec(L+1);
SparseArray<ll> incmaxer(L+1), decmaxer(L+1);
for(int y0: grid[i-1].idxs){
incmaxer.write(y0, dinc[y0] - grid[i-1].prefsum(y0-1));
decmaxer.write(y0, ddec[y0] + grid[i].prefsum(y0-1));
}
incmaxer.init(), decmaxer.init();
for(int y: grid[i].idxs){
ll incy = 0, decy = 0;
if(y == 0) incy = decy = ddec[0];
if(y == L) incy = decy = max(ddec[0], dinc[L]);
ll incmax = grid[i-1].prefsum(y-1) + incmaxer.prefmax(y-1);
incy = max(incy, incmax);
if(y == L) decy = max(decy, incmax);
ll decmax = -grid[i].prefsum(y-1) + decmaxer.sufmax(y+1);
decy = max(decy, decmax);
ndinc.write(y, incy);
nddec.write(y, decy);
}
ndinc.init(), nddec.init();
dinc = ndinc, ddec = nddec;
}
return max(dinc.allmax(), ddec.allmax());
}
#ifdef jh
int main(){OJize();
int n; cin>>n;
vector<int> X, Y, W;
for(int i=0; i<n; i++) for(int j=0; j<n; j++){
int x; cin>>x;
if(x){
X.push_back(j);
Y.push_back(n-1-i);
W.push_back(x);
}
}
cout << max_weights(n, sz(X), X, Y, W);
}
#endif
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