Implementation of various algorithms
#define PROBLEM "https://atcoder.jp/contests/abc480/tasks/abc480_g"
#include "sparse_table.hpp"
#include "anti_monge_dd_smawk.hpp"
int main() {
int N;
cin >> N;
vector<long long> A(N);
for (int i = 0; i < N; ++i) cin >> A[i];
SparseTable<long long> stmi(A);
SparseTable<long long> stma(A, [&](long long p, long long q){return max(p, q);});
auto func = [&](int l, int r) -> long long {
assert(r - l >= 2);
return stma.get(l, r) - stmi.get(l, r);
};
auto res = antiMongeDDSMAWK<long long>(N, func, 2);
cout << res.back().first << endl;
}#line 1 "tests/AtCoder/ABC_480_G_anti_monge_dd_smawk.cpp"
#define PROBLEM "https://atcoder.jp/contests/abc480/tasks/abc480_g"
#line 2 "DataStructure/sparse_table.hpp"
#include <bits/stdc++.h>
#line 4 "DataStructure/sparse_table.hpp"
using namespace std;
// Sparse Table
template<class MeetSemiLattice> struct SparseTable {
using Func = function<MeetSemiLattice(MeetSemiLattice, MeetSemiLattice)>;
// core member
Func OP = [](const MeetSemiLattice &l, const MeetSemiLattice &r) {
return min(l, r);
};
vector<vector<MeetSemiLattice>> dat;
vector<int> height;
SparseTable() {}
SparseTable(const vector<MeetSemiLattice> &vec) {
init(vec);
}
SparseTable(const vector<MeetSemiLattice> &vec, const Func &op) {
init(vec, op);
}
void init(const vector<MeetSemiLattice> &vec) {
int n = (int)vec.size(), h = 1;
while ((1<<h) <= n) ++h;
dat.assign(h, vector<MeetSemiLattice>(1<<h));
height.assign(n+1, 0);
for (int i = 2; i <= n; i++) height[i] = height[i>>1]+1;
for (int i = 0; i < n; ++i) dat[0][i] = vec[i];
for (int i = 1; i < h; ++i) {
for (int j = 0; j < n; ++j)
dat[i][j] = OP(dat[i-1][j], dat[i-1][min(j+(1<<(i-1)),n-1)]);
}
}
void init(const vector<MeetSemiLattice> &vec, const Func &op) {
OP = op;
init(vec);
}
MeetSemiLattice get(int a, int b) {
return OP(dat[height[b-a]][a], dat[height[b-a]][b-(1<<height[b-a])]);
}
};
#line 4 "Optimization/anti_monge_dd_smawk.hpp"
using namespace std;
#line 4 "Optimization/smawk.hpp"
using namespace std;
// find min_j f(i, j) for all i, by SMAWK, O(H + W)
// f(i, j) must be totally monotone
// slide access NG
template<class VAL, class FUNC> void SMAWKRec
(const vector<int> &X, const vector<int> &Y, const FUNC &f, vector<pair<VAL, int>> &res) {
if (X.empty()) return;
// Reduce Step
vector<int> X2, Y2;
for (auto y : Y) {
while (!Y2.empty()) {
int py = Y2.back(), x = X[(int)Y2.size() - 1];
if (f(x, y) >= f(x, py)) break;
Y2.pop_back();
}
if (Y2.size() < X.size()) Y2.emplace_back(y);
}
// Recurse Step
for (int i = 1; i < (int)X.size(); i += 2) X2.emplace_back(X[i]);
SMAWKRec(X2, Y2, f, res);
// Interpolate Step
int p = 0;
for (int i = 0; i < (int)X.size(); i += 2) {
int lim = (i + 1 < (int)X.size() ? res[X[i + 1]].second : Y.back()), best = Y[p];
while (Y[p] < lim) {
p++;
if (f(X[i], Y[p]) < f(X[i], best)) best = Y[p];
}
res[X[i]] = {f(X[i], best), best};
}
}
template<class VAL, class FUNC> vector<pair<VAL, int>> SMAWK(int H, int W, const FUNC &f) {
if (H == 0) return {};
assert(W > 0);
vector<pair<VAL, int>> res(H, make_pair(numeric_limits<VAL>::max() / 2, -1));
vector<int> X(H), Y(W);
for (int i = 0; i < H; i++) X[i] = i;
for (int j = 0; j < W; j++) Y[j] = j;
SMAWKRec(X, Y, f, res);
return res;
}
#line 7 "Optimization/anti_monge_dd_smawk.hpp"
// find shortest path on DAG with anti-Monge cost, by D&D SMAWK, O(NK log N)
// vertex: 0, 1, 2, ..., N
// f(i, j) must be anti-Monge in j >= i + K
// Then, A(j, i) = dp[i] + f(i, j) is also anti-Monge
// slide access NG
template<class VAL, class FUNC> vector<pair<VAL, int>> antiMongeDDSMAWK(int N, const FUNC &f, int K = 1) {
assert(K >= 1);
const VAL INF = numeric_limits<VAL>::max() / 4;
vector<pair<VAL, int>> res(N + 1, make_pair(INF, -1));
vector<pair<VAL, int>> tmp(N + 1, {INF, -1});
res[0].first = VAL(0);
auto relax = [&](int i, int j) -> void {
if (i != 0 && res[i].second == -1) return;
VAL val = res[i].first + f(i, j);
if (val < res[j].first) res[j] = {val, i};
};
auto rec = [&](auto &&rec, int left, int right) -> void {
if (right - left <= 1) return;
int mid = (left + right) / 2, border = min(right, mid + K - 1);
rec(rec, left, mid);
for (int j = mid; j < border; j++) {
for (int i = left; i < mid && i <= j - K; i++) relax(i, j);
}
if (border < right) {
vector<int> X, Y;
for (int j = border; j < right; j++) X.push_back(j);
for (int i = mid - 1; i >= left; i--) {
if (i == 0 || res[i].second != -1) Y.push_back(i);
}
if (!Y.empty()) {
vector<int> cols(Y.size());
iota(cols.begin(), cols.end(), 0);
auto f2 = [&](int j, int k) -> VAL { return res[Y[k]].first + f(Y[k], j); };
SMAWKRec(X, cols, f2, tmp);
for (auto x : X) {
if (tmp[x].first < res[x].first) res[x] = {tmp[x].first, Y[tmp[x].second]};
}
}
}
rec(rec, mid, right);
};
rec(rec, 0, N + 1);
return res;
}
#line 5 "tests/AtCoder/ABC_480_G_anti_monge_dd_smawk.cpp"
int main() {
int N;
cin >> N;
vector<long long> A(N);
for (int i = 0; i < N; ++i) cin >> A[i];
SparseTable<long long> stmi(A);
SparseTable<long long> stma(A, [&](long long p, long long q){return max(p, q);});
auto func = [&](int l, int r) -> long long {
assert(r - l >= 2);
return stma.get(l, r) - stmi.get(l, r);
};
auto res = antiMongeDDSMAWK<long long>(N, func, 2);
cout << res.back().first << endl;
}