This documentation is automatically generated by online-judge-tools/verification-helper
// competitive-verifier: PROBLEM https://judge.yosupo.jp/problem/rectangle_sum
#include "../../template/template.hpp"
#include "../../structure/wavelet/succinct-indexable-dictionary.hpp"
#include "../../structure/wavelet/wavelet-matrix-rectangle-sum.hpp"
int main() {
int N, Q;
cin >> N >> Q;
vector< int > x(N), y(N), w(N);
vector< pair< int, int > > xs(N);
for(int i = 0; i < N; i++) {
cin >> x[i] >> y[i] >> w[i];
xs[i] = {x[i], i};
}
sort(begin(xs), end(xs));
vector< int > ys(N);
vector< int64 > ws(N);
for(int i = 0; i < N; i++) {
x[i] = lower_bound(begin(xs), end(xs), make_pair(x[i], i)) - begin(xs);
ys[x[i]] = y[i];
ws[x[i]] = w[i];
}
CompressedWaveletMatrixRectangleSum< int, 18, int64 > mat(ys, ws);
while(Q--) {
int l, r, d, u;
cin >> l >> d >> r >> u;
l = lower_bound(begin(xs), end(xs), make_pair(l, -1)) - begin(xs);
r = lower_bound(begin(xs), end(xs), make_pair(r, -1)) - begin(xs);
cout << mat.rect_sum(l, r, d, u) << "\n";
}
}
#line 1 "test/verify/yosupo-rectangle-sum.test.cpp"
// competitive-verifier: PROBLEM https://judge.yosupo.jp/problem/rectangle_sum
#line 1 "template/template.hpp"
#include<bits/stdc++.h>
using namespace std;
using int64 = long long;
const int64 infll = (1LL << 62) - 1;
const int inf = (1 << 30) - 1;
struct IoSetup {
IoSetup() {
cin.tie(nullptr);
ios::sync_with_stdio(false);
cout << fixed << setprecision(10);
cerr << fixed << setprecision(10);
}
} iosetup;
template< typename T1, typename T2 >
ostream &operator<<(ostream &os, const pair< T1, T2 >& p) {
os << p.first << " " << p.second;
return os;
}
template< typename T1, typename T2 >
istream &operator>>(istream &is, pair< T1, T2 > &p) {
is >> p.first >> p.second;
return is;
}
template< typename T >
ostream &operator<<(ostream &os, const vector< T > &v) {
for(int i = 0; i < (int) v.size(); i++) {
os << v[i] << (i + 1 != v.size() ? " " : "");
}
return os;
}
template< typename T >
istream &operator>>(istream &is, vector< T > &v) {
for(T &in : v) is >> in;
return is;
}
template< typename T1, typename T2 >
inline bool chmax(T1 &a, T2 b) { return a < b && (a = b, true); }
template< typename T1, typename T2 >
inline bool chmin(T1 &a, T2 b) { return a > b && (a = b, true); }
template< typename T = int64 >
vector< T > make_v(size_t a) {
return vector< T >(a);
}
template< typename T, typename... Ts >
auto make_v(size_t a, Ts... ts) {
return vector< decltype(make_v< T >(ts...)) >(a, make_v< T >(ts...));
}
template< typename T, typename V >
typename enable_if< is_class< T >::value == 0 >::type fill_v(T &t, const V &v) {
t = v;
}
template< typename T, typename V >
typename enable_if< is_class< T >::value != 0 >::type fill_v(T &t, const V &v) {
for(auto &e : t) fill_v(e, v);
}
template< typename F >
struct FixPoint : F {
explicit FixPoint(F &&f) : F(forward< F >(f)) {}
template< typename... Args >
decltype(auto) operator()(Args &&... args) const {
return F::operator()(*this, forward< Args >(args)...);
}
};
template< typename F >
inline decltype(auto) MFP(F &&f) {
return FixPoint< F >{forward< F >(f)};
}
#line 4 "test/verify/yosupo-rectangle-sum.test.cpp"
#line 1 "structure/wavelet/succinct-indexable-dictionary.hpp"
/**
* @brief Succinct Indexable Dictionary(完備辞書)
*/
struct SuccinctIndexableDictionary {
size_t length;
size_t blocks;
vector< unsigned > bit, sum;
SuccinctIndexableDictionary() = default;
SuccinctIndexableDictionary(size_t length) : length(length), blocks((length + 31) >> 5) {
bit.assign(blocks, 0U);
sum.assign(blocks, 0U);
}
void set(int k) {
bit[k >> 5] |= 1U << (k & 31);
}
void build() {
sum[0] = 0U;
for(int i = 1; i < blocks; i++) {
sum[i] = sum[i - 1] + __builtin_popcount(bit[i - 1]);
}
}
bool operator[](int k) {
return (bool((bit[k >> 5] >> (k & 31)) & 1));
}
int rank(int k) {
return (sum[k >> 5] + __builtin_popcount(bit[k >> 5] & ((1U << (k & 31)) - 1)));
}
int rank(bool val, int k) {
return (val ? rank(k) : k - rank(k));
}
};
#line 1 "structure/wavelet/wavelet-matrix-rectangle-sum.hpp"
/*
* @brief Wavelet Matrix Rectangle Sum
*
*/
template< typename T, int MAXLOG, typename D >
struct WaveletMatrixRectangleSum {
size_t length;
SuccinctIndexableDictionary matrix[MAXLOG];
vector< D > ds[MAXLOG];
int mid[MAXLOG];
WaveletMatrixRectangleSum() = default;
WaveletMatrixRectangleSum(const vector< T > &v, const vector< D > &d) : length(v.size()) {
assert(v.size() == d.size());
vector< int > l(length), r(length), ord(length);
iota(begin(ord), end(ord), 0);
for(int level = MAXLOG - 1; level >= 0; level--) {
matrix[level] = SuccinctIndexableDictionary(length + 1);
int left = 0, right = 0;
for(int i = 0; i < length; i++) {
if(((v[ord[i]] >> level) & 1)) {
matrix[level].set(i);
r[right++] = ord[i];
} else {
l[left++] = ord[i];
}
}
mid[level] = left;
matrix[level].build();
ord.swap(l);
for(int i = 0; i < right; i++) {
ord[left + i] = r[i];
}
ds[level].resize(length + 1);
ds[level][0] = D();
for(int i = 0; i < length; i++) {
ds[level][i + 1] = ds[level][i] + d[ord[i]];
}
}
}
pair< int, int > succ(bool f, int l, int r, int level) {
return {matrix[level].rank(f, l) + mid[level] * f, matrix[level].rank(f, r) + mid[level] * f};
}
// count d[i] s.t. (l <= i < r) && (v[i] < upper)
D rect_sum(int l, int r, T upper) {
D ret = 0;
for(int level = MAXLOG - 1; level >= 0; level--) {
bool f = ((upper >> level) & 1);
if(f) ret += ds[level][matrix[level].rank(false, r)] - ds[level][matrix[level].rank(false, l)];
tie(l, r) = succ(f, l, r, level);
}
return ret;
}
D rect_sum(int l, int r, T lower, T upper) {
return rect_sum(l, r, upper) - rect_sum(l, r, lower);
}
};
template< typename T, int MAXLOG, typename D >
struct CompressedWaveletMatrixRectangleSum {
WaveletMatrixRectangleSum< int, MAXLOG, D > mat;
vector< T > ys;
CompressedWaveletMatrixRectangleSum(const vector< T > &v, const vector< D > &d) : ys(v) {
sort(begin(ys), end(ys));
ys.erase(unique(begin(ys), end(ys)), end(ys));
vector< int > t(v.size());
for(int i = 0; i < v.size(); i++) t[i] = get(v[i]);
mat = WaveletMatrixRectangleSum< int, MAXLOG, D >(t, d);
}
inline int get(const T &x) {
return lower_bound(begin(ys), end(ys), x) - begin(ys);
}
D rect_sum(int l, int r, T upper) {
return mat.rect_sum(l, r, get(upper));
}
D rect_sum(int l, int r, T lower, T upper) {
return mat.rect_sum(l, r, get(lower), get(upper));
}
};
#line 7 "test/verify/yosupo-rectangle-sum.test.cpp"
int main() {
int N, Q;
cin >> N >> Q;
vector< int > x(N), y(N), w(N);
vector< pair< int, int > > xs(N);
for(int i = 0; i < N; i++) {
cin >> x[i] >> y[i] >> w[i];
xs[i] = {x[i], i};
}
sort(begin(xs), end(xs));
vector< int > ys(N);
vector< int64 > ws(N);
for(int i = 0; i < N; i++) {
x[i] = lower_bound(begin(xs), end(xs), make_pair(x[i], i)) - begin(xs);
ys[x[i]] = y[i];
ws[x[i]] = w[i];
}
CompressedWaveletMatrixRectangleSum< int, 18, int64 > mat(ys, ws);
while(Q--) {
int l, r, d, u;
cin >> l >> d >> r >> u;
l = lower_bound(begin(xs), end(xs), make_pair(l, -1)) - begin(xs);
r = lower_bound(begin(xs), end(xs), make_pair(r, -1)) - begin(xs);
cout << mat.rect_sum(l, r, d, u) << "\n";
}
}
Env | Name | Status | Elapsed | Memory |
---|---|---|---|---|
g++ | example_00 | AC | 6 ms | 4 MB |
g++ | max_random_00 | AC | 597 ms | 42 MB |
g++ | max_random_01 | AC | 569 ms | 42 MB |
g++ | max_random_02 | AC | 604 ms | 42 MB |
g++ | n_131072_00 | AC | 322 ms | 29 MB |
g++ | random_00 | AC | 350 ms | 28 MB |
g++ | random_01 | AC | 383 ms | 33 MB |
g++ | random_02 | AC | 211 ms | 14 MB |
g++ | small_00 | AC | 7 ms | 4 MB |
g++ | small_01 | AC | 6 ms | 4 MB |
g++ | small_02 | AC | 6 ms | 4 MB |
g++ | xy_concentrate_00 | AC | 515 ms | 42 MB |
g++ | xy_concentrate_01 | AC | 515 ms | 42 MB |
g++ | xy_concentrate_02 | AC | 514 ms | 42 MB |
clang++ | example_00 | AC | 6 ms | 4 MB |
clang++ | max_random_00 | AC | 538 ms | 42 MB |
clang++ | max_random_01 | AC | 541 ms | 42 MB |
clang++ | max_random_02 | AC | 547 ms | 42 MB |
clang++ | n_131072_00 | AC | 313 ms | 29 MB |
clang++ | random_00 | AC | 343 ms | 28 MB |
clang++ | random_01 | AC | 376 ms | 33 MB |
clang++ | random_02 | AC | 207 ms | 14 MB |
clang++ | small_00 | AC | 7 ms | 4 MB |
clang++ | small_01 | AC | 7 ms | 4 MB |
clang++ | small_02 | AC | 6 ms | 4 MB |
clang++ | xy_concentrate_00 | AC | 514 ms | 43 MB |
clang++ | xy_concentrate_01 | AC | 504 ms | 42 MB |
clang++ | xy_concentrate_02 | AC | 517 ms | 42 MB |