This documentation is automatically generated by online-judge-tools/verification-helper
#include "ds/kdtree/dual_kdtree_monoid.hpp"
// 矩形作用と点取得
template <class Monoid, typename XY>
struct Dual_KDTree_Monoid {
using MA = Monoid;
using A = typename Monoid::value_type;
// 小数も考慮すると、閉で持つ設計方針になる。ただし、クエリはいつもの半開を使う
vc<tuple<XY, XY, XY, XY>> closed_range;
vc<A> lazy;
vc<int> size;
vc<int> where;
int n, log;
Dual_KDTree_Monoid(vc<XY> xs, vc<XY> ys) : n(len(xs)) {
assert(n > 0);
log = 0;
while ((1 << log) < n) ++log;
lazy.resize(1 << (log + 1), MA::unit());
closed_range.resize(1 << (log + 1));
size.resize(1 << (log + 1));
where.resize(n);
vc<int> I(n);
iota(all(I), 0);
build(1, xs, ys, I);
}
// [xl, xr) x [yl, yr)
void apply(XY xl, XY xr, XY yl, XY yr, A a) {
assert(xl <= xr && yl <= yr);
return apply_rec(1, xl, xr, yl, yr, a);
}
// コンストラクタで渡したインデックス
A get(int i) {
i = where[i];
FOR_R(k, 1, log + 1) { push(i >> k); }
return lazy[i];
}
private:
void build(int idx, vc<XY> xs, vc<XY> ys, vc<int> raw_idx, bool divx = true) {
int n = len(xs);
size[idx] = n;
auto& [xmin, xmax, ymin, ymax] = closed_range[idx];
xmin = ymin = infty<XY>;
xmax = ymax = -infty<XY>;
FOR(i, n) {
auto x = xs[i], y = ys[i];
chmin(xmin, x), chmax(xmax, x), chmin(ymin, y), chmax(ymax, y);
}
if (xmin == xmax && ymin == ymax) {
assert(len(raw_idx) == 1);
where[raw_idx[0]] = idx;
return;
}
int m = n / 2;
vc<int> I(n);
iota(all(I), 0);
if (divx) {
nth_element(I.begin(), I.begin() + m, I.end(),
[xs](int i, int j) { return xs[i] < xs[j]; });
} else {
nth_element(I.begin(), I.begin() + m, I.end(),
[ys](int i, int j) { return ys[i] < ys[j]; });
}
xs = rearrange(xs, I), ys = rearrange(ys, I),
raw_idx = rearrange(raw_idx, I);
build(2 * idx + 0, {xs.begin(), xs.begin() + m},
{ys.begin(), ys.begin() + m}, {raw_idx.begin(), raw_idx.begin() + m},
!divx);
build(2 * idx + 1, {xs.begin() + m, xs.end()}, {ys.begin() + m, ys.end()},
{raw_idx.begin() + m, raw_idx.end()}, !divx);
}
inline bool is_leaf(int idx) {
auto& [xmin, xmax, ymin, ymax] = closed_range[idx];
return xmin == xmax && ymin == ymax;
}
inline bool isin(XY x, XY y, int idx) {
auto& [xmin, xmax, ymin, ymax] = closed_range[idx];
return (xmin <= x && x <= xmax && ymin <= y && y <= ymax);
}
void apply_at(int idx, A a) { lazy[idx] = MA::op(lazy[idx], a); }
void push(int idx) {
if (lazy[idx] == MA::unit()) return;
apply_at(2 * idx + 0, lazy[idx]), apply_at(2 * idx + 1, lazy[idx]);
lazy[idx] = MA::unit();
}
void apply_rec(int idx, XY x1, XY x2, XY y1, XY y2, A a) {
auto& [xmin, xmax, ymin, ymax] = closed_range[idx];
if (x2 <= xmin || xmax < x1) return;
if (y2 <= ymin || ymax < y1) return;
if (x1 <= xmin && xmax < x2 && y1 <= ymin && ymax < y2) {
return apply_at(idx, a);
}
push(idx);
apply_rec(2 * idx + 0, x1, x2, y1, y2, a);
apply_rec(2 * idx + 1, x1, x2, y1, y2, a);
}
};
#line 1 "ds/kdtree/dual_kdtree_monoid.hpp"
// 矩形作用と点取得
template <class Monoid, typename XY>
struct Dual_KDTree_Monoid {
using MA = Monoid;
using A = typename Monoid::value_type;
// 小数も考慮すると、閉で持つ設計方針になる。ただし、クエリはいつもの半開を使う
vc<tuple<XY, XY, XY, XY>> closed_range;
vc<A> lazy;
vc<int> size;
vc<int> where;
int n, log;
Dual_KDTree_Monoid(vc<XY> xs, vc<XY> ys) : n(len(xs)) {
assert(n > 0);
log = 0;
while ((1 << log) < n) ++log;
lazy.resize(1 << (log + 1), MA::unit());
closed_range.resize(1 << (log + 1));
size.resize(1 << (log + 1));
where.resize(n);
vc<int> I(n);
iota(all(I), 0);
build(1, xs, ys, I);
}
// [xl, xr) x [yl, yr)
void apply(XY xl, XY xr, XY yl, XY yr, A a) {
assert(xl <= xr && yl <= yr);
return apply_rec(1, xl, xr, yl, yr, a);
}
// コンストラクタで渡したインデックス
A get(int i) {
i = where[i];
FOR_R(k, 1, log + 1) { push(i >> k); }
return lazy[i];
}
private:
void build(int idx, vc<XY> xs, vc<XY> ys, vc<int> raw_idx, bool divx = true) {
int n = len(xs);
size[idx] = n;
auto& [xmin, xmax, ymin, ymax] = closed_range[idx];
xmin = ymin = infty<XY>;
xmax = ymax = -infty<XY>;
FOR(i, n) {
auto x = xs[i], y = ys[i];
chmin(xmin, x), chmax(xmax, x), chmin(ymin, y), chmax(ymax, y);
}
if (xmin == xmax && ymin == ymax) {
assert(len(raw_idx) == 1);
where[raw_idx[0]] = idx;
return;
}
int m = n / 2;
vc<int> I(n);
iota(all(I), 0);
if (divx) {
nth_element(I.begin(), I.begin() + m, I.end(),
[xs](int i, int j) { return xs[i] < xs[j]; });
} else {
nth_element(I.begin(), I.begin() + m, I.end(),
[ys](int i, int j) { return ys[i] < ys[j]; });
}
xs = rearrange(xs, I), ys = rearrange(ys, I),
raw_idx = rearrange(raw_idx, I);
build(2 * idx + 0, {xs.begin(), xs.begin() + m},
{ys.begin(), ys.begin() + m}, {raw_idx.begin(), raw_idx.begin() + m},
!divx);
build(2 * idx + 1, {xs.begin() + m, xs.end()}, {ys.begin() + m, ys.end()},
{raw_idx.begin() + m, raw_idx.end()}, !divx);
}
inline bool is_leaf(int idx) {
auto& [xmin, xmax, ymin, ymax] = closed_range[idx];
return xmin == xmax && ymin == ymax;
}
inline bool isin(XY x, XY y, int idx) {
auto& [xmin, xmax, ymin, ymax] = closed_range[idx];
return (xmin <= x && x <= xmax && ymin <= y && y <= ymax);
}
void apply_at(int idx, A a) { lazy[idx] = MA::op(lazy[idx], a); }
void push(int idx) {
if (lazy[idx] == MA::unit()) return;
apply_at(2 * idx + 0, lazy[idx]), apply_at(2 * idx + 1, lazy[idx]);
lazy[idx] = MA::unit();
}
void apply_rec(int idx, XY x1, XY x2, XY y1, XY y2, A a) {
auto& [xmin, xmax, ymin, ymax] = closed_range[idx];
if (x2 <= xmin || xmax < x1) return;
if (y2 <= ymin || ymax < y1) return;
if (x1 <= xmin && xmax < x2 && y1 <= ymin && ymax < y2) {
return apply_at(idx, a);
}
push(idx);
apply_rec(2 * idx + 0, x1, x2, y1, y2, a);
apply_rec(2 * idx + 1, x1, x2, y1, y2, a);
}
};