結果
問題 | No.1332 Range Nearest Query |
ユーザー |
![]() |
提出日時 | 2021-01-08 23:21:06 |
言語 | C++17 (gcc 13.3.0 + boost 1.87.0) |
結果 |
TLE
|
実行時間 | - |
コード長 | 11,206 bytes |
コンパイル時間 | 2,721 ms |
コンパイル使用メモリ | 162,764 KB |
最終ジャッジ日時 | 2025-01-17 14:40:05 |
ジャッジサーバーID (参考情報) |
judge5 / judge2 |
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ファイルパターン | 結果 |
---|---|
other | AC * 27 TLE * 21 |
ソースコード
#include <limits>#include <initializer_list>#include <utility>#include <bitset>#include <tuple>#include <type_traits>#include <functional>#include <string>#include <array>#include <deque>#include <list>#include <queue>#include <stack>#include <vector>#include <map>#include <set>#include <unordered_map>#include <unordered_set>#include <iterator>#include <algorithm>#include <complex>#include <random>#include <numeric>#include <iostream>#include <iomanip>#include <sstream>#include <regex>#include <cassert>#include <cstddef>#include <variant>#define endl codeforces#define ALL(v) std::begin(v), std::end(v)#define ALLR(v) std::rbegin(v), std::rend(v)using ll = std::int64_t;using ull = std::uint64_t;using pii = std::pair<int, int>;using tii = std::tuple<int, int, int>;using pll = std::pair<ll, ll>;using tll = std::tuple<ll, ll, ll>;using size_type = ssize_t;template <typename T> using vec = std::vector<T>;template <typename T> using vvec = vec<vec<T>>;template <typename T> const T& var_min(const T &t) { return t; }template <typename T> const T& var_max(const T &t) { return t; }template <typename T, typename... Tail> const T& var_min(const T &t, const Tail&... tail) { return std::min(t, var_min(tail...)); }template <typename T, typename... Tail> const T& var_max(const T &t, const Tail&... tail) { return std::max(t, var_max(tail...)); }template <typename T, typename... Tail> void chmin(T &t, const Tail&... tail) { t = var_min(t, tail...); }template <typename T, typename... Tail> void chmax(T &t, const Tail&... tail) { t = var_max(t, tail...); }template <typename T, std::size_t Head, std::size_t... Tail>struct multi_dim_array { using type = std::array<typename multi_dim_array<T, Tail...>::type, Head>; };template <typename T, std::size_t Head>struct multi_dim_array<T, Head> { using type = std::array<T, Head>; };template <typename T, std::size_t... Args> using mdarray = typename multi_dim_array<T, Args...>::type;template <typename T, typename F, typename... Args>void fill_seq(T &t, F f, Args... args) {if constexpr (std::is_invocable<F, Args...>::value) {t = f(args...);} else {for (size_type i = 0; i < t.size(); i++) fill_seq(t[i], f, args..., i);}}template <typename T> vec<T> make_v(size_type sz) { return vec<T>(sz); }template <typename T, typename... Tail>auto make_v(size_type hs, Tail&&... ts) {auto v = std::move(make_v<T>(std::forward<Tail>(ts)...));return vec<decltype(v)>(hs, v);}namespace init__ {struct InitIO {InitIO() {std::cin.tie(nullptr);std::ios_base::sync_with_stdio(false);std::cout << std::fixed << std::setprecision(30);}} init_io;}template <typename T>T ceil_pow2(T bound) {T ret = 1;while (ret < bound) ret *= 2;return ret;}template <typename T>T ceil_div(T a, T b) { return a / b + !!(a % b); }namespace utility {template <typename T>using validate_integer = typename std::enable_if<std::is_integral<T>::value, ll>::type;template <typename T>auto popcount(T n) -> validate_integer<T> {return __builtin_popcountll(n);}// 0 indexedtemplate <typename T>auto msb(T n) -> validate_integer<T> {return 64 - __builtin_clzll(n) - 1;}}namespace utility {constexpr ll ceil_div(ll a, ll b) {return a / b + !!(a % b);}}namespace succinct {template <typename T>constexpr T ceil_log2(T n) {for (int i = 0; i < 63; i++) {T mask = 1ll << i;if (n <= mask) return i;}return -1;}template <typename T>constexpr T ceil_even(T n) {return n + (n & 1);}template <std::size_t MaxSize>struct FullyIndexableDictionary {using size_type = ssize_t;private:constexpr static size_type sz_log2 = ceil_even(ceil_log2<size_type>(MaxSize));constexpr static size_type chunk_sz = sz_log2 * sz_log2;constexpr static size_type block_sz = sz_log2 / 2;constexpr static size_type block_per_chunk = chunk_sz / block_sz;size_type sz, cnt1;vec<size_type> chunk, block, dat;public:FullyIndexableDictionary() { }template <typename F>FullyIndexableDictionary(F f, size_type sz): sz(sz), cnt1(0),chunk(utility::ceil_div(sz, chunk_sz)),block(chunk.size() * block_per_chunk),dat(block.size()){size_type idx = 0;for (size_type i = 0; i < chunk.size(); i++) {chunk[i] = cnt1;size_type tmp = 0;for (size_type j = 0; j < block_per_chunk; j++, idx++) {block[idx] = tmp;for (size_type k = 0; k < block_sz; k++) {auto v = f(idx * block_sz + k);size_type mask = (1ll << k) * v;dat[idx] |= mask;tmp += v;}}cnt1 += tmp;}}size_type rank(bool b, size_type pos) const {if (!b) return pos - rank(!b, pos);if (pos == sz) return sum(b);size_type ret = 0;ret += chunk[pos / chunk_sz];ret += block[pos / block_sz];auto mask = (1ll << (pos % block_sz)) - 1;return ret + utility::popcount(dat[pos / block_sz] & mask);}size_type rank(bool b, size_type l, size_type r) const {return rank(b, r) - rank(b, l);}size_type select(bool b, size_type n) const {if (rank(b, sz) < n) return -1;size_type ok = sz, ng = 0;while (1 < std::abs(ok - ng)) {size_type mid = (ok + ng) / 2;(n <= rank(b, mid) ? ok : ng) = mid;}return ok;}bool operator [](size_type i) const {size_type offset = i % block_sz;return (dat[i / block_sz] >> offset) & 1;}size_type sum(bool b) const {return b ? cnt1 : sz - cnt1;}};}namespace succinct {template <typename T, std::size_t MaxSize, std::size_t MaxValueLog = 32>class WaveletMatrix {using data_type = FullyIndexableDictionary<MaxSize>;public:using size_type = typename data_type::size_type;private:size_type sz;std::array<data_type, MaxValueLog> mat;std::array<vec<size_type>, MaxValueLog> acc_sum;void update_range_aux(bool bt, size_type &l, size_type &r, size_type i) const {const auto &dic = mat[i];l = dic.rank(bt, l) + bt * dic.sum(0);r = dic.rank(bt, r) + bt * dic.sum(0);}size_type range_freq_aux(size_type l, size_type r, T bound) const {if ((1ll << MaxValueLog) - 1 <= bound) return r - l;size_type ret = 0;for (size_type i = 0; i < MaxValueLog && l < r; i++) {T mask = 1ll << (MaxValueLog - (i + 1));bool bt = !!(bound & mask);if (bt) ret += mat[i].rank(0, l, r);update_range_aux(bt, l, r, i);}return ret;}size_type range_sum_aux(size_type l, size_type r, T bound) const {if ((1ll << MaxValueLog) - 1 <= bound) return acc_sum[0][r] - acc_sum[0][l];T ret = 0;for (size_type i = 0; i < MaxValueLog && l < r; i++) {T mask = 1ll << (MaxValueLog - (i + 1));bool bt = !!(bound & mask);if (bt) ret += acc_sum[i][r] - acc_sum[i][l];update_range_aux(bt, l, r, i);}return ret;}public:WaveletMatrix(vec<T> dat) : sz(dat.size()) {vec<T> buf(sz);for (size_type i = 0; i < MaxValueLog; i++) {size_type mask = 1ll << (MaxValueLog - i - 1);auto f = [&](size_type idx) -> bool {if (dat.size() <= idx) return false;return !!(dat[idx] & mask);};mat[i] = std::move(data_type(f, dat.size()));size_type l = 0, r = 0;acc_sum[i].resize(sz + 1, 0);for (size_type j = 0; j < dat.size(); j++) {auto e = dat[j];if (e & mask) {r++;buf[sz - r] = e;} else {buf[l] = e;acc_sum[i][j + 1] += e;l++;}}for (size_type k = 0; k < dat.size(); k++) acc_sum[i][k + 1] += acc_sum[i][k];std::reverse(buf.begin() + l, buf.end());std::swap(buf, dat);}}size_type rank(T t, size_type pos) const {size_type mask = 1ll << (MaxValueLog - 1);size_type l = 0, r = pos;for (size_type i = 0; i < MaxValueLog; i++, mask /= 2) {bool bt = !!(t & mask);update_range_aux(bt, l, r, i);}return r - l;}size_type select(T t, size_type n) const {std::array<size_type, MaxValueLog> larr, rarr;size_type l = 0, r = sz;for (size_type i = 0, mask = (1ll << (MaxValueLog - 1)); i < MaxValueLog; i++, mask /= 2) {larr[i] = l, rarr[i] = r;bool bt = !!(t & mask);update_range_aux(bt, l, r, i);}for (size_type i = 0, mask = 1; i < MaxValueLog; i++, mask *= 2) {size_type idx = MaxValueLog - (i + 1);const auto &dic = mat[idx];bool bt = !!(t & mask);n += dic.rank(bt, larr[idx]);size_type ra = dic.sel(bt, n);if (ra == -1) return -1;n = ra;}return n;}// k >= 0T quantile(size_type l, size_type r, size_type k) const {T ret = 0;for (size_type i = 0; i < MaxValueLog && l < r; i++) {T mask = 1ll << (MaxValueLog - (i + 1));const auto &dic = mat[i];size_type cl = dic.rank(1, l), cr = dic.rank(1, r);if (k < cr - cl) {l = cl + dic.sum(0);r = cr + dic.sum(0);ret |= mask;} else {k -= cr - cl;l -= cl;r -= cr;}}return ret;}// [l, r), [min, max)size_type range_freq(size_type l, size_type r, T min, T max) const {return range_freq_aux(l, r, max) - range_freq_aux(l, r, min);}size_type range_sum(size_type l, size_type r, T min, T max) const {return range_sum_aux(l, r, max) - range_sum_aux(l, r, min);}};}#pragma GCC target("avx2")#pragma GCC optimize("O3")#pragma GCC optimize("unroll-loops")int main() {ll n;std::cin >> n;vec<ll> xv(n);for (ll &e : xv) std::cin >> e;ll q;std::cin >> q;auto mat = succinct::WaveletMatrix<ll, ll(3e5 + 10), 32>(xv);const ll inf = 1e9 + 10;while (q--) {ll l, r, x;std::cin >> l >> r >> x;l--;ll ok = inf, ng = -1;while (std::abs(ok - ng) > 1) {const ll mid = (ok + ng) / 2;const ll lb = std::max<ll>(0, x - mid);const ll ub = x + mid + 1;const ll cnt = mat.range_freq(l, r, lb, ub);(cnt ? ok : ng) = mid;}std::cout << ok << "\n";}return 0;}