結果
| 問題 |
No.738 平らな農地
|
| ユーザー |
 kcvlex
|
| 提出日時 | 2020-05-15 19:18:40 |
| 言語 | C++17(gcc12) (gcc 12.3.0 + boost 1.87.0) |
| 結果 |
RE
|
| 実行時間 | - |
| コード長 | 11,051 bytes |
| コンパイル時間 | 7,144 ms |
| コンパイル使用メモリ | 198,408 KB |
| 最終ジャッジ日時 | 2025-01-10 11:09:28 |
|
ジャッジサーバーID （参考情報） |
judge3 / judge4 |
（要ログイン）
| ファイルパターン | 結果 |
|---|---|
| sample | AC * 5 |
| other | AC * 3 WA * 1 RE * 81 TLE * 2 |
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>
// Yay!!
#define endl codeforces
// macros for iterator
#define ALL(v) std::begin(v), std::end(v)
#define ALLR(v) std::rbegin(v), std::rend(v)
// alias
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>;
template <typename T> using vec = std::vector<T>;
template <typename T> using vvec = vec<vec<T>>;
// variadic min/max
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...)); }
// variadic chmin/chmax
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...); }
// multi demension array
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;
// fill container
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 (ssize_t i = 0; i < t.size(); i++) fill_seq(t[i], f, args..., i); } }
// make multi dimension vector
template <typename T> vec<T> make_v(ssize_t sz) { return vec<T>(sz); }
template <typename T, typename... Tail> auto make_v(ssize_t hs, Tail&&... ts) { auto v = std::move(make_v<T>(std::forward<Tail>(ts)...)); return vec<decltype(v)>(hs, v); }
// init
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;
}
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_popcount(n);
}
// 0 indexed
template <typename T>
auto msb(T n) -> validate_integer<T> {
return 64 - __builtin_clzll(n) - 1;
}
template <typename T>
constexpr auto ceil_pow2(T s) -> validate_integer<T> {
ll ret = 1;
while (ret < s) ret *= 2;
return ret;
}
}
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 <std::size_t MaxSize>
struct FullyIndexableDictionary {
using size_type = ssize_t;
private:
constexpr static size_type sz_log2 = 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> dat;
vec<size_type> chunk;
vvec<size_type> block;
public:
FullyIndexableDictionary() { }
template <typename F>
FullyIndexableDictionary(F f, size_type sz)
: sz(sz), cnt1(0),
dat(utility::ceil_div(sz, block_sz), 0),
chunk(utility::ceil_div(sz, chunk_sz)),
block(make_v<size_type>(chunk.size(), block_per_chunk))
{
for (size_type i = 0; i < chunk.size(); i++) {
chunk[i] = cnt1;
size_type tmp = 0;
for (size_type j = 0; j < block[i].size(); j++) {
block[i][j] = tmp;
for (size_type k = 0; k < block_sz; k++) {
size_type idx = i * chunk_sz + j * block_sz;
auto v = f(idx + k);
size_type mask = (1ll << k) * v;
dat[i * block_per_chunk + j] |= mask;
tmp += v;
}
}
cnt1 += tmp;
}
}
size_type rank(bool b, size_type pos) const {
if (!b) return pos - rank(!b, pos);
size_type ret = 0, idx = 0;
size_type i = pos / chunk_sz;
pos %= chunk_sz;
idx += i * chunk_sz * block_per_chunk;
ret += chunk[i];
size_type j = pos / block_sz;
pos %= block_sz;
idx += j * block_sz;
ret += block[i][j];
auto mask = (1ll << pos) - 1;
return ret + utility::popcount(dat[idx] & 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 {
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 {
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);
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 >= 0
T quantile(size_type l, size_type r, size_type k) const {
T ret = 0;
for (size_type i = 0; i < MaxValueLog; 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);
}
};
}
const std::size_t SIZE = 1e5 + 10;
const ll inf = 5e15;
int main() {
ll n, k;
std::cin >> n >> k;
vec<ll> av(n);
for (auto &&e : av) std::cin >> e;
ll ans = inf;
succinct::WaveletMatrix<ll, SIZE> wm(av);
for (ll i = 0; i + k <= n; i++) {
ll mode = wm.quantile(i, i + k, k / 2);
ll cost = 0;
cost += mode * wm.range_freq(i, i + k, 0, mode) - wm.range_sum(i, i + k, 0, mode);
cost += wm.range_sum(i, i + k, mode, inf) - mode * wm.range_freq(i, i + k, mode, inf);
chmin(ans, cost);
}
std::cout << ans << "\n";
return 0;
}