結果
問題 |
No.1171 Runs in Subsequences
|
ユーザー |
|
提出日時 | 2025-08-03 03:52:55 |
言語 | C++17 (gcc 13.3.0 + boost 1.87.0) |
結果 |
WA
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実行時間 | - |
コード長 | 49,281 bytes |
コンパイル時間 | 5,662 ms |
コンパイル使用メモリ | 338,668 KB |
実行使用メモリ | 7,720 KB |
最終ジャッジ日時 | 2025-08-03 03:53:03 |
合計ジャッジ時間 | 6,944 ms |
ジャッジサーバーID (参考情報) |
judge4 / judge2 |
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ファイルパターン | 結果 |
---|---|
sample | AC * 3 WA * 1 |
other | AC * 6 WA * 12 |
ソースコード
#ifndef HIDDEN_IN_VS // 折りたたみ用 // 警告の抑制 #define _CRT_SECURE_NO_WARNINGS // ライブラリの読み込み #include <bits/stdc++.h> using namespace std; // 型名の短縮 using ll = long long; using ull = unsigned long long; // -2^63 ~ 2^63 = 9e18(int は -2^31 ~ 2^31 = 2e9) using pii = pair<int, int>; using pll = pair<ll, ll>; using pil = pair<int, ll>; using pli = pair<ll, int>; using vi = vector<int>; using vvi = vector<vi>; using vvvi = vector<vvi>; using vvvvi = vector<vvvi>; using vl = vector<ll>; using vvl = vector<vl>; using vvvl = vector<vvl>; using vvvvl = vector<vvvl>; using vb = vector<bool>; using vvb = vector<vb>; using vvvb = vector<vvb>; using vc = vector<char>; using vvc = vector<vc>; using vvvc = vector<vvc>; using vd = vector<double>; using vvd = vector<vd>; using vvvd = vector<vvd>; template <class T> using priority_queue_rev = priority_queue<T, vector<T>, greater<T>>; using Graph = vvi; // 定数の定義 const double PI = acos(-1); int DX[4] = { 1, 0, -1, 0 }; // 4 近傍(下,右,上,左) int DY[4] = { 0, 1, 0, -1 }; int INF = 1001001001; ll INFL = 4004004003094073385LL; // (int)INFL = INF, (int)(-INFL) = -INF; // 入出力高速化 struct fast_io { fast_io() { cin.tie(nullptr); ios::sync_with_stdio(false); cout << fixed << setprecision(18); } } fastIOtmp; // 汎用マクロの定義 #define all(a) (a).begin(), (a).end() #define sz(x) ((int)(x).size()) #define lbpos(a, x) (int)distance((a).begin(), std::lower_bound(all(a), (x))) #define ubpos(a, x) (int)distance((a).begin(), std::upper_bound(all(a), (x))) #define Yes(b) {cout << ((b) ? "Yes\n" : "No\n");} #define rep(i, n) for(int i = 0, i##_len = int(n); i < i##_len; ++i) // 0 から n-1 まで昇順 #define repi(i, s, t) for(int i = int(s), i##_end = int(t); i <= i##_end; ++i) // s から t まで昇順 #define repir(i, s, t) for(int i = int(s), i##_end = int(t); i >= i##_end; --i) // s から t まで降順 #define repe(v, a) for(const auto& v : (a)) // a の全要素(変更不可能) #define repea(v, a) for(auto& v : (a)) // a の全要素(変更可能) #define repb(set, d) for(int set = 0, set##_ub = 1 << int(d); set < set##_ub; ++set) // d ビット全探索(昇順) #define repis(i, set) for(int i = lsb(set), bset##i = set; i < 32; bset##i -= 1 << i, i = lsb(bset##i)) // set の全要素(昇順) #define repp(a) sort(all(a)); for(bool a##_perm = true; a##_perm; a##_perm = next_permutation(all(a))) // a の順列全て(昇順) #define uniq(a) {sort(all(a)); (a).erase(unique(all(a)), (a).end());} // 重複除去 #define EXIT(a) {cout << (a) << endl; exit(0);} // 強制終了 #define inQ(x, y, u, l, d, r) ((u) <= (x) && (l) <= (y) && (x) < (d) && (y) < (r)) // 半開矩形内判定 // 汎用関数の定義 template <class T> inline ll powi(T n, int k) { ll v = 1; rep(i, k) v *= n; return v; } template <class T> inline bool chmax(T& M, const T& x) { if (M < x) { M = x; return true; } return false; } // 最大値を更新(更新されたら true を返す) template <class T> inline bool chmin(T& m, const T& x) { if (m > x) { m = x; return true; } return false; } // 最小値を更新(更新されたら true を返す) template <class T> inline int getb(T set, int i) { return (set >> i) & T(1); } template <class T> inline T smod(T n, T m) { n %= m; if (n < 0) n += m; return n; } // 非負mod // 演算子オーバーロード template <class T, class U> inline istream& operator>>(istream& is, pair<T, U>& p) { is >> p.first >> p.second; return is; } template <class T> inline istream& operator>>(istream& is, vector<T>& v) { repea(x, v) is >> x; return is; } template <class T> inline vector<T>& operator--(vector<T>& v) { repea(x, v) --x; return v; } template <class T> inline vector<T>& operator++(vector<T>& v) { repea(x, v) ++x; return v; } #endif // 折りたたみ用 #if __has_include(<atcoder/all>) #include <atcoder/all> using namespace atcoder; #ifdef _MSC_VER #include "localACL.hpp" #endif //using mint = modint998244353; using mint = static_modint<(int)1e9+7>; //using mint = modint; // mint::set_mod(m); using vm = vector<mint>; using vvm = vector<vm>; using vvvm = vector<vvm>; using vvvvm = vector<vvvm>; using pim = pair<int, mint>; #endif #ifdef _MSC_VER // 手元環境(Visual Studio) #include "local.hpp" #else // 提出用(gcc) int mute_dump = 0; int frac_print = 0; #if __has_include(<atcoder/all>) namespace atcoder { inline istream& operator>>(istream& is, mint& x) { ll x_; is >> x_; x = x_; return is; } inline ostream& operator<<(ostream& os, const mint& x) { os << x.val(); return os; } } #endif inline int popcount(int n) { return __builtin_popcount(n); } inline int popcount(ll n) { return __builtin_popcountll(n); } inline int lsb(int n) { return n != 0 ? __builtin_ctz(n) : 32; } inline int lsb(ll n) { return n != 0 ? __builtin_ctzll(n) : 64; } inline int msb(int n) { return n != 0 ? (31 - __builtin_clz(n)) : -1; } inline int msb(ll n) { return n != 0 ? (63 - __builtin_clzll(n)) : -1; } #define dump(...) #define dumpel(v) #define dump_math(v) #define input_from_file(f) #define output_to_file(f) #define Assert(b) { if (!(b)) { vc MLE(1<<30); EXIT(MLE.back()); } } // RE の代わりに MLE を出す #endif // 愚直 mint naive(const string& s) { int n = sz(s); mint res = 0; repb(set, n) { char c = '-'; res++; repis(i, set) { if (c != '-') { if (c != s[i]) res++; } c = s[i]; } } return res - 1; } //【行列】 /* * Matrix<T>(int n, int m) : O(n m) * n×m 零行列で初期化する. * * Matrix<T>(int n) : O(n^2) * n×n 単位行列で初期化する. * * Matrix<T>(vvT a) : O(n m) * 二次元配列 a[0..n)[0..m) の要素で初期化する. * * bool empty() : O(1) * 行列が空かを返す. * * A + B : O(n m) * n×m 行列 A, B の和を返す.+= も使用可. * * A - B : O(n m) * n×m 行列 A, B の差を返す.-= も使用可. * * c * A / A * c : O(n m) * n×m 行列 A とスカラー c のスカラー積を返す.*= も使用可. * * A * x : O(n m) * n×m 行列 A と n 次元列ベクトル x の積を返す. * * x * A : O(n m)(やや遅い) * m 次元行ベクトル x と n×m 行列 A の積を返す. * * A * B : O(n m l) * n×m 行列 A と m×l 行列 B の積を返す. * * Mat pow(ll d) : O(n^3 log d) * 自身を d 乗した行列を返す. */ template <class T> struct Matrix { int n, m; // 行列のサイズ(n 行 m 列) vector<vector<T>> v; // 行列の成分 // n×m 零行列で初期化する. Matrix(int n, int m) : n(n), m(m), v(n, vector<T>(m)) {} // n×n 単位行列で初期化する. Matrix(int n) : n(n), m(n), v(n, vector<T>(n)) { rep(i, n) v[i][i] = T(1); } // 二次元配列 a[0..n)[0..m) の要素で初期化する. Matrix(const vector<vector<T>>& a) : n(sz(a)), m(sz(a[0])), v(a) {} Matrix() : n(0), m(0) {} // 代入 Matrix(const Matrix&) = default; Matrix& operator=(const Matrix&) = default; // アクセス inline vector<T> const& operator[](int i) const { return v[i]; } inline vector<T>& operator[](int i) { // verify : https://judge.yosupo.jp/problem/matrix_product // inline を付けて [] でアクセスするとなぜか v[] への直接アクセスより速くなった. return v[i]; } // 入力 friend istream& operator>>(istream& is, Matrix& a) { rep(i, a.n) rep(j, a.m) is >> a.v[i][j]; return is; } // 行の追加 void push_back(const vector<T>& a) { Assert(sz(a) == m); v.push_back(a); n++; } // 行の削除 void pop_back() { Assert(n > 0); v.pop_back(); n--; } // サイズ変更 void resize(int n_) { v.resize(n_); n = n_; } void resize(int n_, int m_) { n = n_; m = m_; v.resize(n); rep(i, n) v[i].resize(m); } // 空か bool empty() const { return min(n, m) == 0; } // 比較 bool operator==(const Matrix& b) const { return n == b.n && m == b.m && v == b.v; } bool operator!=(const Matrix& b) const { return !(*this == b); } // 加算,減算,スカラー倍 Matrix& operator+=(const Matrix& b) { rep(i, n) rep(j, m) v[i][j] += b[i][j]; return *this; } Matrix& operator-=(const Matrix& b) { rep(i, n) rep(j, m) v[i][j] -= b[i][j]; return *this; } Matrix& operator*=(const T& c) { rep(i, n) rep(j, m) v[i][j] *= c; return *this; } Matrix operator+(const Matrix& b) const { return Matrix(*this) += b; } Matrix operator-(const Matrix& b) const { return Matrix(*this) -= b; } Matrix operator*(const T& c) const { return Matrix(*this) *= c; } friend Matrix operator*(const T& c, const Matrix<T>& a) { return a * c; } Matrix operator-() const { return Matrix(*this) *= T(-1); } // 行列ベクトル積 : O(m n) vector<T> operator*(const vector<T>& x) const { vector<T> y(n); rep(i, n) rep(j, m) y[i] += v[i][j] * x[j]; return y; } // ベクトル行列積 : O(m n) friend vector<T> operator*(const vector<T>& x, const Matrix& a) { vector<T> y(a.m); rep(i, a.n) rep(j, a.m) y[j] += x[i] * a[i][j]; return y; } // 積:O(n^3) Matrix operator*(const Matrix& b) const { // verify : https://judge.yosupo.jp/problem/matrix_product Matrix res(n, b.m); rep(i, res.n) rep(k, m) rep(j, res.m) res[i][j] += v[i][k] * b[k][j]; return res; } Matrix& operator*=(const Matrix& b) { *this = *this * b; return *this; } // 累乗:O(n^3 log d) Matrix pow(ll d) const { // verify : https://judge.yosupo.jp/problem/pow_of_matrix Matrix res(n), pow2 = *this; while (d > 0) { if (d & 1) res *= pow2; pow2 *= pow2; d >>= 1; } return res; } #ifdef _MSC_VER friend ostream& operator<<(ostream& os, const Matrix& a) { rep(i, a.n) { os << "["; rep(j, a.m) os << a[i][j] << " ]"[j == a.m - 1]; if (i < a.n - 1) os << "\n"; } return os; } #endif }; //【行簡約形(行交換なし)】O(n m min(n, m)) /* * 行基本変形(行交換なし)で n×m 行列 A を行簡約形に変形し,ピボット位置のリストを返す. */ template <class T> vector<pii> row_reduced_form(Matrix<T>& A) { int n = A.n, m = A.m; vector<pii> piv; piv.reserve(min(n, m)); // 未確定の列を記録しておくリスト list<int> rjs; rep(j, m) rjs.push_back(j); rep(i, n) { // 第 i 行の係数を左から走査し非 0 を見つける. auto it = rjs.begin(); for (; it != rjs.end(); it++) if (A[i][*it] != 0) break; // 第 i 行の全てが 0 なら無視する. if (it == rjs.end()) continue; // A[i][j] をピボットに選択する. int j = *it; rjs.erase(it); piv.emplace_back(i, j); // A[i][j] が 1 になるよう行全体を A[i][j] で割る. T Aij_inv = T(1) / A[i][j]; repi(j2, j, m - 1) A[i][j2] *= Aij_inv; // 第 i 行以外の第 j 列の成分が全て 0 になるよう第 i 行を定数倍して減じる. rep(i2, n) if (A[i2][j] != 0 && i2 != i) { T mul = A[i2][j]; repi(j2, j, m - 1) A[i2][j2] -= A[i][j2] * mul; } } return piv; } //【逆行列】O(n^3) /* * n 次正方行列 mat の逆行列を返す(存在しなければ空) */ template <class T> Matrix<T> inverse_matrix(const Matrix<T>& mat) { // verify : https://judge.yosupo.jp/problem/inverse_matrix int n = mat.n; // 元の行列 mat と単位行列を繋げた拡大行列 v を作る. vector<vector<T>> v(n, vector<T>(2 * n)); rep(i, n) rep(j, n) { v[i][j] = mat[i][j]; if (i == j) v[i][n + j] = 1; } int m = 2 * n; // 注目位置を (i, j)(i 行目かつ j 列目)とする. int i = 0, j = 0; // 拡大行列に対して行基本変形を行い,左側を単位行列にすることを目指す. while (i < n && j < m) { // 同じ列の下方の行から非 0 成分を見つける. int i2 = i; while (i2 < n && v[i2][j] == T(0)) i2++; // 見つからなかったら全て 0 の列があったので mat は非正則 if (i2 == n) return Matrix<T>(); // 見つかったら i 行目とその行を入れ替える. if (i != i2) swap(v[i], v[i2]); // v[i][j] が 1 になるよう行全体を v[i][j] で割る. T vij_inv = T(1) / v[i][j]; repi(j2, j, m - 1) v[i][j2] *= vij_inv; // v[i][j] と同じ列の成分が全て 0 になるよう i 行目を定数倍して減じる. rep(i2, n) { // i 行目だけは引かない. if (i2 == i) continue; T mul = v[i2][j]; repi(j2, j, m - 1) v[i2][j2] -= v[i][j2] * mul; } // 注目位置を右下に移す. i++; j++; } // 拡大行列の右半分が mat の逆行列なのでコピーする. Matrix<T> mat_inv(n, n); rep(i, n) rep(j, n) mat_inv[i][j] = v[i][n + j]; return mat_inv; } // 遷移行列の係数を計算し,埋め込み用のコードを出力する. // 待てない場合は len_max とか LB_max とかを指定する. void embed_coefs(int K, int len_max = INF, int LB_max = INF) { vector<string> ss{""}; int idx = 0; vector<pii> piv_prv; repi(len, 0, INF) { dump("----------- len:", len, "--------------"); int L = sz(ss); int LB = min(L, LB_max); dump("L:", L); // (i,j) 成分が naive(ss[i] + ss[j]) であるような行列 mat を得る. Matrix<mint> mat(L, LB); rep(i, L) rep(j, LB) mat[i][j] = naive(ss[i] + ss[j]); //dump("mat:"); dump(mat); // mat に対して行基本変形を行いピボット位置のリスト piv を得る. auto piv = row_reduced_form(mat); dump("piv(", sz(piv), "):"); dump(piv); // rank の更新がなかったら必要な情報は揃ったとみなして打ち切る. if (len == len_max || (sz(piv) > 0 && sz(piv) == sz(piv_prv))) { int R = sz(piv); // 選択した行と列をそれぞれ昇順に並べて is, js とする(0 始まりのはず) vi is(R), js(R); rep(r, R) tie(is[r], js[r]) = piv[r]; sort(all(js)); // 基底の変換行列 P を得る. Matrix<mint> P(R, R); rep(i, R) rep(j, R) P[i][j] = naive(ss[is[i]] + ss[js[j]]); // P の逆行列 P_inv を得る. auto P_inv = inverse_matrix(P); // 各文字に対応する表現行列を得る. vector<Matrix<mint>> mats(K, Matrix<mint>(R, R)); rep(k, K) { char c = '0' + k; rep(i, R) rep(j, R) mats[k][i][j] = naive(ss[is[i]] + c + ss[js[j]]); mats[k] = mats[k] * P_inv; } // 雑に圧縮しようとしたけどあんま効いてない //mt19937_64 mt((int)time(NULL)); //uniform_int_distribution<ll> rnd(0, (ll)1e18); //rep(hoge, 10000) { // int i = rnd(mt) % sz(mats); // int j = rnd(mt) % sz(mats); // mats.push_back(mats[i] * mats[j]); //} //unordered_map<int, int> cnt; //rep(i, R) rep(j, R) cnt[mats.back()[i][j].val()]++; //dump(cnt); dump(sz(cnt)); exit(0); vector<tuple<int, int, mint>> elems; vi offsets{ 0 }; rep(k, K) { rep(i, R) rep(j, R) { if (mats[k][i][j] != 0) elems.emplace_back(i, j, mats[k][i][j]); } offsets.push_back(sz(elems)); } // 埋め込み用の文字列を出力する. auto to_signed_string = [](mint x) { int v = x.val(); int mod = mint::mod(); if (2 * v > mod) v -= mod; return to_string(v); }; string eb = "constexpr int DIM = "; eb += to_string(R); eb += ";\n"; eb += "constexpr int COL = "; eb += to_string(K); eb += ";\n"; eb += ""; eb += "tuple<int, int, VTYPE> matAs[] = {"; for (auto [i, j, v] : elems) { eb += "{"; eb += to_string(i); eb += ","; eb += to_string(j); eb += ","; eb += to_signed_string(v); eb += "},"; } eb.pop_back(); eb += "};\n"; eb += "int offset[COL + 1] = {"; repi(k, 0, K) eb += to_string(offsets[k]) + ","; eb.pop_back(); eb += "};\n"; eb += "VTYPE vecQ[DIM] = {"; rep(i, R) eb += to_signed_string(P[i][0]) + ","; eb.pop_back(); eb += "};\n"; cout << eb; exit(0); } // 基底ガチャ //mt19937_64 mt((int)time(NULL)); shuffle(ss.begin() + 1, ss.end(), mt); // 次に長い文字列たちを ss に追加する. int nidx = sz(ss); repi(i, idx, nidx - 1) rep(k, K) { ss.push_back(ss[i]); ss.back().push_back('0' + k); } idx = nidx; piv_prv = move(piv); } } template <class VTYPE> VTYPE solve(const string& s) { // --------------- embed_coefs() からの出力を貼る ---------------- constexpr int DIM = 28; constexpr int COL = 26; tuple<int, int, VTYPE> matAs[] = { 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}; int offset[COL + 1] = { 0,106,184,314,444,574,704,834,964,1094,1224,1354,1484,1614,1744,1874,2004,2134,2264,2394,2524,2654,2784,2914,3044,3174,3304 }; VTYPE vecQ[DIM] = { 0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,4 }; // -------------------------------------------------------------- // ここ以降は書き換えなくて良い. array<VTYPE, DIM> dp; dp[0] = 1; repi(i, 1, DIM - 1) dp[i] = 0; auto apply = [&](const array<VTYPE, DIM>& x, int col) { array<VTYPE, DIM> z; rep(i, DIM) z[i] = 0; repi(pt, offset[col], offset[col + 1] - 1) { auto [i, j, v] = matAs[pt]; z[j] += x[i] * v; } return z; }; repe(c, s) { dp = apply(dp, c - '0'); } VTYPE res = 0; rep(i, DIM) res += vecQ[i] * dp[i]; return res; } int main() { // input_from_file("input.txt"); // output_to_file("output.txt"); //【方法】 // 愚直を書いて集めたデータをもとに遷移行列を復元する. //【使い方】 // 1. mint naive(文字列) を実装する. // 2. embed_coefs(文字の種類数); を実行する. // 3. 出力を solve() 内に貼る. // 4. auto dp = solve<答えの型>(文字列) で勝手に DP してくれる. // embed_coefs(26, 2, INF); string s; cin >> s; rep(i, sz(s)) s[i] = s[i] - 'a' + '0'; dump("naive:", naive(s)); dump("======"); cout << solve<ll>(s) << "\n"; }