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レールガンディーゼル †#include <bits/stdc++.h> #include <sys/time.h> using namespace std; #define rep(i,n) for(long long i = 0; i < (long long)(n); i++) #define repi(i,a,b) for(long long i = (long long)(a); i < (long long)(b); i++) #define pb push_back #define all(x) (x).begin(), (x).end() #define fi first #define se second #define mt make_tuple #define mp make_pair template<class T1, class T2> bool chmin(T1 &a, T2 b) { return b < a && (a = b, true); } template<class T1, class T2> bool chmax(T1 &a, T2 b) { return a < b && (a = b, true); } using ll = long long; using vll = vector<ll>; using vvll = vector<vll>; using P = pair<ll, ll>; ll ugauss(ll a, ll b) { if (!a) return 0; if (a>0^b>0) return a/b; else return (a+(a>0?-1:1))/b+1; } ll lgauss(ll a, ll b) { if (!a) return 0; if (a>0^b>0) return (a+(a>0?-1:1))/b-1; else return a/b; } template <typename T, typename U> ostream &operator<<(ostream &o, const pair<T, U> &v) { o << "(" << v.first << ", " << v.second << ")"; return o; } template<size_t...> struct seq{}; template<size_t N, size_t... Is> struct gen_seq : gen_seq<N-1, N-1, Is...>{}; template<size_t... Is> struct gen_seq<0, Is...> : seq<Is...>{}; template<class Ch, class Tr, class Tuple, size_t... Is> void print_tuple(basic_ostream<Ch,Tr>& os, Tuple const& t, seq<Is...>){ using s = int[]; (void)s{0, (void(os << (Is == 0? "" : ", ") << get<Is>(t)), 0)...}; } template<class Ch, class Tr, class... Args> auto operator<<(basic_ostream<Ch, Tr>& os, tuple<Args...> const& t) -> basic_ostream<Ch, Tr>& { os << "("; print_tuple(os, t, gen_seq<sizeof...(Args)>()); return os << ")"; } ostream &operator<<(ostream &o, const vvll &v) { rep(i, v.size()) { rep(j, v[i].size()) o << v[i][j] << " "; o << endl; } return o; } template <typename T> ostream &operator<<(ostream &o, const vector<T> &v) { o << '['; rep(i, v.size()) o << v[i] << (i != v.size()-1 ? ", " : ""); o << "]"; return o; } template <typename T> ostream &operator<<(ostream &o, const deque<T> &v) { o << '['; rep(i, v.size()) o << v[i] << (i != v.size()-1 ? ", " : ""); o << "]"; return o; } template <typename T> ostream &operator<<(ostream &o, const set<T> &m) { o << '['; for (auto it = m.begin(); it != m.end(); it++) o << *it << (next(it) != m.end() ? ", " : ""); o << "]"; return o; } template <typename T> ostream &operator<<(ostream &o, const unordered_set<T> &m) { o << '['; for (auto it = m.begin(); it != m.end(); it++) o << *it << (next(it) != m.end() ? ", " : ""); o << "]"; return o; } template <typename T, typename U> ostream &operator<<(ostream &o, const map<T, U> &m) { o << '['; for (auto it = m.begin(); it != m.end(); it++) o << *it << (next(it) != m.end() ? ", " : ""); o << "]"; return o; } template <typename T, typename U, typename V> ostream &operator<<(ostream &o, const unordered_map<T, U, V> &m) { o << '['; for (auto it = m.begin(); it != m.end(); it++) o << *it; o << "]"; return o; } vector<int> range(const int x, const int y) { vector<int> v(y - x + 1); iota(v.begin(), v.end(), x); return v; } template <typename T> istream& operator>>(istream& i, vector<T>& o) { rep(j, o.size()) i >> o[j]; return i;} template <typename T, typename S, typename U> ostream &operator<<(ostream &o, const priority_queue<T, S, U> &v) { auto tmp = v; while (tmp.size()) { auto x = tmp.top(); tmp.pop(); o << x << " ";} return o; } template <typename T> ostream &operator<<(ostream &o, const queue<T> &v) { auto tmp = v; while (tmp.size()) { auto x = tmp.front(); tmp.pop(); o << x << " ";} return o; } template <typename T> ostream &operator<<(ostream &o, const stack<T> &v) { auto tmp = v; while (tmp.size()) { auto x = tmp.top(); tmp.pop(); o << x << " ";} return o; } template <typename T> unordered_map<T, ll> counter(vector<T> vec){unordered_map<T, ll> ret; for (auto&& x : vec) ret[x]++; return ret;}; void vizGraph(vvll& g, int mode = 0, string filename = "out.png") { ofstream ofs("./out.dot"); ofs << "digraph graph_name {" << endl; set<P> memo; rep(i, g.size()) rep(j, g[i].size()) { if (mode && (memo.count(P(i, g[i][j])) || memo.count(P(g[i][j], i)))) continue; memo.insert(P(i, g[i][j])); ofs << " " << i << " -> " << g[i][j] << (mode ? " [arrowhead = none]" : "")<< endl; } ofs << "}" << endl; ofs.close(); system*1; } struct timeval start; double sec() { struct timeval tv; gettimeofday(&tv, NULL); return (tv.tv_sec - start.tv_sec) + (tv.tv_usec - start.tv_usec) * 1e-6; } size_t random_seed; struct init_{init_(){ ios::sync_with_stdio(false); cin.tie(0); gettimeofday(&start, NULL); struct timeval myTime; struct tm *time_st; gettimeofday(&myTime, NULL); time_st = localtime(&myTime.tv_sec); srand(myTime.tv_usec); random_seed = RAND_MAX / 2 + rand() / 2; }} init__; #define ldout fixed << setprecision(40) #define EPS (double)1e-14 #define INF (ll)1e18 #define mo (ll)(1e9+7) vll f(ll x) { vll ret;
while (x) {
ret.pb(x % 10);
x /= 10;
}
rep(_, 3) ret.pb(0);
return ret;
} int main(void) { ll n; cin >> n;
for (int x : {-4000, -2000, 0, 2000})
for (int z : {0, -100})
for (int w : {0, 100})
for (int a : {0, -100, -200, -150, -120})
{
ll sum = n + x + z + w + a;
auto ret = f(sum);
if (ret[1] == ret[2] && ret[2] == ret[3]) {
cout << "3: " << sum << " " << mt(x, z, w, a) << endl;
}
if (ret[2] == ret[3]) {
cout << "2: " << sum << " " << mt(x, z, w, a) << endl;
}
}
return 0;
} ``` セーブデータ †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?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?+O+5AmBKB3BZ4axg0ZdCOWJKSGV/3ZeEYVClScOGY14dN9V83aKOBGsYFAZAu5XAC7Kwb8Tyw7js9tegUbcA/4FBGn6XAVP5eM9F4d3YF3Mds7RCmHH3LTfy+YtwXgdvrN+6zDlLPjAAtiCs1cL9aJxu0RiDai70beHMXmwYGvMRKPaHFZVBhVuBl48rnxBCLuFc6GazDuQlx?/AXHkHigPoVtMBAC8wzg7aeBk6ECpagug0Bt8wxNidUhNQht4RwVwercqO+NdweQNe41b688SV4pJyQPCJM8R31JDPRKBP8QEM5WGW+u7/FH2/d9Yh7BdJD9F9aRT9cxLho0k8/06MIIpgYVmQOUQdpBADSwQCisQg?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?+8Y134lggSwAQSlC+TgLOJQKLB4T6KddkS/iTyYIMTtTsTItKtdg?/BKhn4ksIt5BVyni18ahKTqTaT1LMK5MgpmTuTHhjMuS2SiQnzwSoKyAhSRTFSxSZBJTUzx1pT/hEA5SQhxMI0SIYN/Ap8CIHTMhtTzBLT9S/dgqDAbTbzFSwq9TrSiJbSppXLoyoq3BNyoT+gFQfTMqY0ZhoSvTVVfTOAir/AAyeIaKsBF8wyIyIcoyGKpyszEzGBky7TUrGrlyszNhczq0aiShL9iyACBLyzMjo0ShdjsNrtZF6yA8QpmzWz2yvdW11yeymQSgw1OrBzCtDCCJ/yJyBzpzDy?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?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?+3AWJyqg16quQWqquk1hlS1uutJ/NjJjenM7JyqBIPJkMYap13uyskpqEcpmojoL1sehlX1hpkG1awNsd1pijuNr+wKGNlJmcoBhc2NvekZg?+7Ok+p6/c2ZjN+ZmCRZrI5ZvNhDwG9ZuB6MrZ5e747p8t/Cd87pht0CiB+t9ll8bG4zo8ttpBztzYp52Yl5t6oCd5gjPBkdxm35i4s4sdwFmdwj+dxh9MwW+hkWph9diWuF6WhFgiL9ziXh1Fo9jFwR4Rs9sRgieS/WvEol?+oIYXAO8YyRgNsclu95ey26lx9xR+lkyj9izfR99nkoxjLjln98jv980pgQDi4YD+V0D4VmDzUlxkrKD+O1DxVgJoxhV5DoxrO8ZzksJkICJ0qwujbvDvVgjlVcu4jxJ6u8j5u5qqjgzvGmTnq?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?/1/6iiXxdqXp42L5d4WqFgr2S48UVe3dXdgrU16HtteuXE9nr21oG98WdtK9sahvZ1dze8bKllb2a5207ebXB3oqU65O9P27LV3r+3d5+0hufLX3gKwm4R1RWwfSDhKzD5Glo+ArJDqwLW5x9U+2VLbtEB24HcU+uHfDhn06pGtSOufGTua3x7idMmdHPMqXxfid1Xu2BNjhoU+4xBvuxaa7M/HkIN9qm49RakDxnoBt2+VEBeou0uoW94egzbatG2h6I8rByPfbqp2maT8jKmPG+rPwfr6dzShbc0qZ3X5yc/6FPazkc136Il7OdPdXk52P5N03OrPJwrkG7ZX8EiWFFCKhC7y4AH+DNb4CTRf5i8ReVUD/tcWhIgt?+ai7WXgAOl7QtFeKXDhmALV57sv+z5LXt5B15Ys4BojC9kb1ywm8zeGlKwQ+3UYtdn2eAsygQIsr4CLMLvTlmQMsae83K3vIOqNz97jcA+dAzgOlRD7uMpuLApVovzMDsD9hKHcPsE1w4J9wmSfAQTh3aLCD4m2fcQUyyL5SCDhMg2jjawe4KDy+ygnuhWTUELQEQtfdIfX1ZANl9B/HQwS32B5t9W0AIrvg4IwED95Od3TetJ1DaOCR+zg1Hq4IvpT9iAn1aUtm1065s8erwvwUYwCFf0N+EbLfpTxs7hC62UQpoUf2bZM 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?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?/KkxJWkJjnZSYh4dxJuaeyG6GY3plkz9klxnuzHE6SoPEmHRccl07QSOFkk1jm+T0tQC9MbElxzBbwjphDR0moLM59C7OfZN7F5zgZz1UGYaHBlZs76UM21D4Nhk2SKRdkjLCpHJ5a8ye9I1yTTw8nMi253krgLjPP6xAVIl/AebyMIVkywpFMx/hoMvEf9ziei2KZ/zvHSjyhaU1mSvI5mbt2GG8r8a5L7mFSK2f4vediyAkID9RPQ8CQlhqlhY6pMErAZaJvkKybRqs6MihI6mOjn53UrWe?/M9H9S1h38k2RFVGn/zI6C3S2W5Sj4UTZpC3NVjwJYn8D4xfYtiaIPgXncPZO0r2a8J9loLsx3wTvFhgr44KxqeC0OVdPizEKHppCx?+c9ITmUKGlKc1sfZPTmw8jKoy2hWuVzlJsx?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?/QtEqaWG79ccvpY/oGWOGX9X+huX3w/2eGXD3hp7eP38P/6XNgBtzcAcD2gHJlfcqI/UZiO1Hv1h/X9R3LC3KLHUKBoKUPP0MYHPAwoxLVPP+Z9zxelDQvalLKNy92Z+OuoYmsr0QC6jFbQWSVIAk30ytbRpg8bQawdHZx5o1vRwcZK9GJhdGqUq1v70UC4lQh8Y0qUmPDS+tLayfXMekOvDZDyxhQ3RNl2XDptGxh2eypV3bHFtMm1MdoZqW6HlNCIVTfmN23irvgrrbTZ6xuNySrdRm8Y+ymcPDLXDyIhhdZo?+MOmvj9m57X/rxE+6Z+Fk7yPPwD1hGQTF8hubSMkVhDXJe/eI7+ESN/qu5qR4mqop7aw7PuT+TIfFrwNENktXI3E4QaQ0/KiTsayo6SaJ0MawGlJtFrQfr2izG9jJhYM3q/qs1at8E5nZ3vNI8He9fBt3gIcWF1rhTgrcOj?/OImBRSJFK+Y8Nol0z75D0uibRAqKUzaN9aprfZax31aG5NB+tMnqcOiMdTjLSjTShE45mH2UN+/TVaZ6XW6ROsQZIB9Ku1v7P97xp058d1U+Giunu9HsOLe2+mgjlkx9S/RANuUEZeB8E84qB0FaAtTIhWrGbhPxmAN+M0NITNQPBSEQaJ+mlgef4/NcD7/PPRhZKP5nMtli0vbUK5mlnGhCtag?/XLw2NG6T9B8rcRqUooCWDDB00V/RUaM6WznBts9wZ73O8OdcwgfYKbGPeiklUhyU4cN40iX+NixycwsamMznFDk2pU+sZYmqn1pcCnYxUtHXrnVtBxlujrpqLzBDTs6gsecZKbzASxiBeYLptv1nnDN0Ih4w4fmD2nbNrx9wy6cfNunnz3xuZV7u9OBGVlgJskf?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?/JggjHez9doh43ZIcSmW75DyiZQ/n2Ok+btDvuwOs32D2RbTwzXTofYcT3rHU9g3Tw9MuSSlb1jxexbpO0r27LZ12MRveu1b2bretp849o9OH2fLH5n06OLetAGL7n1q+39pvvRG9HZFgx67ZjPu20yiB/GUdMsd?+33SqewdnY9QuIyVI0U7K+KPyNJSSa7j/CyQYqNEWfHlBhWmVYCfk7SpEM+k+LJI3E2Gr7J9i5ybLuNb2rWKxJzEv4sEPP56Tpm1KaGujm?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?+rMhPGDYT5gxE60poOUzVG2J1xZ5OdmfXeD90ak8EsN3IXPN8QyOfJWhuZLFpL9x3YmurGiniukpwPbUuandjy1sD+LYg9puoPWHup+fv3PQf9r0Hwt7cdsMgBztCHnp3eerfb3CPuH/e74dNtH3zbJ9oV+fY7e0fJl4B+cVANCsNtDlkex?+7EI9txW2eyc7jymZlQjQ9nfPAT5mfndxTAHS73K0a5Q3o3bnsnigzUfvuKfKzKn?+B4fPU/HuUBp7r58Udde6fUVcTwzzxa7MmfsJdd8zxC5ffBusnZDj9zKbGu5Kf3LnqbQB/c9Af0yq55N1pb8+bnqnehrirB/qcmX9Lkq/N1xRQ9tO1b1p0t2vd7A4epHtb6625YB9G3iPDb0j8o8taqP711HjRyvy0f0fCv5V/t5jSjOGPVn8r0G4q848JWMjOz?/fJq8wOIz4b+Rwxd5HF7AOUb2O7rzc68dmu5Pvjx58nYIhwPgnCD8b46+NqnzD36Ar+qop0+Ub5vBnr10Z69qzD73+D/1+C8DeWfhr1n8Nyzdl+t29vCLg77zfktzm0X8b5c+d6Tc4vfPWu8e3d5mDBezjObmVIute8FVVbxbr72I5+/xfdbNgwHwR+B9Ef63+q9L3y/I8tvllajnL+ss7fE9JlCPgHWHqY/lmWP6PtjyY69vVfIbuPtAwCtscZmhoIXdr4YqcfXF2JknmOwVdXnZT6fDz5j0N93f4bVPbPkrkTYLtsGujvzjvfp?/LvxOOrNN5jQ+7M9PuLPm3qz9xps/iX2b3NhzxG7Dfd+0OhT478U9m0eeFrXnjS3sdYeaXIPRv/Alm7JcOotNlvpIO96Lc2GztjL/SwIRZe9PEv/Tp3yD/d8H3wfV6lRxbb98hG/zl9rtyGdD2Sunb27kHTCYx+V 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?/zZDL6G6LuiMsf7G9RsGTIRejyIZKBlDmhY4kXdzib6OuJCIldxqjjXOqNp8+vao1BjMaavSK8IYtxXQCK/LO1p1TQ/mJfBSA0oIoCAXW9z71BowzCxiO/DbzGjpjUSNmM0QiSMc9iYroNJjloiBUpj5I0kJpjp/UYIZj99UQJpDJglmPUD5g+MM5c3dBRwuiUw?/QL5jC7VdhlQnDJ6LahRYwSAtwLLU/RFiuwjOIdx58D4k3JLgGXRCCZcNPRtI3o/S1ZBXAV6lABlgciDCobMEAGIw+IBcCVBEUTsDeADcEAGcxAAfpjAAZDNKwDRnTROgcCKFiSxEACYimILCCyxgg5OM3whqZOO0JgwOAinAsIDCOQAeoXYHiB7AZkDiBQgCokzB1oV1FVRYUXsAHBcEaInsBKY5OKmArpdECAAA= 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