cp/codeforces/886/f.cc

258 lines
6 KiB
C++

#include <bits/stdc++.h> // {{{
// https://codeforces.com/blog/entry/96344
#pragma GCC optimize("O2,unroll-loops")
#pragma GCC target("avx2,bmi,bmi2,lzcnt,popcnt")
using namespace std;
template <typename T>
[[nodiscard]] static T MIN() {
return std::numeric_limits<T>::min();
}
template <typename T>
[[nodiscard]] static T MAX() {
return std::numeric_limits<T>::max();
}
template <typename T>
[[nodiscard]] static T sc(auto &&x) {
return static_cast<T>(x);
}
template <typename T>
[[nodiscard]] static T sz(auto &&x) {
return static_cast<T>(x.size());
}
#define prln(...) std::println(__VA_ARGS__)
#define pr(...) std::print(__VA_ARGS__)
#ifdef LOCAL
#define dbgln(...) std::println(__VA_ARGS__)
#define dbg(...) std::print(__VA_ARGS__)
#endif
inline static void NO() {
prln("NO");
}
inline static void YES() {
prln("YES");
}
using ll = long long;
using ld = long double;
template <typename T>
using ve = std::vector<T>;
template <typename T, size_t N>
using ar = std::array<T, N>;
template <typename T1, typename T2>
using pa = std::pair<T1, T2>;
template <typename... Ts>
using tu = std::tuple<Ts...>;
template <typename... Ts>
using dq = std::deque<Ts...>;
template <typename... Ts>
using qu = std::queue<Ts...>;
template <typename... Ts>
using pq = std::priority_queue<Ts...>;
template <typename... Ts>
using st = std::stack<Ts...>;
auto lb = [](auto... args) {
return std::lower_bound(args...);
};
auto ub = [](auto... args) {
return std::upper_bound(args...);
};
#define ff first
#define ss second
#define eb emplace_back
#define pb push_back
#define all(x) (x).begin(), (x).end()
#define rall(x) (x).rbegin(), (x).rend()
// }}}
#include <ext/pb_ds/assoc_container.hpp>
#include <ext/pb_ds/tree_policy.hpp>
using namespace __gnu_pbds;
// https://mirror.codeforces.com/blog/entry/124683
namespace hashing {
using i64 = std::int64_t;
using u64 = std::uint64_t;
static const u64 FIXED_RANDOM =
std::chrono::steady_clock::now().time_since_epoch().count();
#if USE_AES
std::mt19937 rd(FIXED_RANDOM);
const __m128i KEY1{(i64)rd(), (i64)rd()};
const __m128i KEY2{(i64)rd(), (i64)rd()};
#endif
template <class T, class D = void>
struct custom_hash {};
template <class T>
inline void hash_combine(u64 &seed, T const &v) {
custom_hash<T> hasher;
seed ^= hasher(v) + 0x9e3779b97f4a7c15 + (seed << 12) + (seed >> 4);
};
template <class T>
struct custom_hash<T,
typename std::enable_if<std::is_integral<T>::value>::type> {
u64 operator()(T _x) const {
u64 x = _x;
#if USE_AES
__m128i m{i64(u64(x) * 0xbf58476d1ce4e5b9u64), (i64)FIXED_RANDOM};
__m128i y = _mm_aesenc_si128(m, KEY1);
__m128i z = _mm_aesenc_si128(y, KEY2);
return z[0];
#else
x += 0x9e3779b97f4a7c15 + FIXED_RANDOM;
x = (x ^ (x >> 30)) * 0xbf58476d1ce4e5b9;
x = (x ^ (x >> 27)) * 0x94d049bb133111eb;
return x ^ (x >> 31);
#endif
}
};
template <class T>
struct custom_hash<T, std::void_t<decltype(std::begin(std::declval<T>()))>> {
u64 operator()(T const &a) const {
u64 value = FIXED_RANDOM;
for (auto &x : a)
hash_combine(value, x);
return value;
}
};
template <class... T>
struct custom_hash<std::tuple<T...>> {
u64 operator()(const std::tuple<T...> &a) const {
u64 value = FIXED_RANDOM;
std::apply(
[&value](T const &...args) {
(hash_combine(value, args), ...);
},
a);
return value;
}
};
template <class T, class U>
struct custom_hash<std::pair<T, U>> {
u64 operator()(std::pair<T, U> const &a) const {
u64 value = FIXED_RANDOM;
hash_combine(value, a.first);
hash_combine(value, a.second);
return value;
}
};
}; // namespace hashing
#ifdef PB_DS_ASSOC_CNTNR_HPP
template <class Key, class Value = null_type>
using hashtable = gp_hash_table<
Key, Value, hashing::custom_hash<Key>, std::equal_to<Key>,
direct_mask_range_hashing<>, linear_probe_fn<>,
hash_standard_resize_policy<hash_exponential_size_policy<>,
hash_load_check_resize_trigger<>, true>>;
#endif
#ifdef PB_DS_TREE_POLICY_HPP
template <typename T>
using multitree = tree<T, null_type, std::less_equal<T>, rb_tree_tag,
tree_order_statistics_node_update>;
template <class Key, class Value = null_type>
using rbtree = tree<Key, Value, std::less<Key>, rb_tree_tag,
tree_order_statistics_node_update>;
#endif
void solve() {
// division/math is weak point, but good amortized analysis
// should be able to evaluate/come up with S(n=10^5)
// instead of typing it into python
// series/real analysis weakness
// NOTE: better workflow for testing, i can't be certain if i would've tested
// with 10^5 numbers 1..10^5 because i was on an airplane, but i tested it now
int n;
cin >> n;
ve<ll> a(n);
hashtable<int, int> f;
for (auto &e : a) {
cin >> e;
++f[e];
}
ve<int> sieve(n + 1, 0);
for (auto [k, v] : f) {
ll K = k;
while (K <= n) {
sieve[K] += v;
K += k;
}
}
// TC: O(n + n + n / 2 + n / 3 + n / 4)
// with n <= 10^5, that's O(14 n), which should be fine
prln("{}", *max_element(all(sieve)));
/*
n + n / 2 + n / 3 + n / 4
1 + 1 / 2 + 1 / 3 + 1 / 4
a, 2a, 3a, 4a
b, 2b, 3b, 4b
c, 2c, 3c, 4c
looking for number most frogs hit
most frequent common multiple
can't scan frog hop distances
sort them
a
b
makes sense to choose earliest hop in common for now
lcm(a, b), ans = 2 (NOTE: if <= 10^9)
find c: trap: lcm(a, b, c), ans = 3
or don't: lcm(a, b), lcm(c) = c
^ prob dp?
binary search on place to trap, check if can trap:
time-wise yes
if can trap a at position x? x % a = 0
no monotonic search space?
consider iterating from trap=1..n
how many frogs can i trap?
number of frogs s.t. trap % frog = 0
*/
}
int main() { // {{{
cin.tie(nullptr)->sync_with_stdio(false);
cin.exceptions(cin.failbit);
int t = 1;
cin >> t;
while (t--) {
solve();
}
return 0;
}
// }}}