結果

問題 No.3507 RangeSum RangeUpdate RangeSqrt
コンテスト
ユーザー 👑 to-omer
提出日時 2026-04-17 22:35:55
言語 Rust
(1.94.0 + proconio + num + itertools)
コンパイル:
/usr/bin/rustc_custom
実行:
./target/release/main
結果
WA  
実行時間 -
コード長 24,835 bytes
記録
記録タグの例:
初AC ショートコード 純ショートコード 純主流ショートコード 最速実行時間
コンパイル時間 8,144 ms
コンパイル使用メモリ 188,196 KB
実行使用メモリ 19,712 KB
最終ジャッジ日時 2026-04-17 22:36:23
合計ジャッジ時間 16,195 ms
ジャッジサーバーID
（参考情報） 		judge1_1 / judge2_1
このコードへのチャレンジ
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ファイルパターン 結果
sample AC * 1
other AC * 28 WA * 1
権限があれば一括ダウンロードができます

ソースコード

diff #
raw source code 

code!{
pub fn solve() {
    crate::prepare!();
    define_enum_scan! {
        enum Query: u8 {
            0 => RangeSum { l: usize, r: usize },
            1 => RangeUpdate { l: usize, r: usize, x: usize },
            2 => RangeIsqrt { l: usize, r: usize },
        }
    }
    sc!(n, q, a: [usize; n], queries: [Query; q]);
    let mut seg = LazySegmentTree::<X>::from_keys(a.iter().cloned());
    for query in queries {
        match query {
            Query::RangeSum { l, r } => {
                if l == n {
                    continue;
                }
                let ans = seg.fold(l..r).0;
                pp!(ans);
            }
            Query::RangeUpdate { l, r, x } => {
                if l == n {
                    continue;
                }
                seg.update(l..r, (Some(x), 0));
            }
            Query::RangeIsqrt { l, r } => {
                if l == n {
                    continue;
                }
                seg.update(l..r, (None, 1));
            }
        }
    }
}
struct X;
impl Magma for X {
    type T = (Option<usize>, usize);
    fn operate(x: &Self::T, y: &Self::T) -> Self::T {
        if let Some(y0) = y.0 {
            (Some(y0), y.1)
        } else {
            (x.0, x.1 + y.1)
        }
    }
}
impl Associative for X {}
impl Unital for X {
    fn unit() -> Self::T {
        (None, 0)
    }
}
impl MonoidAct for X {
    type Key = usize;
    type Act = (Option<usize>, usize);
    type ActMonoid = X;

    fn act(x: &Self::Key, a: &Self::Act) -> Self::Key {
        let mut t = if let Some(a0) = a.0 { a0 } else { *x };
        for _ in 0..a.1 {
            if t <= 1 {
                break;
            }
            t = t.isqrt();
        }
        t
    }
}
impl LazyMapMonoid for X {
    type Key = usize;
    type Agg = (usize, usize, usize, usize);
    type Act = (Option<usize>, usize);
    type AggMonoid = (
        AdditiveOperation<usize>,
        MinOperation<usize>,
        MaxOperation<usize>,
        AdditiveOperation<usize>,
    );
    type ActMonoid = X;
    type KeyAct = X;

    fn single_agg(&key: &Self::Key) -> Self::Agg {
        (key, key, key, 1)
    }

    fn act_agg(x: &Self::Agg, a: &Self::Act) -> Option<Self::Agg> {
        if a.1 == 0 {
            if let Some(a0) = a.0 {
                Some((a0 * x.3, a0, a0, x.3))
            } else {
                Some(*x)
            }
        } else if x.1.isqrt() == x.2.isqrt() {
            let mut t = if let Some(a0) = a.0 { a0 } else { x.1 };
            for _ in 0..a.1 {
                if t <= 1 {
                    break;
                }
                t = t.isqrt();
            }
            Some((t * x.3, t, t, x.3))
        } else {
            None
        }
    }
}
crate::main!();
}
fn main()->std::io::Result<()>{use std::{env::temp_dir,fs::File,io::Write,process::{exit,Command}};let e=temp_dir().join("bin79BD43A6");let mut b=Vec::with_capacity(B.len()*8/6);let mut x=0;let mut t=vec![64;256];for i in 0..64{t[b"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"[i]as usize]=i as u8;}for(i,c)in B.iter().map(|&c|t[c as usize]).filter(|&c|c<64).enumerate(){x=match i%4{0=>c<<2,1=>{b.push(x|c>>4);c<<4}2=>{b.push(x|c>>2);c<<6}_=>{b.push(x|c);0}}}Write::write_all(&mut File::create(&e)?,&b)?;#[cfg(unix)]std::fs::set_permissions(&e,std::os::unix::fs::PermissionsExt::from_mode(0o755))?;exit(Command::new(&e).status()?.code().unwrap())}#[macro_export]macro_rules!code{($($t:tt)*)=>{}}const B:&[u8]=b"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";
0