// This code is generated by [cargo-atcoder](https://github.com/tanakh/cargo-atcoder)
// Original source code:
/*
use std::env;
use std::io::Read;

use intro_heuristics::*;
use intro_heuristics::algorithm::{AnnealingSearch, DoubleLocalSearch, LocalSearch, SearchContext, SearchState};
use intro_heuristics::io::*;
use intro_heuristics::math::{ArithmeticSequence, Sequence};

fn main() {
    let mut source = String::new();

    if let Ok(test_file_path) = env::var("TEST_FILE_PATH") {
        source = read_file(test_file_path.as_str());
    } else {
        std::io::stdin().read_to_string(&mut source).unwrap();
    }

    let contest_count = 26 as usize;

    input! {
        source = source,
        days: usize,
        costs: [u32; contest_count],
        satisfaction_map: [[u32; contest_count]; days],
    }

    struct Context {
        days: usize,
        costs: Vec<u32>,
        satisfaction_map: Vec<Vec<u32>>,
    }

    let context = Context {
        days,
        costs,
        satisfaction_map,
    };

    #[derive(Clone, Eq, PartialEq)]
    struct State {
        value: i64,
        schedule: Vec<Option<usize>>,
    }

    impl State {
        pub fn new(context: &Context) -> Self {
            let total_cost: u32 = context.costs.iter()
                .map(|cost| -> u32 {
                    let seq = ArithmeticSequence::new(
                        *cost,
                        *cost,
                        context.days,
                    );
                    seq.sum()
                })
                .sum();
            State {
                value: -(total_cost as i64),
                schedule: vec![None; context.days],
            }
        }
    }

    let add_contest = |state: &mut State, day: usize, contest_idx: usize| {
        let day = day as i32;
        let mut state = state;
        state.schedule[day as usize] = Some(contest_idx);
        let prev_idx = {
            let mut prev_day = day - 1;
            while prev_day >= 0 && state.schedule[prev_day as usize] != Some(contest_idx) {
                prev_day -= 1;
            }
            prev_day + 1
        };

        let next_idx = {
            let mut next_day = day + 1;
            while next_day < days as i32 && state.schedule[next_day as usize] != Some(contest_idx) {
                next_day += 1;
            }
            next_day + 1
        };

        let current_idx = day + 1;

        let cost = (current_idx - prev_idx) as i64 * context.costs[contest_idx as usize] as i64 * (next_idx - current_idx) as i64;
        state.value += cost;
        state.value += context.satisfaction_map[day as usize][contest_idx as usize] as i64;
    };

    let remove_contest = |state: &mut State, day: usize| {
        let mut state = state;
        let contest_idx = {
            if let Some(idx) = state.schedule[day] {
                idx
            } else {
                return;
            }
        };
        state.schedule[day as usize] = None;

        let day = day as i32;
        let prev_idx = {
            let mut prev_day = day - 1;
            while prev_day >= 0 && state.schedule[prev_day as usize] != Some(contest_idx) {
                prev_day -= 1;
            }
            prev_day + 1
        };

        let next_idx = {
            let mut next_day = day + 1;
            while next_day < days as i32 && state.schedule[next_day as usize] != Some(contest_idx) {
                next_day += 1;
            }
            next_day + 1
        };

        let current_idx = day + 1;

        let cost = (current_idx - prev_idx) as i64 * context.costs[contest_idx as usize] as i64 * (next_idx - current_idx) as i64;
        state.value -= cost as i64;
        state.value -= context.satisfaction_map[day as usize][contest_idx as usize] as i64;
    };

    impl SearchState for State {
        fn value(&self) -> f64 {
            self.value as f64
        }
    }

    let initial_state = State::new(&context);
    let mut state = initial_state;

    for day in 0..context.days {
        let contest_idx = day % contest_count;
        add_contest(&mut state, day, contest_idx);
    }

    let search_by_one_change = {
        #[derive(Clone)]
        pub struct TransitionParam {
            target_day: usize,
            contest_idx: usize,
        }
        let gen_transition_param = |_: &State, _: &SearchContext<State>| -> TransitionParam {
            let target_day = rand::random::<usize>() % days;
            let contest_idx = rand::random::<usize>() % contest_count;
            TransitionParam {
                target_day,
                contest_idx,
            }
        };
        let transition = |state: State, transition_param: TransitionParam| -> State {
            let mut state = state;
            remove_contest(&mut state, transition_param.target_day);
            add_contest(&mut state, transition_param.target_day, transition_param.contest_idx);
            state
        };
        #[derive(Clone)]
        pub struct UndoParam {
            target_day: usize,
            contest_idx: usize,
        }
        let gen_undo_param = |state: &State, transition_param: &TransitionParam| -> UndoParam {
            UndoParam {
                target_day: transition_param.target_day,
                contest_idx: state.schedule[transition_param.target_day].unwrap(),
            }
        };
        let undo = |state: State, undo_param: UndoParam| -> State {
            let mut state = state;
            remove_contest(&mut state, undo_param.target_day);
            add_contest(&mut state, undo_param.target_day, undo_param.contest_idx);
            state
        };

        AnnealingSearch::new(
            gen_transition_param,
            transition,
            gen_undo_param,
            undo,
            2e3,
            6e2,
        )
    };

    let search_by_two_opt = {
        #[derive(Clone)]
        pub struct TransitionParam {
            target_day_0: usize,
            target_day_1: usize,
        }
        let gen_transition_param = |_: &State, _: &SearchContext<State>| -> TransitionParam {
            let target_day_0 = rand::random::<usize>() % days;
            let target_day_1 = (target_day_0 + rand::random::<usize>() % 16).min(days - 1);

            TransitionParam {
                target_day_0,
                target_day_1,
            }
        };
        let transition = |state: State, transition_param: TransitionParam| -> State {
            let mut state = state;
            let day0_contest_idx = state.schedule[transition_param.target_day_0 as usize].unwrap();
            let day1_contest_idx = state.schedule[transition_param.target_day_1 as usize].unwrap();

            remove_contest(&mut state, transition_param.target_day_0);
            add_contest(&mut state, transition_param.target_day_0, day1_contest_idx);

            remove_contest(&mut state, transition_param.target_day_1);
            add_contest(&mut state, transition_param.target_day_1, day0_contest_idx);

            state
        };
        #[derive(Clone)]
        pub struct UndoParam {
            target_day_0: usize,
            contest_idx_0: usize,
            target_day_1: usize,
            contest_idx_1: usize,
        }
        let gen_undo_param = |state: &State, transition_param: &TransitionParam| -> UndoParam {
            UndoParam {
                target_day_0: transition_param.target_day_0,
                contest_idx_0: state.schedule[transition_param.target_day_0].unwrap(),
                target_day_1: transition_param.target_day_1,
                contest_idx_1: state.schedule[transition_param.target_day_1].unwrap(),
            }
        };
        let undo = |state: State, undo_param: UndoParam| -> State {
            let mut state = state;
            remove_contest(&mut state, undo_param.target_day_0);
            add_contest(&mut state, undo_param.target_day_0, undo_param.contest_idx_0);

            remove_contest(&mut state, undo_param.target_day_1);
            add_contest(&mut state, undo_param.target_day_1, undo_param.contest_idx_1);

            state
        };

        AnnealingSearch::new(
            gen_transition_param,
            transition,
            gen_undo_param,
            undo,
            2e3,
            6e2,
        )
    };


    let mut search = DoubleLocalSearch::new(
        search_by_one_change, 1,
        search_by_two_opt, 1,
    );

    let state = search.search(
        state,
        1800,
    ).unwrap();

    for contest_idx in &state.schedule {
        println!("{}", contest_idx.unwrap() + 1);
    }

    eprintln!("{}", state.value);
}
*/

fn main() {
    let exe = "/tmp/bin083DC004";
    std::io::Write::write_all(&mut std::fs::File::create(exe).unwrap(), &decode(BIN)).unwrap();
    std::fs::set_permissions(exe, std::os::unix::fs::PermissionsExt::from_mode(0o755)).unwrap();
    std::process::exit(std::process::Command::new(exe).status().unwrap().code().unwrap())
}

fn decode(v: &str) -> Vec<u8> {
    let mut ret = vec![];
    let mut buf = 0;
    let mut tbl = vec![64; 256];
    for i in 0..64 { tbl[TBL[i] as usize] = i as u8; }
    for (i, c) in v.bytes().filter_map(|c| { let c = tbl[c as usize]; if c < 64 { Some(c) } else { None } }).enumerate() {
        match i % 4 {
            0 => buf = c << 2,
            1 => { ret.push(buf | c >> 4); buf = c << 4; }
            2 => { ret.push(buf | c >> 2); buf = c << 6; }
            3 => ret.push(buf | c),
            _ => unreachable!(),
        }
    }
    ret
}

const TBL: &'static [u8] = b"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/";
const BIN: &'static str = "
f0VMRgIBAQAAAAAAAAAAAAIAPgABAAAAcARAAAAAAABAAAAAAAAAACjiBAAAAAAAAAAAAEAAOAAHAEAA
DwAOAAEAAAAFAAAAAAAAAAAAAAAAAEAAAAAAAAAAQAAAAAAAALgEAAAAAAAAuAQAAAAAAAAAIAAAAAAA
AQAAAAYAAAAAwQQAAAAAAADBZAAAAAAAAMFkAAAAAACUIAAAAAAAAEA8AAAAAAAAAAAgAAAAAAAEAAAA
BAAAAMgBAAAAAAAAyAFAAAAAAADIAUAAAAAAACQAAAAAAAAAJAAAAAAAAAAEAAAAAAAAAAcAAAAEAAAA
AMEEAAAAAAAAwWQAAAAAAADBZAAAAAAAAAAAAAAAAABIAgAAAAAAACAAAAAAAAAAUOV0ZAQAAACsaAQA
AAAAAKxoRAAAAAAArGhEAAAAAABMCwAAAAAAAEwLAAAAAAAABAAAAAAAAABR5XRkBgAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAFLldGQEAAAAAMEEAAAAAAAAwWQA
AAAAAADBZAAAAAAAAB8AAAAAAAAAHwAAAAAAAAEAAAAAAAAABAAAABQAAAADAAAAR05VAC1jWbRXr+ZI
GlLJ+0h4jT4KV+F1UFjDAEFXQVYxwEFVQVRJg8z/VVNJif5Mic9OjSwCSIPsSEiJNCRIiUwkCEyJ4UyJ
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AAAAAKDhZAAAAAAAlOEEAAAAAACgGwAAAAAAAAAAAAAAAAAAIAAAAAAAAAAAAAAAAAAAAHMAAAABAAAA
MAAAAAAAAAAAAAAAAAAAAJThBAAAAAAAEQAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAA
AwAAAAAAAAAAAAAAAAAAAAAAAACl4QQAAAAAAHwAAAAAAAAAAAAAAAAAAAABAAAAAAAAAAAAAAAAAAAA
";


Measured memory_bytes: 2976