rosu-pp

用于计算所有 osu! 游戏模式的难度和表现属性的库。

rosu-pp 的很大一部分是将 osu!lazer 的难度和表现计算移植过来，重点在于将代码精确地翻译为 Rust 以获得最精确的结果，同时提供显著的性能提升。

移植代码的最新提交

• osu!lazer : 7342fb7f51b34533a42bffda89c3d6c569cc69ce (2022-10-11)
• osu!tools : 146d5916937161ef65906aa97f85d367035f3712 (2022-10-08)

最新游戏模式更新新闻

• osu: https://osu.ppy.sh/home/news/2022-09-30-changes-to-osu-sr-and-pp
• taiko: https://osu.ppy.sh/home/news/2022-09-28-changes-to-osu-taiko-sr-and-pp
• catch: https://osu.ppy.sh/home/news/2020-05-14-osucatch-scoring-updates
• mania: https://osu.ppy.sh/home/news/2022-10-09-changes-to-osu-mania-sr-and-pp

使用方法

// Decode the map
let map = rosu_pp::Beatmap::from_path("./resources/2785319.osu").unwrap();

// Calculate difficulty attributes
let diff_attrs = rosu_pp::Difficulty::new()
    .mods(8 + 16) // HDHR
    .calculate(&map);

let stars = diff_attrs.stars();

// Calculate performance attributes
let perf_attrs = rosu_pp::Performance::new(diff_attrs)
    // To speed up the calculation, we used the previous attributes.
    // **Note** that this should only be done if the map and all difficulty
    // settings stay the same, otherwise the final attributes will be incorrect!
    .mods(24) // HDHR, must be the same as before
    .combo(789)
    .accuracy(99.2)
    .misses(2)
    .calculate();

let pp = perf_attrs.pp();

// Again, we re-use the previous attributes for maximum efficiency.
let max_pp = perf_attrs.performance()
    .mods(24) // Still the same
    .calculate()
    .pp();

println!("Stars: {stars} | PP: {pp}/{max_pp}");

逐步计算

逐步计算属性提供了一种有效的方法来单独处理每个 hitobject 并仅计算到该点的属性。

对于难度属性，有 GradualDifficulty 实现了 Iterator，而对于表现属性，有 GradualPerformance 需要当前的分数状态。

use rosu_pp::{Beatmap, GradualPerformance, Difficulty, any::ScoreState};

let map = Beatmap::from_path("./resources/1028484.osu").unwrap();

let mut gradual = Difficulty::new()
    .mods(16 + 64) // HRDT
    .clock_rate(1.2)
    .gradual_performance(&map);

let mut state = ScoreState::new(); // empty state, everything is on 0.

// The first 10 hitresults are 300s
for _ in 0..10 {
    state.n300 += 1;
    state.max_combo += 1;
    let attrs = gradual.next(state.clone()).unwrap();
    println!("PP: {}", attrs.pp());
}

// Fast-forward to the end
state.max_combo = ...
state.n300 = ...
state.n_katu = ...
...
let attrs = gradual.last(state).unwrap();
println!("PP: {}", attrs.pp());

准确性

rosu-pp 在多种 mod 组合下与所有当前 beatmap 进行了测试，并提供了与 osu!lazer 完全匹配的值，精确到小数点后最后一位。

然而，有一个小注意事项：只有在调试模式下，值才如此精确。在发布模式下，Rust编译器会进行优化，这可能导致由于浮点数不精确而产生微小的差异，最终可能会放大。考虑到这一点，rosu-pp在不针对.NET编译器本身的情况下，尽可能精确。实际上，发布模式下的不精确性可以忽略不计。

速度

rosu-pp的一个重要因素是计算速度。优化和精确翻译并不总是相辅相成。不过，仍然尽可能地进行了性能改进，提供了比原生C#代码显著更快的运行时。

osu!lazer和rosu-pp的简单基准测试结果

osu!lazer:
Decoding maps:            Median: 378.10ms | Mean: 381.47ms
Calculating difficulties: Median: 588.89ms | Mean: 597.11ms
Calculating performances: Median: 315.90µs | Mean: 310.60µs

rosu-pp:
Decoding maps:            Median: 46.94ms | Mean: 47.21ms
Calculating difficulties: Median: 72.90ms | Mean: 73.13ms
Calculating performances: Median: 44.13µs | Mean: 45.53µs

特性

绑定

使用除Rust以外的语言使用rosu-pp

• JavaScript：rosu-pp-js
• Python：rosu-pp-py