Library to calculate difficulty and performance attributes for all osu! gamemodes.
A large part of rosu-pp
is a port of osu!lazer's difficulty and performance calculation
with emphasis on a precise translation to Rust for the most accurate results
while also providing a significant boost in performance.
Last commits of the ported code:
- osu!lazer :
8bd65d9938a10fc42e6409501b0282f0fa4a25ef
(2024-11-08) - osu!tools :
89b8f3b1c2e4e5674004eac4723120e7d3aef997
(2024-11-03)
News posts of the latest updates: https://osu.ppy.sh/home/news/2024-10-28-performance-points-star-rating-updates
// 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}");
Gradually calculating attributes provides an efficient way to process each hitobject separately and calculate the attributes only up to that point.
For difficulty attributes, there is GradualDifficulty
which implements Iterator
and for performance attributes there is GradualPerformance
which requires the current
score state.
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());
rosu-pp
was tested against all current beatmaps on multiple mod combinations and delivered
values that matched osu!lazer perfectly down to the last decimal place.
However, there is one small caveat: the values are only this precise on debug mode.
On release mode, Rust's compiler performs optimizations that produce the tiniest discrepancies
due to floating point inaccuracies which can cascade into larger differences in the end.
With this in mind, rosu-pp
is still as accurate as can be without targeting the
.NET compiler itself. Realistically, the inaccuracies in release mode are negligibly small.
An important factor for rosu-pp
is the calculation speed. Optimizations and an accurate translation
unfortunately don't always go hand-in-hand. Nonetheless, performance improvements are still
snuck in wherever possible, providing a significantly faster runtime than the native C# code.
Results of a rudimentary benchmark of osu!lazer and rosu-pp:
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
Flag | Description | Dependencies |
---|---|---|
default |
Enables the compact_strains feature |
|
compact_strains |
Storing internal strain values in a plain Vec introduces an out-of-memory risk on maliciously long maps (see /b/3739922). This feature stores strains more compactly, but comes with a ~5% loss in performance. | |
sync |
Some gradual calculation types can only be shared across threads if this feature is enabled. This adds a performance penalty so only enable this if really needed. | |
tracing |
Any error encountered during beatmap decoding will be logged through tracing::error . If this feature is not enabled, errors will be ignored. |
tracing |
Using rosu-pp
from other languages than Rust:
- JavaScript: rosu-pp-js
- Python: rosu-pp-py